In January, we responded to the Lazarus Group’s novel attack campaign against South Korea, which followed last year’s Operation SyncHole. In this new operation, the group employed an updated malware chain that included both their old and new malware, which we disclosed in full, and used another mandatory South Korean security software program as a part of infection chain using a watering‑hole strategy. Notably, the group targeted victims more selectively, sending spear‑phishing emails with links to fabricated but relevant sites, such as portfolio and résumé pages tailored to each target. We dubbed this activity Operation FlashHole.

Our examination reveals that the earliest evidence of this new operation dates back to July 2025. This suggests the group began preparing for the campaign shortly after ending Operation SyncHole, which lasted at least four months. We identified a minimum of three organizations impacted by the campaign in South Korea’s software, construction, and wired communication equipment manufacturing sectors. These sectors differ from those affected by Operation SyncHole, indicating that the group has expanded its target scope over time.

Background

After more than a year since the first observation of Operation SyncHole, we detected a suspicious execution chain originating from legitimate South Korean software. This chain mirrors the one from the previous operation; however, this time, the attacker abused CrossWeb EX instead of Cross EX, which was abused in Operation SyncHole. Both applications appear to be maintained by the same vendor, and both are related to financial security. CrossWeb EX is a financial security solution that is required to access widely used online banking and government websites. It encrypts communications between the user’s browser and the web server using public key infrastructure (PKI). This is not the first time Lazarus has abused this software. It was also used in 2021 to deploy the Racket downloader and again in 2022 and 2023. Although the exact method by which CrossWeb EX was abused remains unclear, we determined that the attack chain ultimately leads to the execution of the malware in memory.

We noted that the spawned process was running with a high integrity level. The parent process, INISAFECrossWebEXSvc.exe, originates from the installation bundle of INISAFE CrossWeb EX V3 version 3.4.1.2, released in 2023 after KrCERT’s public advisory.

As we already mentioned in our SyncHole blog post, this pattern closely mirrors the long‑standing strategy employed by the Lazarus Group to target South Korea. Since CrossWeb EX and similar software is mandatory for South Korean users and typically runs in the background to interact with the browser, it has been leveraged as a critical attack vector by the group. In 2025, a paper was presented at the USENIX Security Symposium that investigated vulnerabilities in South Korea’s mandatory security software and demonstrated how such software can unintentionally create a massive attack surface.

In July 2026, the South Korean government and several local security vendors also published a joint security advisory covering typical Lazarus attack techniques, including exploitation of financial security software. While this advisory overlaps with our findings from Operation FlashHole and Operation SyncHole, and AhnLab’s detailed analysis report Operation Double Barrel covers a wide range of recent Lazarus Group activities, we are conducting a more granular classification based on their TTPs. We will discuss this further in the attribution section.

Initial infection vector

Although we could not precisely determine what triggered the infection chain, our analysis uncovered a suspicious website hosted on GitHub Pages that is associated with the GitHub account used as the C2 channel. The GitHub account was created last September, and the initial version of the site was designed to showcase the résumé of a senior network appliance developer. In January, however, this site was replaced with another featuring an interior design showcase. The first site was likely accessed by an employee of a wired communication manufacturing company, while the second site likely affected a target in the construction sector.

The first site with the résumé had a photograph supposedly of a job seeker, but the lack of EXIF metadata and the unnatural texture of the image indicate that it was generated by AI. This suggests the Lazarus Group has incorporated AI into its long‑standing strategy, like other Korean‑speaking threat actors (1, 2). The group most likely also used AI to create the lure site: the job seeker’s name resembles the Korean version of “John Doe,” and the portfolio was populated with seemingly meaningless details and random companies. The generated site was then manually tailored to specific targets.

The websites contained embedded links that loaded an external JavaScript file via a script tag.

• Malicious link embedded in the résumé site: hxxps://javadevhouse.co[.]kr/ajax/libs/jquery/1.7.3/jquery.min.js
• Malicious link embedded in interior design site: hxxps://pythonapischool[.]com/api/detach

Based on the analysis, we assess with medium-to-high confidence that the targets received phishing emails containing links to the malicious site hosted on GitHub Pages (using the domain <username>.github.io). The research results showed a high possibility that visiting the malicious site initiated an infection process involving CrossWeb EX software. This assessment aligns with Lazarus’s recent approach, as detailed in the joint advisory published by the South Korean government and security companies.

Full infection chain

Following the initial compromise, the legitimate Windows binary fsquirt.exe was executed under the CrossWeb EX process and injected with shellcode containing a malicious DLL – TechHub malware. From our extensive and thorough examination, we identified several malicious payloads and reconstructed the complete infection chain. The infection chain is rather complex and reveals the Lazarus Group’s advanced operational techniques on targeted hosts. These techniques conceal their malicious payloads, intent and their sophisticated malware delivery framework. The latter was updated extensively compared to the previous campaign, despite the new operation starting less than a year later. Significantly, the execution chain below exists only in memory during the initial infiltration, highlighting the attackers’ considerable efforts to hide the initial compromise.

Following the initial compromise, the group sought to maintain persistence on the network by installing a pair of malware strains – TouchHub and TouchShift – leveraging DLL side‑loading under the name mscoree.dll. TouchHub was deployed by the first instance of TechHub. It then used DLL side-loading to launch TouchShift, which led to the in‑memory execution of another TechHub instance. After launching the second time, TechHub deployed another pair, ClientHub and LPEClient, rather than executing Cubridge directly. Only minimal traces of these files were found on disk; the remainder of the malicious code persisted exclusively in memory.

Since Cubridge remains only in memory at the initial compromise stage, we suspect the group designed this indirect, multistage chain to deliberately redeploy Cubridge after gaining persistence, as it serves as the most sophisticated orchestrator of the attack.

Malware set

The full chain comprises advanced variants of the known Lazarus malware strains, including TechHub, Cubridge, TouchShift, LPEClient, and the newly identified TouchHub and ClientHub.

TechHub – the start of the chain

TechHub, a downloader that plays a central role in this attack, communicates with GitHub using a Personal Access Token (PAT). It serves as the initial payload, providing the top of the chain with sufficient functionality to profile compromised hosts and facilitate subsequent payloads.

This variant is a more advanced version of the malware named CLOUDBURST by Mandiant and NickelLoader by ESET. According to their reports, the earlier version communicated with a C2 server via HTTP(S) to fetch additional payloads. The latest iteration we found, however, communicates with GitHub instead and has updated command strings.

We identified three variants of TechHub in the chain: an in‑memory version, a simple DLL side‑loading version, and a DLL side‑loading version that uses a registered Windows service. Depending on which stage loads the malware, it contacts a private GitHub repository via the GitHub API using either hard‑coded credentials or credentials retrieved from its configuration file.

When TechHub loads, it creates a 4‑byte hexadecimal identifier (ID) in the range 0x1000–0xFFFF or reads one from the configuration file, enabling the attackers to distinguish between compromised hosts. TechHub then checks a GitHub issue by sending the request GET /issues?state=[open/closed] to determine whether any previous communication remains active and removes any traces of it if found. It then proceeds with the handshaking process.

1. It creates a new issue titled 1[ID] with the body “hel” using the POST /issues request, and sets its status to open.
2. It then retrieves a file from the repository containing the 2[ID] value in its name. This file contains the RSA public key.
3. It generates a random 16‑byte XOR key, encrypts it with the provided RSA public key, and uploads the result, prefixed with 1[ID], to the repository.
4. The hard‑coded IV is XORed with the generated 16‑byte key and then used after the handshake.

During file exchange, filenames follow the pattern [1|2][ID][random-16-byte-key] throughout communication. The “2” prefix indicates delivery from the repository to TechHub, while “1” indicates delivery from TechHub to the repository. The random 16‑byte key in the filename is used for AES encryption or decryption of each file’s contents, employing either a hard‑coded IV or an updated IV.

After the key exchange is complete, TechHub reads a file with the prefix “2” once again and verifies that the delivered data equals “hel”. If the check passes, TechHub gathers extensive information from the infected host. This data is then encrypted and sent to the repository. After transmitting the device information, the process concludes by updating the body of the previously created issue from “hel” to “hey” using PATCH /issues/[issue number]. The malware is now fully prepared to receive commands from the repository.

TechHub supports four commands. The laeca command deploys a payload packaged in shellcode that reflectively loads the embedded payload directly into memory.

Command	Description
mqdrz	Collect information about the device and its running processes
laeca	Directly invoke the received shellcode in memory
aqvxp	Terminate the current process
rtcya	Beaconing after finishing the handshake process

Cubridge – the framework orchestrator

Cubridge, deployed via TechHub on the compromised host, is capable of retrieving various payloads through multiple methods. It serves as the central orchestrator of the entire malware framework, supporting a range of plugins, modules, and tools. An earlier version of Cubridge was also disclosed in the reports covering the previous version of TechHub. In those reports, Mandiant identified it as SIDESHOW, and ESET identified one of its modules as LightlessCan.

To establish communication with the C2 server, Cubridge randomly selects one of the predefined C2 servers and constructs a dedicated C2 URL for every request, using the pattern [C2_URL]/[page1]/[page2]/[page3]. This is achieved by concatenating terms from predefined word lists. Our analysis identified a single hardcoded C2 server – hxxps://cubedesign[.]co[.]kr/news/AABBCC – associated with the examined instance that is configured to version 5.1. During URL generation, AABBCC is substituted with a null value. The page3 segment is assigned a randomly generated integer between 10000000 and 99999999. Consequently, each generated URL is designed to appear authentic and remain unique for each request.

The predefined list for page1 is shown below. TechHub randomly selects one item from the list.

economy, opinion, politics, national, international, medical, investment, sports, lifestyle, shopping, culture

The predefined word list for page2 is shown below.

article, list, story

This means the hardcoded URL can later be transformed, for example, into hxxps://cubedesign[.]co[.]kr/news/economy/article/12345678 by following the steps described above.

Authentication using the POST request with the C2 server requires three parameters in the form of key‑value pairs. Each key is randomly generated using a different predefined word dictionary, and the associated values consist of a randomly generated 8‑byte hexadecimal bot ID, a fixed authentication token (KW4Ofw982CNJjxd51AVqkGAop), and a randomly generated 16‑byte hexadecimal session ID.

Cubridge employs a more robust handshaking process than TechHub, combining the RSA and RC6 algorithms. Unlike TechHub, it skips the profiling step and proceeds directly to command and control after the handshake. During communication, the malware mimics browser requests, using X‑CSRF‑Token and X‑Requested‑With headers for authentication and the Upgrade‑Insecure‑Requests header to request additional data.

Cubridge contains extensive functionality, with a particular focus on loading subsequent‑stage payloads. The commands employ various techniques, such as DLL injection, reflective loading, and section‑mapping injection. The payloads may be delivered in various forms:

• Plugins – reusable extensions that add functionality as needed and can be invoked at any time (in shellcode and DLL form);
• Tools (in DLL form) – independent utilities that perform one-off tasks;
• Modules – components that are loaded once and remain active providing an extended set of functionalities.

It is anticipated that the commands for plugins and shellcode will load identical types of plugins because both support a similarly formed exported function for subsequent activity. The shellcode can be generated using the open‑source sRDI tool to package a DLL‑style plugin. The capabilities of a single DLL are likely utilized to load a tool that works independently because when a single DLL is loaded, only its DllMain entry point and its parameters are accessible; no other exported functions are exposed.

Command	Payload type	Description
0	–	Collect device info including the computer name, time zone, PID, and other similar details
1		Archive the specified file/directory using the legacy ZipCrypto algorithm and the hard‑coded password: xdkiTajAAxc3i/w[<881fnC!G*cb1Dit2sh.gAk/
2		Create a file at the specified path
3	Possibly plugin	Inject the provided DLL payload into the target process and load it reflectively using reflective DLL injection
4	Plugin	Reflectively load a plugin in DLL format
5		Retrieve the address of the specified exported function from the target plugin and run it with the provided parameters
6		Retrieve all information about the loaded plugins
7		Unload the specified plugin
8	Shellcode	Inject the provided shellcode into the target process and load it using section mapping injection
9		Load the provided shellcode directly into memory
10		Retrieve the address of the specified export function from the target shellcode (likely a plugin in shellcode form) and run it with the provided parameter
11		Retrieve all information about the loaded shellcode
12		Unload the specified shellcode
13	–	Set the scheduled Cubridge execution time (in minutes) by updating a global variable
14		Set the scheduled Cubridge execution time (in minutes) by updating a global variable, while disabling monitoring by also updating another global variable
15		Terminate in a controlled manner
16		Get the configuration for Cubridge: retrieve the global flags, the number of C2 servers, the C2 addresses, etc.
17		Update the global flags, the number of C2 servers, the C2 addresses, etc.
18	Tool	Load a DLL reflectively with the specified parameter
19		Configure the parameters for loading a single DLL
20		Unload the single DLL
21	Module	Load the “action module” (ActionModule.dll) reflectively and invoke its AppinfoView export function
22		Load the “function module” (FunctionModule.dll) reflectively and invoke its PresentationFontConfig export function

Commands 21 and 22 each load a different module. As their internal names imply, the action module manages basic file and process operations, while the function module implements Windows’ default commands. The action module covers commands 23–41, and the function module handles commands 42–79.

The action module handles system operation commands, file system interactions, and process behavior. It is invoked by passing the appropriate command and parameters to its AppinfoView export function. The module supports 19 commands, numbered 23 through 41. Execution results are first sent to Cubridge, which then forwards them to the C2 server.

Command	Role
23	Get local disk space for each drive
24	Get information about the specified file or directory
25	Execute the provided command
26	Get information about the specified file or directory (similar to command 24)
27	Execute the provided command under the target process (PPID spoofing)
28	Execute the provided command under the target process within the provided session (PPID spoofing + session impersonation)
29	Get detailed information about processes
30	Terminate the provided process
31	Suspend all threads belonging to the specified process
32	Resume all threads belonging to the specified process
33	Permanently delete the file by overwriting its entire contents with the sequence: 0 → 1 → random bytes → 1 → 0
34	Rename the provided file to :EFS (the alternate data stream area) and delete it using the native API SetFileInformationByHandle
35	Set the current working directory
36	Copy the specified file to the provided path
37	Delete the specified directory
38	Move the specified file to the provided path
39	Create the provided directory
40	Initiate a non‑blocking connection attempt to the specified IP address and port (possibly for port scanning)
41	Read the specified file

The function module implements commands that emulate Windows’ built-in commands. Similar to the action module, its DllMain routine initializes all supported command functions, which are later accessed through the PresentationFontConfig export. Altogether, the module offers 38 commands, numbered from 42 to 79. While we believe this module is based on the previous LightlessCan, this is the first time we’ve seen it in the form of a separate module.

Command	Role
42	Capture all displays and archive them using the legacy ZipCrypto algorithm with the hard‑coded password: xdkiTajAAxc3i/w[<881fnC!G*cb1Dit2sh.gAk/
43	Synchronize the MAC (Modified, Accessed, and Created) times of the file provided in the second argument to match those of the file provided as the first argument
44	Get information about the specified directory
45	Get information about the specified drive
46	Inject the provided DLL payload into the target process
47	Unload the specified DLL from the specified process
48	Implementation of the ipconfig command
49	Implementation of the net command
50	Implementation of the netsh advfirewall firewall command
51	Implementation of the netstat command
52	Implementation of the ping -6 command
53	Implementation of the reg command
54	Implementation of the sc command
55	Implementation of the ping command
56	Implementation of the whoami command
57	Implementation of the nslookup command
58	Implementation of the schtasks command
59	Implementation of the systeminfo command
60	Implementation of the arp command
61	Call the CryptUnprotectData function to retrieve the AES key that DPAPI protects. Extract the key using the encrypted_key keyword from Chromium’s Local State file located at: %LOCALAPPDATA%\Google\Chrome\User Data\Local State
62	Not implemented
63	Not implemented
64	Read the specified file and decrypt it using an XOR operation with the key 0x59. Then extract the paths from the decrypted buffer and archive files and directories at these paths with the legacy ZipCrypto algorithm, using the hard‑coded password: xdkiTajAAxc3i/w[<881fnC!G*cb1Dit2sh.gAk/
65 ~ 79	Not implemented

Besides the modules, we also observed that the actor deployed various plugins and tools.

Type of payload	Name	Description
Plugin	ADFinder (AdFinder.dll)	Launches LDAP queries in an Active Directory environment, taking six arguments such as log file path, ADsPath, search filter, and attribute names
Plugin	FileCollector (Dll.dll)	Recursively scans every subdirectory and file in the provided directory, gathering detailed information about each
Tool	Browser stealer	Can be injected into Chromium-based browsers, such as Google Chrome, Microsoft Edge, and Brave. Once injected, it extracts files and credentials from the victim’s browsers, including stored passwords, bookmarks, history, preferences, and cookies
Tool	Process collector	Iterates over all running processes, collecting each process’s ID, path, and command line

TouchHub installs a service for TouchShift

During our analysis, we obtained a previously unknown malware sample from TechHub’s private GitHub repository, which served as a parent installer for TouchShift. We dubbed this malware TouchHub. Upon execution, it copies the legitimate printfilterpipelinesvc.exe to C:\Windows\System32\RasConv\ImeBroker.exe, registers it as a service, and places an embedded TouchShift payload named mscoree.dll in the same directory. Following creation, the malware synchronizes the MAC timestamps of C:\Windows\System32\drivers\monitor.sys with those of the newly written file, hindering forensic analysis.

It then goes through the service registration process by collecting up to 100 legitimate service names that are registered under the netsvcs svchost group in HKLM\SOFTWARE\Microsoft\Windows NT\CurrentVersion\Svchost. It randomly selects one of these names, appends two random alphabetic characters to form a new service name, and uses this name to create a service that runs the hard‑coded command line C:\Windows\System32\RasConv\ImeBroker.exe -TimeBroker with the description Microsoft Service. The newly created service is started immediately.
Overall, TouchHub creates three files in the designated directory to launch TouchShift with SYSTEM privileges.

Path	Type	Description
C:\Windows\System32\RasConv\ImeBroker.exe	Executable file registered as a service	Copied from C:\Windows\System32\printfilterpipelinesvc.exe
C:\Windows\System32\RasConv\mscoree.dll	Side-loaded TouchShift payload	Dropped by TouchHub. It contains encrypted payloads and includes portions of a legitimate DLL’s contents, which significantly inflates its size
C:\Windows\System32\RasConv\ActivationStore.dat	TechHub’s configuration file	Dropped by TouchHub after extracting configuration values

TouchShift, a prevalent loader employed across multiple infection chains

The version of TouchShift dropped by TouchHub is almost identical to the version described in Mandiant’s blog post, even sharing the same malicious export function, LockClrVersion. It takes the argument supplied by TouchHub and XORs it with a hard‑coded key. The resulting value is XORed once more with the executable’s filename, and this result is used as the AES key. All strings involved in this process (the argument, the XOR key, the filename) must be exactly 16 bytes long. If a string is shorter, it is padded with NULL bytes (\x00); if it is longer, it is truncated to 16 characters. For example, one of the string combinations in the obtained sample was:

• Argument: -TimeBroker\x00\x00\x00\x00\x00 (padded with NULL)
• Hard-coded XOR key: x809G736iC3f8Wp8
• Executable filename: ImeBroker.exe\x00\x00\x00 (padded with NULL)

After deriving the key, the malware decrypts the embedded payload using AES‑CBC‑128 without padding. The decrypted data is shellcode that starts with a call instruction. It wraps the next‑stage payload – identified as the third version of TechHub (DLL side-loading with a registered service) – that reads the ActivationStore.dat file as an external configuration.

ClientHub

We also identified a new piece of malware stored in TechHub’s private repository, which we named ClientHub. It supports various commands formed using a bitmask. There are at least two versions of ClientHub: one that communicates with websites via HTTP(S) and one that interacts with the Dropbox API using credentials.

Depending on the version, its configuration is sourced from internal resources or the external configuration file C:\Program Files\Common Files\System\msadc\msadc.inc. The configuration comprises keys and IVs for the SNOW 1.0 algorithm, scheduled execution times, and C2 server addresses encrypted with the SNOW stream cipher. The SNOW cipher is a family of high‑speed stream ciphers used for secure data encryption in telecommunications and wireless networks. This is the first time it has been observed in the malware of the Lazarus Group.

To establish C2 communication, the malware initially generates a 32‑byte random array. It subsequently overwrites portions of this array with data collected from the compromised device. The resulting 32‑byte array comprises a blend of random bytes and relevant information. This array is later used as the key for the SNOW algorithm to decrypt data received from the C2 server. Finally, the key array is encrypted with a hard‑coded RSA public key and encoded in Base64.

Offset	Size	Field value
0	4	Current process ID
4	4	First four bytes of the decrypted C2 server information.
8	7	Randomly generated bytes
15	1	Calculated flag value that indicates a state machine.
16	8	Current system time, represented as a FILETIME structure.
24	8	Randomly generated bytes

The ciphertext is delivered to the C2 server via GET requests. Each request contains headers that are atypical for malware: Sec-CH-UA, Sec-CH-UA-Platform, Sec-CH-UA-Mobile, Sec-Fetch-Mode, and Sec-Fetch-Dest. These headers are normally used by legitimate Chromium‑based browsers and enable malware to imitate legitimate traffic and evade detection. The C2 server replies with commands in a custom header and message body.

struct header
{
  int has_more_data // whether more body data remains 
  int body_checksum;// ROR13 checksum for the body data
  int body_type;    // specifies the body type
  int unknown;
  int body_length;  // Length of the body data
  int IV[2];        // Random IV used to encrypt the body data
};

The body_type field in the header determines how the subsequent payload is processed. This value functions as a bitmask, with each bit representing a distinct flag (e.g., 0x1, 0x2, 0x4, etc.). The resulting behavior also depends on whether the least‑significant bit (bit 0) is set: when the value is odd, the malware interprets the incoming message body as an additional payload that is subsequently loaded into memory. Conversely, when the value is even, the malware invokes the previously loaded payload.

The odd value supports four distinct loading methods based on the received message body and ensures that each method executes only once.

Bitmask	Value in decimal	Description	Result sent to the C2
0x00000001	1	DLL loading: load the received body reflectively along with the provided parameter	The payload’s image base
0x00000011	3	Plugin: load the received body reflectively, obtain the address of a function in the payload, and then invoke that function along with the provided parameter	The payload’s image base, the address of the invoked function, and the execution result
0x00000101	5	Plugin: load the received body reflectively, obtain the address of a function in the payload, but refrain from invoking it immediately	The payload’s image base, the address of the function
0x00001011	11	Plugin: execute the behavior associated with value 3, then unload immediately after invoking the plugin	–
0x00010001	17	DLL loading: load the received body reflectively with the provided parameter, maintaining stateful communication via a persistent interactive session using a shared buffer	The payload’s image base, the address of the interactive shared buffer, and the execution result

The even value provides two distinct invocation methods for DLLs and plugins that have already been loaded and are associated with the odd‑value bitmask. The 2 (0x10) flag allows the payload previously loaded with the 1, 3, or 5 bitmask to be reused and invoked directly. The value 16 (0x10000) corresponds to the 17 (0x10001) flag in loading mode and uses the established interactive shared buffer to exchange data. All values are guaranteed to act independently.

Bitmask	Value in decimal	Description	Result sent to the C2
0x00000010	2	Invoke the previously loaded DLLs and plugins along with the provided parameter	The execution result
0x00000100	4	Not implemented	–
0x00001000	8	Unload the previously loaded DLLs and plugins	The execution result
0x00010000	16	Send the updated parameter to the payload loaded by the command with the value 17, and exchange data through the interactive session. This command also determines whether to retrieve the execution result or unload the payload	The execution result

Taking into account the loading mechanism, we identified four plugins deployed to the target that work perfectly with ClientHub.

Plugin	Description
File archiver	Archives the provided file using the legacy ZipCrypto algorithm (without password protection) and returns the compressed data
File collector	Searches for all files matching the provided search pattern and collects metadata including filename, MAC timestamps, file size, and attribute values
File cleaner	Overwrites the provided file with NULL bytes, renames it to a randomly generated filename of the same length, and then deletes it. If a directory with a search pattern is provided, it locates all matching files, renames each to a randomly generated name of identical length to its original name, and deletes them
Drive and session monitor	Monitors remote session changes and local drive changes for the provided duration (in 10-minute intervals) and returns the collected status information

In addition to the plugins, ClientHub supports the loading of LPEClient malware and communication with it. We found that ClientHub’s body_type values 16 and 17 correspond to LPEClient’s C2 communication mechanism.

LPEClient

LPEClient is the only malware that was also observed in Operation SyncHole, indicating that the actor relies heavily on it for sophisticated victim profiling and payload delivery across multiple operations. LPEClient first appeared in 2019, and was discovered in 2020. Since then, the tool has been widely observed in the Dream Job and Cascade Hole campaigns that targeted South Korea. Recent research conducted by Check Point revealed that LPEClient was used to deploy the FudModule malware using a zero-day.

LPEClient has evolved continuously over time, but we discovered that it recently underwent a major operational revamp. It no longer contains the C2 server address itself; instead, it interacts with ClientHub via a shared buffer. We believe this change is intended to enhance concealment.

The previous version collected the computer name, memory status, CPU specifications, operating system details, version of the ntoskrnl.exe file, firmware table, antivirus name, domain name, user name, the integrity level of the current process, and a random byte sequence of 1,568 bytes. The newly updated LPEClient variant mostly collects the same information; however, it also introduces several changes.

• It does not collect the version of the ntoskrnl.exe file by querying the FileVersion value. Instead, depending on the specific build, it reads either the HKLM\SOFTWARE\Microsoft\Windows NT\CurrentVersion\UBR registry key or the SYSTEM_BUILD_VERSION_INFORMATION structure to retrieve the revision portion of the Windows build number. These values can be used to infer the system’s cumulative update or patch level.
• To collect information about installed antivirus products, it switched from querying a WQL command to reading the WMI repository file directly. It now reads C:\Windows\System32\wbem\Repository\OBJECTS.DATA and searches for keywords such as AntiVirusProduct, companyName, and displayName to identify the installed products.
• It also collects low‑level Windows security mitigation states. To achieve this, it queries the SYSTEM_KERNEL_VA_SHADOW_INFORMATION structure for the Kernel VA Shadow mitigation status and the SYSTEM_SHADOW_STACK_INFORMATION structure for the Shadow Stack (CET) protection status.

Additionally, it generates a 32‑byte random unique identifier by using the HighwayHash algorithm and an XOR operation with the current system time. The collected information, including the generated identifier, is compressed with the XPRESS Huffman algorithm using the maximum compression setting. The compressed data is then concatenated with the message ID 0xF07D6B34 and encrypted using GOST (also known as Magma), Russia’s national cryptographic standard that employs a DES‑like structure, before being sent to the ClientHub via a shared buffer. Initially, KrCERT described the algorithm as a custom DES‑like scheme. However, further analysis by us and Check Point confirmed that it is actually the GOST algorithm. The key is randomly generated by a proprietary key‑generation algorithm and prepended to the encrypted message.

The next request handles the key exchange by delivering the message ID 0xA39CF278 together with the generated unique identifier. The response is decrypted using the AES‑CBC‑256 algorithm. The SHA‑256 hash of the previously generated 1,568‑byte random value, which was originally sent to the C2 server during the collection phase, serves as the key for this decryption.

Through this process, LPEClient obtains a byte array comprising four 1,568‑byte blocks from the C2 response. Each block contains an ML‑KEM‑1024 public key, where ML‑KEM is a NIST‑standardized post‑quantum key encapsulation mechanism derived from CRYSTALS‑Kyber. LPEClient then generates four distinct pairs of shared keys and ciphertexts from these blocks, encrypts the ciphertexts with the GOST algorithm, and transmits them to the C2 server via ClientHub together with the message identifier 0xEF8C0D51 and the associated identifier. Now that the preparation phase for receiving payloads is complete, the malware is ready to receive payloads forwarded by ClientHub from the C2 server, along with the necessary parameters. The use of post-quantum cryptography shows that the group intends to hide subsequent payloads.

The response to the 0xEF8C0D51 message is decrypted with the Threefish algorithm using a 128-byte key, composed of the four distinct shared keys. Threefish is a tweakable block cipher that accepts a ‘tweak’ value alongside the key and the message. The concept of a tweak is similar to that of a nonce or initialization vector, which are used in different types of ciphers. In LPEClient communication, the tweak for the decryption is derived by XORing the unique identifier with 165 (0xA5). The first four bytes of the decrypted message must specify the parameter’s length, followed by the parameter itself and then the payload. The payload must be larger than 4 KB and start with the characters 'MZ', which indicates that the decrypted payload is an executable file. The payload is then reflectively loaded into memory. After successful loading, LPEClient sends the message ID 0xCB790A25 to the C2 server.

Before loading the acquired payload, LPEClient takes measures to bypass security products. Instead of invoking VirtualProtect directly, the malware uses the identified HeapPageAllocator::ProtectPages in jscript9.dll to modify the memory page protection of the MD4Update function. The beginning of the function is then overwritten with a hard‑coded opcode sequence that serves as a syscall stub with the required arguments. LPEClient then uses the syscall stub to disable a user‑mode syscall instrumentation hook.

We identified the final payload that was ultimately loaded as Cubridge. The overall communication process is as follows.

Comparison of plugins and modules

Throughout the engagement, we identified a variety of payloads deployed by TechHub, Cubridge, and ClientHub. These payloads have been categorized as tools, plugins, and modules that constitute the group’s modular malware framework. While we have not yet ascertained which payloads are deployed under specific conditions, the evidence suggests that the Lazarus Group’s toolkit is becoming increasingly sophisticated and segmented into specialized components rather than a single comprehensive backdoor. We also believe that TechHub and Cubridge may share similar tools.

Deployed via	Type of payload	Family
TechHub/Cubridge	Tool	Process collector, Browser stealer
Cubridge	Module	Action module, Function module
Cubridge	Plugin	ADFinder, FileCollector
ClientHub	Plugin	File archiver, File collector, File cleaner, Drive/session monitor

These modularizations are not confined to the instances within this campaign. As previously noted, similar patterns have been identified in CookiePlus, MISTPEN, SIGNBT, and IMETHOD. Note that we have reclassified the ThreatNeedle variant used in Operation SyncHole as the latest version of IMETHOD, the predecessor of ThreatNeedle in use since at least 2016.

Infrastructure

Based on the information we obtained from the TechHub malware, we identified at least three primary repositories used as the C2 server and one fallback repository. The earliest evidence indicates that the group has been leveraging GitHub as a C2 server since at least July 2025. We suspect that all the accounts were created using hijacked email accounts, and disguised as normal repositories by copying or creating normal projects to avoid suspicion.

For the Cubridge and ClientHub C2 servers, the Lazarus Group employed only a minimal number of compromised yet legitimate South Korean media and interior design websites. Later, we observed that a broader range of compromised legitimate sites across various industries were also exploited. In addition, one ClientHub sample that we detected used Dropbox as a C2 channel.

Victims

We have identified at least three firms from the software, construction, and wired communication equipment industries in South Korea that were targeted by Operation FlashHole. As with the previous operation, however, we remain confident that a considerably larger number of organizations across a broader spectrum of industries have been affected.

The software sector was the only sector targeted in both the SyncHole and FlashHole campaigns. This suggests the actor is eager to compromise the sector, steal source code, and exploit vulnerabilities for further attacks.

Attribution and links to other campaigns

Operation FlashHole is the latest wave in the broader Cascade Hole campaign, which involves the use of South Korean software as a potential entry point to deliver malware targeting the country. Although the malware chain has advanced significantly since last year, we assess with medium-to-high confidence that the same actor is responsible for both the SyncHole and FlashHole operations based on the initial vector, targets, multi‑stage chain, and technical and operational improvements. The use of LPEClient in particular is a strong indicator supporting this assessment.

The malware strains used in the attack are historically linked to the toolsets observed in the Lazarus Group’s notorious Dream Job campaign. Earlier versions of TechHub (also known as CLOUDBURST and NickelLoader), Cubridge (also known as SIDESHOW and LightlessCan), and TouchShift were all observed in that campaign, especially between 2022 and 2023.

We also discovered that both CookiePlus and ClientHub have significant overlaps in class name, configuration path, and plugins. Based on these similarities, we assess with medium‑high confidence that ClientHub is an advanced version of CookiePlus.

Since July, around the time Operation SyncHole began winding down, we have also observed several notable attacks against South Korea employing the COPPERHEDGE backdoor and targeting various South Korean organizations. Interestingly, the start times of these activities align with the earliest evidence we have identified for Operation FlashHole. Although the backdoor was part of the second phase of Operation SyncHole, it has been operating independently with its custom loader since then. These incidents featured malware chains and tools that were distinct from those used in Operation SyncHole and FlashHole.

As AhnLab noted in their report, the same backdoor was likely observed in atypical activity, specifically the Gunra ransomware infection. Our investigation further revealed that one instance of a backdoor infection ultimately resulted in the exfiltration of data to a dark web leak site, which clearly differed from Gunra’s. The site appears to have been crafted exclusively for this activity. In summary, unlike other attacks, the backdoor was used in conjunction with both ransomware and data exfiltration.

Another noteworthy point is that the recent Dream Job campaign employs an updated malware chain that, since around 2024, has primarily involved MISTPEN and ForestTiger rather than the earlier arsenal that included tools such as TechHub and Cubridge. However, the updated versions of this older malware have now re-emerged as part of Operation FlashHole. Considering these changes and all aspects of each attack’s TTPs, we have organized a classification for each attack.

Conclusion

Our analysis shows that the Lazarus Group begins preparing for its next operation shortly after completing the previous one, ultimately deploying an enhanced malware chain by refining existing tools. The group continues to use the advanced version of LPEClient for profiling and payload delivery, indicating that the tool is meticulously managed and well maintained. Ironically, the group seems to have adopted more secure post-quantum cryptography faster than many legitimate security products. These observations suggest the involvement of a dedicated developer, with others orchestrating comprehensive attack scenarios against newly targeted software.

We anticipated that specialized attacks targeting South Korea would persist. However, we did not foresee multiple attack campaigns being executed simultaneously, each leveraging different types of software and tools. Notably, the COPPERHEDGE cluster appears to be involved in monetizing the attacks, while Operation FlashHole is focused on espionage. We are closely monitoring these changes to understand their motivations and ultimate goals.
In October 2025, the South Korean government unveiled a comprehensive cybersecurity plan that will phase out the mandatory installation of security software for users beginning in 2026. We estimate that operations exploiting this software will remain highly active for some time, maximizing efficiency, before the software is fully eliminated or mitigated.

Kaspersky products detect the exploits and malware used in this attack with the following verdicts: MEM:Trojan.Win64.Shellcode.gen, Trojan.Win64.DLLhijack.*, Trojan.Win64.Lazarus.*.

Indicators of compromise

File hashes

TouchShift
ec84d6cb2ae7974767aedac246b50a3e             mscoree.dll
a28cba214058fcae2883d8cffc883abd                mscoree.dll
c105d6b16f544582772de0159f24c00a               mscoree.dll
2f8475a90a25624ed02f1d18d4e6d65d              mscoree.dll
676fabe30a28b53925fba98e34b35986              mscoree.dll
b4a7eff35f048f06fb0a2d7631f23a7d                  mscoree.dll

ClientHub Loader
ff07641dc56914dd90ee0bd7404d7ad7               liblzma.dll

File paths

C:\ProgramData\Package.txt
C:\ProgramData\RasConv\mscoree.dll
C:\ProgramData\Apple\mscoree.dll
C:\ProgramData\ssh\mscoree.dll
C:\ProgramData\qorestor\mscoree.dll
C:\ProgramData\Dell\mscoree.dll
C:\ProgramData\Dell\Dell1.tmp
C:\ProgramData\Dell\Dell3.tmp
C:\Windows\System32\RasConv\mscoree.dll
C:\Windows\System32\RasConv\ActivationStore.dat
C:\Windows\System32\DrvConh\mscoree.dll
C:\Windows\System32\DrvConh\ActivationStore.dat
C:\Program Files\Common Files\System\msadc\msadc.inc
C:\ProgramData\desktops.ini

C2 servers

javadevhouse.co[.]kr
pythonapischool[.]com
hxxps://cubedesign[.]co[.]kr/news            C2 of Cubridge
hxxps://cubedesign[.]co[.]kr/mobile/fashion            C2 of Cubridge
hxxps://fp-news[.]co[.]kr/shop/cart                                C2 of Cubridge
hxxps://k-wbc[.]co[.]kr/skin/social/social_view.php         C2 of ClientHub
hxxps://rcsh[.]co[.]kr/modules/bbs/tiles/bbs_div/inputForm.php    C2 of ClientHub
hxxps://www[.]ksog[.]org/insert_file/handle.php                   C2 of ClientHub

All threats

The percentage of ICS computers on which malicious objects were blocked continued to decrease, reaching 19.6% in Q1 2026. This is the lowest value in three years, and it is 1.4 times lower than in Q2 2023.

Regionally, the percentages ranged from 9.1% in Northern Europe to 27.4% in Africa.

The percentage of ICS computers on which malicious objects were blocked increased in five regions over the quarter, most notably in Southern Europe, Northern Europe, and Russia.

In Q1 2026, Southern Europe led the way in growth for internet and email threats. The region also saw the fastest growth in spyware, as well as malicious scripts and phishing pages.

In Russia, the percentage of ICS computers on which malicious objects were blocked exceeded the figures for the previous two quarters. Russia saw an increase in the percentage for threats from the internet, and a slight increase in the figure for threats from email clients (Russia is one of three regions where this figure did not decrease).

Among the threat categories, the greatest increases were observed in the percentages for denylisted internet resources, as well as spyware (distributed in the region via the internet and email clients).

Selected industries

Biometric systems (26.4%) traditionally rank top among the industries and OT infrastructure types covered in this report in terms of the percentage of ICS computers on which malicious objects were blocked. These systems are characterized by internet access, extensive email use for data exchange and approvals (such as access granting), and, in many cases, minimal cybersecurity controls within the organizations that use these systems.

Biometric systems rank first among industries in terms of email threats. At the same time, unlike other industries, the percentage for email threats in biometric systems exceeds that for internet threats.

In all selected industries, the global average follows a downward trend. In Q1 2026, the percentage of ICS computers on which malicious objects were blocked increased only in the manufacturing sector — by 1.0 pp. The percentages for this industry increased across 10 regions, with the most notable increases in Western Europe, Northern Europe, and Russia.

Threat categories

In Q1 2026, Kaspersky security solutions blocked malware from 10,052 different malware families of various categories on industrial automation systems.

Over the quarter, the percentage of ICS computers on which denylisted internet resources were blocked increased (after decreasing over the previous two quarters), and there was a slight increase in the percentage for AutoCAD malware.

Malicious scripts and phishing pages (JS and HTML)

Malicious scripts and phishing pages retained their to spot among threat categories by the percentage of ICS computers on which these threats were blocked. The global average in Q1 2026 was 6.56%.

Over the quarter, the percentages increased in four regions. The most significant change was observed in Southern Europe (9.85%, +0.94 pp). The figures for malicious scripts in the region increased over three consecutive quarters.

Among the selected industries, across all regions, the highest percentages for the malicious scripts and phishing pages category were recorded for biometric systems (19.59%) and building automation (15.43%) in Southern Europe. These same industries lead in similar rankings for malicious documents and spyware.

Spyware

The percentage of ICS computers on which spyware was blocked decreased over two consecutive quarters, dropping to 3.73%. Despite the decline, spyware has ranked second among threat categories by the percentage of attacked computers for three consecutive quarters.

The percentages increased in five regions over the quarter, most notably in Southern Europe (5.46%, +0.35 pp) and Russia (2.84%, +0.24 pp).

In Southern Europe, the percentage of ICS computers on which spyware was blocked increased in all the selected industries except manufacturing. The greatest increase was observed in biometric systems.

Among the selected industries, the highest percentage of spyware in Russia was recorded in biometric systems. That said, the percentage of ICS computers on which spyware was blocked increased in all industries in the region except construction. The percentage figure has been increasing for two consecutive quarters in the oil and gas industry (by a factor of 1.63 over six months), and for three consecutive quarters in engineering and ICS integration, as well as electric power. In the remaining sectors, the values have been fluctuating.

Denylisted internet resources

The percentage of ICS computers on which denylisted internet resources were blocked increased to 3.54%.

The most notable increase over the quarter occurred in Southeast Asia (4.58%, +0.65 pp). Among the industries in the region, the highest percentage figures for this threat category were recorded in electric power and construction. Over the quarter, the largest increases in percentages figures were observed in the electric power and manufacturing industries.

In North America (Canada), denylisted internet resources (2.14%) showed the greatest increase among all categories — by a factor of 1.22.

Among the selected industries across all regions, the highest percentage figures for the denylisted internet resources category were in the electric power (7.11%) and construction (6.25%) industries in Southeast Asia.

Malicious documents (Microsoft Office + PDF)

The percentage figure for this category decreased over two consecutive quarters, reaching its lowest value (1.56%) for the entire period of observations in Q1 2026. It increased just in two regions: Australia and New Zealand (1.12%, +0.04 pp), and Russia (0.62%, +0.01 pp).

Among the selected industries across all regions, the highest percentages for malicious documents were recorded for biometric systems (9.02%) and building automation (6.97%) in Southern Europe. These same industries also lead in similar rankings for malicious scripts and spyware.

Ransomware

The percentage of ICS computers on which ransomware was blocked has decreased for two consecutive quarters, dropping to 0.14%. This is the lowest value among all categories.

The percentage increased in two regions: North America (Canada) (0.11%, +0.04 pp) and slightly in Northern Europe (0.06%, +0.01 pp).

Among the selected industries across all regions, the highest percentages for ransomware were recorded in the oil and gas and manufacturing industries (0.92% and 0.65%, respectively) in Central Asia and the South Caucasus, and in biometric systems (0.89%) in Russia.

Miners in the form of executable files for Windows

The percentage of ICS computers on which miners in the form of executable files for Windows were blocked decreased to 0.59%.

The percentage increased in seven regions. The largest increase was observed in Africa (0.63%, +0.16 pp). Among the selected industries, the largest increases in the region were in the manufacturing and oil and gas industries.

Among the selected industries across all regions, the highest percentages for miners in the form of executable files were recorded in construction (1.99%), biometric systems (1.98%), and the oil and gas industry (1.97%) in Central Asia and the South Caucasus.

Web miners

The percentage of ICS computers on which web miners were blocked has been declining for a year, and in Q1 2026, it reached the lowest value for the entire period under review (0.22%).

At the same time, the percentage increased in seven regions. The largest increases were observed in South Asia (0.28%, +0.11 pp), the Middle East (0.31%, +0.09 pp), and Africa (0.34%, +0.08 pp). Despite the increases, the percentages in these regions for Q1 2026 did not exceed those observed in 2023–2024 and in Q1 2025.

Among the selected industries across all regions, the highest percentages for web miners were recorded for biometric systems (0.97%) in Russia. Biometric systems in South Asia (0.79%) ranked second, and the electric power sector in Southeast Asia (0.76%) ranked third.

Worms

The percentage of ICS computers on which worms were blocked decreased to 1.33%.

The percentage decreased across all regions following an increase in the previous quarter (due to a wave of phishing attacks that distributed the Backdoor.MSIL.XWorm backdoor worm across all regions of the world).

Among the selected industries across all regions, the highest percentage figure for worms was recorded for biometric systems (4.80%) in Central Asia and the South Caucasus. Two industries in Africa – biometric systems (4.04%) and electric power (3.53%) – took the second and third spots, respectively.

Viruses

The percentage of ICS computers on which viruses were blocked decreased to 1.31%.

The top 3 regions by this figure remained the same: Southeast Asia (6.11%, first by a wide margin), Africa (4.15%), and East Asia (2.97%). These same regions are also among the leaders by the percentage of systems affected by AutoCAD malware. The largest increase in this figure was observed in Africa (+0.41 pp).

Among the selected industries across all regions, the highest percentages for viruses were recorded in the construction industry (6.35%) and building automation (5.50%) in Southeast Asia.

Malware for AutoCAD

The percentage of ICS computers on which malware for AutoCAD was blocked increased to 0.30%.

The most notable increase over the quarter was observed in Africa, with the region’s percentage figure rising by 0.47 pp, a very significant increase for this category, and almost doubling (to 0.91%).

Among the selected industries across all regions, the highest percentages for AutoCAD malware were recorded in the construction industry in East Asia (5.58%) and Southeast Asia (3.87%).

Main threat sources

In Q1 2026, the average percentages across all threat sources, except threats from the internet, decreased globally.

Internet

The percentage of ICS computers on which threats from the internet were blocked increased to 7.88%. However, over the past three years, the percentage figure for internet threats has followed a downward trend.

The largest increases in the percentages were recorded in Southern Europe (8.59%, +0.59 pp), Southeast Asia (10.16%, +0.55 pp), and Northern Europe (4.47%, +0.51 pp).

Among the selected industries across all regions, the highest percentages for threats from the internet were recorded in electric power (13.16%) and construction (12.55%) in Southeast Asia, and in the engineering and ICS integration sector (12.33%) in South Asia.

Email clients

The percentage of ICS computers on which threats delivered via email clients were blocked decreased to 2.59%. This is a three-year low.

The percentage of this threat source increased in three regions: Southern Europe (6.54%, +0.2 pp), East Asia (1.5%, +0.09 pp), and slightly in Russia (0.7%, +0.04 pp).

Among the selected industries across all regions, the highest percentages for email threats were recorded for biometric systems (19.78%) and building automation (12.34%) in Southern Europe. In these two industries, the percentage of ICS computers on which email threats are blocked is higher than the percentage for threats from the internet. A similar situation was observed in two other instances, both in biometric systems (in South America and Southeast Asia).

Removable media

The percentage of ICS computers on which threats were detected when connecting removable media continued to decrease, reaching its lowest value for the period under review (0.26%).

Among the selected industries across all regions, the highest percentages for removable media threats blocked on ICS computers were observed in the electric power sector in Central Asia and the South Caucasus (1.45%), East Asia (1.34%), and Africa (1.16%).

Network folders

The percentage of ICS computers on which threats are blocked in network folders is steadily decreasing. In Q1 2026, it was the lowest for the period under review (0.029%).

East Asia has traditionally led by a wide margin. The percentage for East Asia (0.135%) is 27 times higher than the lowest regional value (recorded in Northern Europe).

The largest increases in the percentages for threats from network folders were observed in Africa (0.037%, +0.006 pp) and South America (0.013%, +0.006 pp).
Among the selected industries across all regions, the construction industry in East Asia, at 0.36%, holds the top positions in the ranking by the percentage of ICS computers on which threats are blocked in network folders.

For more information on industrial threats see the full version of the report.

Introduction

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

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

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

Technical details

Spreading

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

Malicious wheel packages

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

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

The key metadata for these packages are as follows:

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

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

Initial infection

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

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

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

Windows version

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

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

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

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

Dropper for ZiChatBot

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

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

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

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

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

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

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

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

Linux version

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

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

ZiChatBot

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

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

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

// Auth token:
TW9yaWFuLWJvdEBoZWxwZXIuenVsaXBjaGF0LmNvbTpVOFJFWGxJNktmOHFYQjlyUXpPUEJpSUE0YnJKNThxRw==

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

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

Infrastructure

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

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

Victims

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

Attribution

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

Conclusions

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

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

Indicators of compromise

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

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

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

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

Dropper for ZiChatBot
Backward.dll
c33782c94c29dd268a42cbe03542bca5
454b85dc32dc8023cd2be04e4501f16a

Backward.so
fce65c540d8186d9506e2f84c38a57c4
652f4da6c467838957de19eed40d39da

terminate.dll
1995682d600e329b7833003a01609252

terminate.so
38b75af6cbdb60127decd59140d10640

ZiChatBot
libcef.dll
a26019b68ef060e593b8651262cbd0f6

Statistics across all threats

The percentage of ICS computers on which malicious objects were blocked has been decreasing since the beginning of 2024. In Q4 2025, it was 19.7%. Over the past three years, the percentage has decreased by 1.36 times, and by 1.25 times since Q4 2023.

Regionally, in Q4 2025, the percentage of ICS computers on which malicious objects were blocked ranged from 8.5% in Northern Europe to 27.3% in Africa.

Four regions saw an increase in the percentage of ICS computers on which malicious objects were blocked. The most notable increases occurred in Southern Europe and South Asia. In Q3 2025, East Asia experienced a sharp increase triggered by the local spread of malicious scripts, but the figure has since returned to normal.

Feature of the quarter: worms in email

In Q4 2025, the percentage of ICS computers on which wormsinemailattachments were blocked increasedinallregions of the world.

Many of the blocked threats were related to the worm Backdoor.MSIL.XWorm. This malware is designed to persist on the system and then remotely control it.

Interestingly, this threat was not detected on ICS computers in the previous quarter, yet it appeared in all regions in Q4 2025.

A study found that the active spread of Backdoor.MSIL.XWorm via phishing emails was likely linked to the use by hackers of another malware obfuscation technique that was actively used during massive phishing campaigns in Q4 2025. These campaigns have been known since 2024 as “Curriculum-vitae-catalina”.

The attackers distributed phishing emails to HR managers, recruiters, and employees responsible for hiring. The messages were disguised as responses from job applicants with subjects such as “Resume” or “Attached Resume” and contained a malicious executable file under the guise of a curriculum vitae. Typically, the file was named Curriculum Vitae-Catalina.exe. When executed, it infected the system.

In Q4 2025, the threat spread across regions in two waves — one in October and another in November. Russia, Western Europe, South America, and North America (Canada) were attacked in October. A spike in Backdoor.MSIL.XWorm blocking was observed in other regions in November. The attack subsided in all regions in December.

The highest percentage of ICS computers on which Backdoor.MSIL.XWorm was blocked was observed in regions where threats from email clients had been historically blocked at high rates on ICS computers: Southern Europe, South America, and the Middle East.

At the same time, in Africa, where USB storage media are still actively used, the threat was also detected when removable devices were connected to ICS computers.

Selected industries

The biometrics sector has historically led the rankings of industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked.

These systems are characterized by accessibility to and from the internet, as well as minimal cybersecurity controls by the consumer organization.

In Q4 2025, the percentage of ICS computers on which malicious objects were blocked increased only in one sector: oil and gas. The corresponding figures increased in two regions: Russia, and Central Asia and the South Caucasus.

However, if we look at a broader time span, there is a downward trend in all the surveyed industries.

Diversity of detected malicious objects

In Q4 2025, Kaspersky protection solutions blocked malware from 10,142 different malware families of various categories on industrial automation systems.

In Q4 2025, there was an increase in the percentage of ICS computers on which worms, and miners in the form of executable files for Windows were blocked. These were the only categories that exhibited an increase.

Main threat sources

Depending on the threat detection and blocking scenario, it is not always possible to reliably identify the source. The circumstantial evidence for a specific source can be the blocked threat’s type (category).

The internet (visiting malicious or compromised internet resources; malicious content distributed via messengers; cloud data storage and processing services and CDNs), email clients (phishing emails), and removable storage devices remain the primary sources of threats to computers in an organization’s technology infrastructure.

In Q4 2025, the percentage of ICS computers on which malicious objects from various sources were blocked decreased. All sources except email clients saw their lowest levels in three years.

The same computer can be attacked by several categories of malware from the same source during a quarter. That computer is counted when calculating the percentage of attacked computers for each threat category, but is only counted once for the threat source (we count unique attacked computers). In addition, it is not always possible to accurately determine the initial infection attempt. Therefore, the total percentage of ICS computers on which various categories of threats from a certain source were blocked can exceed the percentage of computers affected by the source itself.

• In Q4 2025, the percentage of ICS computers on which threats from the internet were blocked decreased to 7.67% and reached its lowest level since the beginning of 2023. The main categories of internet threats are malicious scripts and phishing pages, and denylisted internet resources. The percentage ranged from 3.96% in Northern Europe to 11.33% in South Asia.
• The main categories of threats from email clients blocked on ICS computers were malicious scripts and phishing pages, spyware, and malicious documents. Most of the spyware detected in phishing emails was delivered as a password archive or a multi-layered script embedded in office document files. The percentage of ICS computers on which threats from email clients were blocked ranged from 0.64% in Northern Europe to 6.34% in Southern Europe.
• The main categories of threats that were blocked when removable media was connected to ICS computers were worms, viruses, and spyware. The percentage of ICS computers on which threats from removable media were blocked ranged from 0.05% in Australia and New Zealand to 1.41% in Africa.
• The main categories of threats that spread through network folders in Q4 2025 were viruses, AutoCAD malware, worms, and spyware. The percentage of ICS computers on which threats from network folders were blocked ranged from 0.01% in Northern Europe to 0.18% in East Asia.

Threat categories

Typical attacks blocked within an OT network are multi-step sequences of malicious activities, where each subsequent step of the attackers is aimed at increasing privileges and/or gaining access to other systems by exploiting the security problems of industrial enterprises, including OT infrastructures.

Malicious objects used for initial infection

In Q4 2025, the percentage of ICS computers on which denylisted internet resources were blocked decreased to 3.26%. This is the lowest quarterly figure since the beginning of 2022, and it has decreased by 1.8 times since Q2 2025.

Regionally, the percentage of ICS computers on which denylisted internet resources were blocked ranged from 1.74% in Northern Europe to 3.93% in Southeast Asia, which displaced Africa from first place. Russia rounded out the top three regions for this indicator.

The percentage of ICS computers on which malicious documents were blocked increased for three consecutive quarters. However, in Q4 2025 it decreased by 0.22 pp to 1.76%.

Regionally, the percentage ranged from 0.46% in Northern Europe to 3.82% in Southern Europe. In Q4 2025, the indicator increased in Eastern Europe, Russia, and Western Europe.

The percentage of ICS computers on which malicious scripts and phishing pages were blocked decreased to 6.58%. Despite the decline, this category led the rankings of threat categories in terms of the percentage of ICS computers on which they were blocked.

Regionally, the percentage ranged from 2.52% in Northern Europe to 10.50% in South Asia. The indicator increased in South Asia, South America, Southern Europe, and Africa. South Asia saw the most notable increase, at 3.47 pp.

Next-stage malware

Malicious objects used to initially infect computers deliver next-stage malware — spyware, ransomware, and miners — to victims’ computers. As a rule, the higher the percentage of ICS computers on which the initial infection malware is blocked, the higher the percentage for next-stage malware.

In Q4 2025, the percentage of ICS computers on which spyware, ransomware and web miners were blocked decreased. The rates were:

• Spyware: 3.80% (down 0.24 pp). For the second quarter in a row, spyware took second place in the rankings of threat categories in terms of the percentage of ICS computers on which it was blocked.
• Ransomware: 0.16% (down 0.01 pp).
• Web miners: 0.24% (down 0.01 pp), this is the lowest level observed thus far in the period under review.

The percentage of ICS computers on which miners in the form of executable files for Windows were blocked increased to 0.60% (up 0.03 pp).

Self-propagating malware

Self-propagating malware (worms and viruses) is a category unto itself. Worms and virus-infected files were originally used for initial infection, but as botnet functionality evolved, they took on next-stage characteristics.

To spread across ICS networks, viruses and worms rely on removable media and network folders and are distributed in the form of infected files, such as archives with backups, office documents, pirated games and hacked applications. In rarer and more dangerous cases, web pages with network equipment settings, as well as files stored in internal document management systems, product lifecycle management (PLM) systems, resource management (ERP) systems and other web services are infected.

In Q4 2025, the percentage of ICS computers on which worms were blocked increased by 1.6 times to 1.60%. As mentioned above, this increase is related to a global phishing attack that spread the Backdoor.MSIL.XWorm backdoor worm across all regions of the world. The percentage increased in all regions. The biggest increase (up by 2.16 times) was in Southern Europe. The malware was primary distributed through email clients, and Southern Europe led the way in terms of the percentage of ICS computers on which threats from email clients were blocked.

The percentage of ICS computers on which viruses were blocked decreased to 1.33%.

AutoCAD malware

This category of malware can spread in a variety of ways, so it does not belong to a specific group.

After an increase in the previous quarter, the percentage of ICS computers on which AutoCAD malware was blocked decreased to 0.29% in Q4 2025.

For more information on industrial threats see the full version of the report.

Statistics across all threats

In Q3 2025, the percentage of ICS computers on which malicious objects were blocked decreased from the previous quarter by 0.4 pp to 20.1%. This is the lowest level for the observed period.

Regionally, the percentage of ICS computers on which malicious objects were blocked ranged from 9.2% in Northern Europe to 27.4% in Africa.

In Q3 2025, the percentage increased in five regions. The most notable increase occurred in East Asia, triggered by the local spread of malicious scripts in the OT infrastructure of engineering organizations and ICS integrators.

Selected industries

The biometrics sector traditionally led the rankings of the industries and OT infrastructures surveyed in this report in terms of the percentage of ICS computers on which malicious objects were blocked.

In Q3 2025, the percentage of ICS computers on which malicious objects were blocked increased in four of the seven surveyed industries. The most notable increases were in engineering and ICS integrators, and manufacturing.

Diversity of detected malicious objects

In Q3 2025, Kaspersky protection solutions blocked malware from 11,356 different malware families of various categories on industrial automation systems.

In Q3 2025, there was a decrease in the percentage of ICS computers on which denylisted internet resources and miners of both categories were blocked. These were the only categories that exhibited a decrease.

Main threat sources

Depending on the threat detection and blocking scenario, it is not always possible to reliably identify the source. The circumstantial evidence for a specific source can be the blocked threat’s type (category).

The internet (visiting malicious or compromised internet resources; malicious content distributed via messengers; cloud data storage and processing services and CDNs), email clients (phishing emails), and removable storage devices remain the primary sources of threats to computers in an organization’s technology infrastructure.

In Q3 2025, the percentage of ICS computers on which malicious objects from various sources were blocked decreased.

The same computer can be attacked by several categories of malware from the same source during a quarter. That computer is counted when calculating the percentage of attacked computers for each threat category, but is only counted once for the threat source (we count unique attacked computers). In addition, it is not always possible to accurately determine the initial infection attempt. Therefore, the total percentage of ICS computers on which various categories of threats from a certain source were blocked can exceed the percentage of threats from the source itself.

• The main categories of threats from the internet blocked on ICS computers in Q3 2025 were malicious scripts and phishing pages, and denylisted internet resources. The percentage ranged from 4.57% in Northern Europe to 10.31% in Africa.
• The main categories of threats from email clients blocked on ICS computers were malicious scripts and phishing pages, spyware, and malicious documents. Most of the spyware detected in phishing emails was delivered as a password-protected archive or a multi-layered script embedded in an office document. The percentage of ICS computers on which threats from email clients were blocked ranged from 0.78% in Russia to 6.85% in Southern Europe.
• The main categories of threats that were blocked when removable media was connected to ICS computers were worms, viruses, and spyware. The percentage of ICS computers on which threats from this source were blocked ranged from 0.05% in Australia and New Zealand to 1.43% in Africa.
• The main categories of threats that spread through network folders were viruses, AutoCAD malware, worms, and spyware. The percentages of ICS computers where threats from this source were blocked ranged from 0.006% in Northern Europe to 0.20% in East Asia.

Threat categories

Typical attacks blocked within an OT network are multi-step sequences of malicious activities, where each subsequent step of the attackers is aimed at increasing privileges and/or gaining access to other systems by exploiting the security problems of industrial enterprises, including technological infrastructures.

Malicious objects used for initial infection

In Q3 2025, the percentage of ICS computers on which denylisted internet resources were blocked decreased to 4.01%. This is the lowest quarterly figure since the beginning of 2022.

Regionally, the percentage of ICS computers on which denylisted internet resources were blocked ranged from 2.35% in Australia and New Zealand to 4.96% in Africa. Southeast Asia and South Asia were also among the top three regions for this indicator.

The percentage of ICS computers on which malicious documents were blocked has grown for three consecutive quarters, following a decline at the end of 2024. In Q3 2025, it reached 1,98%.

The indicator increased in four regions: South America, East Asia, Southeast Asia, and Australia and New Zealand. South America saw the largest increase as a result of a large-scale phishing campaign in which attackers used new exploits for an old vulnerability (CVE-2017-11882) in Microsoft Office Equation Editor to deliver various spyware to victims’ computers. It is noteworthy that the attackers in this phishing campaign used localized Spanish-language emails disguised as business correspondence.

In Q3 2025, the percentage of ICS computers on which malicious scripts and phishing pages were blocked increased to 6.79%. This category led the rankings of threat categories in terms of the percentage of ICS computers on which they were blocked.

Regionally, the percentage of ICS computers on which malicious scripts and phishing pages were blocked ranged from 2.57% in Northern Europe to 9.41% in Africa. The top three regions for this indicator were Africa, East Asia, and South America. The indicator increased the most in East Asia (by a dramatic 5.23 pp) as a result of the local spread of malicious spyware scripts loaded into the memory of popular torrent clients including MediaGet.

Next-stage malware

Malicious objects used to initially infect computers deliver next-stage malware — spyware, ransomware, and miners — to victims’ computers. As a rule, the higher the percentage of ICS computers on which the initial infection malware is blocked, the higher the percentage for next-stage malware.
In Q3 2025, the percentage of ICS computers on which spyware and ransomware were blocked increased. The rates were:

• spyware: 4.04% (up 0.20 pp);
• ransomware: 0.17% (up 0.03 pp).

The percentage of ICS computers on which miners of both categories were blocked decreased. The rates were:

• miners in the form of executable files for Windows: 0.57% (down 0.06 pp), it’s the lowest level since Q3 2022;
• web miners: 0.25% (down 0.05 pp). This is the lowest level since Q3 2022.

Self-propagating malware

Self-propagating malware (worms and viruses) is a category unto itself. Worms and virus-infected files were originally used for initial infection, but as botnet functionality evolved, they took on next-stage characteristics.

To spread across ICS networks, viruses and worms rely on removable media and network folders in the form of infected files, such as archives with backups, office documents, pirated games and hacked applications. In rarer and more dangerous cases, web pages with network equipment settings, as well as files stored in internal document management systems, product lifecycle management (PLM) systems, resource management (ERP) systems and other web services are infected.

In Q3 2025, the percentage of ICS computers on which worms and viruses were blocked increased to 1.26% (by 0.04 pp) and 1.40% (by 0.11 pp), respectively.

AutoCAD malware

This category of malware can spread in a variety of ways, so it does not belong to a specific group.

In Q3 2025, the percentage of ICS computers on which AutoCAD malware was blocked slightly increased to 0.30% (by 0.01 pp).

For more information on industrial threats see the full version of the report.