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GoldFactory has expanded the evasion capabilities of its Gigabud Android banking trojan by deploying Vwork, a weaponized fork of the open-source Shelter application. The companion tool abuses Android Work Profile isolation to clone banking apps into a separate managed environment, weakening the link between malware signals detected in a victim’s personal profile and fraudulent activity […]
A sophisticated Linux implant linked to compromised F5 BIG-IP Access Policy Management (APM) environments. The activity has been associated with exploitation of CVE-2025-53521, an unauthenticated remote code execution flaw affecting BIG-IP APM when an access policy is configured on a virtual server. F5 has confirmed exploitation of the vulnerability and links the related compromise activity […]
We continue tracking the activity of Toy Ghouls (also known as Bearlyfy, Laboo.boo, and Feral Wolf), a financially motivated group that has been targeting Russian organizations since 2025. The attackers initially relied exclusively on tools pulled from public GitHub repositories along with leaked Babuk and LockBit ransomware builders, later shifting to their own custom ransomware, GenieLocker. In early July 2026, we observed the group using a custom backdoor for the first time.
We identified two versions of this backdoor: one uses the HiveMQ MQTT broker as its C2 server, while the other relies on the Element messenger. Both versions include “bird” in their names:
mqtt-bird-agent 0.1.0 (HiveMQ version)
matrix-bird-agent 0.1.0 (Element version)
This post examines how the backdoor is delivered to target systems, how it establishes persistence, and how it communicates with its C2 server.
Technical details
Delivery
In this campaign, the attackers use Windows Remote Management (WinRM) to deliver the backdoors and their configuration files to compromised systems. The group relies on open-source tools such as Evil-WinRM and WinRM-fs to do this.
Installation
The backdoor can both run within an interactive command-line session and establish persistence as a Windows service, using the --install or install option, depending on the backdoor version. The --service (or service) option is not available by default and is instead used as an argument for the installed Windows service.
Other launch options are listed in the backdoor’s help output:
C:\cplsupport.exe -h
Bird Agent - MQTT server monitor
Usage: cplsupport.exe [OPTIONS]
Options:
-c, --config <CONFIG> Path to config.toml config file
--install Install as a system service
--uninstall Uninstall the system service
--seal Encrypt sensitive config fields in-place using a machine-bound key
-h, --help Print help
-V, --version Print version
HiveMQ version backdoor help output
In the Element version, the backdoor help output looks as follows:
C:\wtass.exe -h
Matrix monitoring agent
Usage: wtass.exe [OPTIONS] [COMMAND]
Commands:
install Register this agent with the Matrix homeserver and panel
uninstall Remove this agent's service and credentials
service Run as a Windows service (internal)
help Print this message or the help of the given subcommand(s)
Options:
-c, --config <CONFIG>
-h, --help Print help
-V, --version Print version
Element version backdoor help output
By default, the backdoor looks for a config.toml configuration file in the directory where the executable was launched, then falls back to %PROGRAMDATA%\SynapseAgent\config.toml (Element version) or %PROGRAMDATA%\cplsupport\config.toml (HiveMQ version). If no configuration file is found in either location, the full path can be specified using the -c (--config) option.
The backdoor accepts both unencrypted configuration files and files with partially encrypted sections. In the first case, once the backdoor is launched, it reads the file and partially encrypts it using the seal() function (the --seal option in the HiveMQ version), applying the ChaCha20-Poly1305 algorithm with a key derived from the value of the HKLM\Software\Microsoft\Cryptography\MachineGuid registry key. This means that after the backdoor’s first run, the configuration file becomes bound to that specific machine. On subsequent runs, the configuration is decrypted automatically. If the input configuration was already partially encrypted, it is likewise decrypted automatically.
If the configuration cannot be decrypted, the backdoor stops running.
Encrypted configuration files look as follows:
Encrypted backdoor configuration file, HiveMQ version
The encrypted portion of the HiveMQ version’s configuration contains the following parameters:
agent_privkey: the agent’s private key
channel_id: the channel identifier used to communicate with the broker
server_pubkey: the server’s public key
Decrypted blob field in the HiveMQ version’s configuration
In the Element version, the configuration file is deleted immediately after the first run, and the relevant parameters are instead written to the HKLM\Software\synapse\Config\SealedConfig registry key. On subsequent runs, the backdoor checks the registry for its configuration first.
Decrypted Element version configuration file, retrieved from the registry
The Element version’s configuration specifies the address of an Element server controlled by the attackers, a room identifier, and an access_token used to access that room. If this parameter is left empty, the backdoor prompts for the password interactively during installation. After successfully creating a session, the backdoor saves the received token to the blob field.
Communication
At startup, both backdoor versions send a GET request to http://ip-api.com/json to determine the system’s public IP address and country of origin.
The first version uses the public HiveMQ MQTT broker (broker.hivemq.com) as its C2 server. The free tier of this broker supports up to 100 concurrent connections and up to 10 GB of traffic per month. The attackers set up their own cluster and used it both to collect telemetry from compromised systems and to send commands to the backdoor.
Once a connection is established, the system’s status is sent via a POST request to
broker.hivemq.com:8883/[cluster_id]/status. The message format is:
{"online":bool,"hostname":"hostname.domain","timestamp":unix_timestamp,"location":{"json"}}.
At intervals defined in the configuration file, system information, such as CPU load and available memory, is sent via a POST request to
broker.hivemq.com:8883/[cluster_id]/metrics3. The message format is:
{cpu_percent":float,"mem_used_bytes":int,"mem_total_bytes":int,"disk_used_bytes":int,"disk_total_bytes":int,"load_1m":float,"load_5m":float,"load_15m":float,"uptime_secs":int,"hostname":"hostname.domain","timestamp":unix_timestamp}.
The backdoor sends GET requests to
broker.hivemq.com:8883/[cluster_id]/cmd/req to retrieve commands from the C2 server. The server responds in the format:
{"cmd_id":int,"command":"str","timeout_secs":int}.
Commands are executed via PowerShell.exe in hidden mode, using the -NonInteractive -NoProfile -Command parameters.
Command execution results are sent to the command server at
broker.hivemq.com:8883/[cluster_id]/cmd/res in the
{"stdout":"str","stderr":"str","exit_code":int,"duration_ms":int} format.
For the second backdoor version, the attackers set up their own Element server running on the Matrix protocol, meet.element[.]tw, as the C2 server. On this server, they created a room used to receive messages containing device information and to send commands for execution on the compromised system. The communication flow is as follows:
Once a connection is successfully established, the backdoor sends an m.bird.status message containing the system’s status. This message format is identical to that used in the HiveMQ version.
At intervals defined in the configuration file, information about the compromised system is sent as an m.bird.metrics message. Field names are slightly different from those in the first version:
{cpu_percent_x100":float,"mem_used_bytes":int,"mem_total_bytes":int,"disk_used_bytes":int,"disk_total_bytes":int,"load_1m_x100":float,"load_5m_x100":float,"load_15m_x100":float,"uptime_secs":int,"hostname":"hostname.domain","timestamp":unix_timestamp}.
This version of the backdoor supports two types of commands, distinguished by the start of the received message.
To set a new interval for sending metrics, the attackers send a message beginning with config:set_interval (accepting values from 5 to 3600 seconds). The new value is saved to the HKLM\Software\SynapseAgent\metrics_interval registry key.
Messages containing commands to execute begin with the string cmd:. Based on data extracted from Element’s SQLite databases on the compromised system, we were able to identify the account name the attackers used to send commands: panel-bot.
Received commands are executed via the Windows command line interface.
Command output is sent as an m.bird.cmd_response message. This message format mirrors the one used in the HiveMQ version.
Takeaways
We have been tracking Toy Ghouls’ activity for quite some time. We previously found that the group had expanded its arsenal with a custom ransomware strain, GenieLocker, and we have now discovered that it has also developed a backdoor capable of giving it full control over an infected device. The new tools use unconventional channels to communicate with their C2 server: the HiveMQ MQTT broker and the Matrix-based Element messenger. This shift away from publicly available open-source projects toward custom-built tools suggests that Toy Ghouls is working to make its attacks more sophisticated and to evade detection for longer.
A malicious ScreenConnect campaign in which rogue remote-access clients do more than provide attackers with hands-on control: modified clients can automatically push a multi-stage VBScript malware chain to newly connected Windows endpoints. Once deployed, the clients repeatedly spawned wscript.exe to execute four scripts 1.vbs, 2.vbs, 3.vbs, and 4.vbs from ScreenConnect-related temporary locations. The behavior is […]
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BraZetsu, a Python-based Windows malware framework allegedly operated by the Brazilian threat actor Exilware to identify, profile, and monetize compromised corporate systems. Rather than behaving like a conventional infostealer, BraZetsu appears designed to support an Initial Access Broker operation, converting infected endpoints into cataloged access offerings for an underground marketplace. The framework is reportedly the […]
While monitoring Mirage Kitten activity, we uncovered a previously undocumented malware family that we dubbed NodeRabbit. We identified the first sample on a system in Afghanistan. Further threat hunting revealed two additional, more advanced, variants: one on a system in Egypt and another on a system in Ethiopia.
NodeRabbit is a cross-platform remote access trojan (RAT) built with Node.js. It targets Windows, Linux, and macOS. Its operators deliver it through spear-phishing messages on LinkedIn and other job search platforms that contain trojanized coding challenge archives.
During the same investigation, we discovered another previously undocumented malware family that we dubbed PollCat. Like NodeRabbit, PollCat is a cross-platform RAT, but it is written in obfuscated JavaScript also distributed through trojanized coding challenge archives.
Mirage Kitten has historically relied on native malware written in languages such as C, C++, and Go, often deploying it through DLL search-order hijacking. NodeRabbit and PollCat represent the first publicly documented use of Node.js- and JavaScript-based malware by this APT group.
Kaspersky’s products detect this threat as Trojan.JS.MirageKitten.*
Background
During recent threat research, we detected suspicious activity on a system in Afghanistan. We traced it to an archive containing a software development project that the user may have received during a job application process. The archive purported to contain a coding challenge for candidates applying for an engineering role.
The archive, Front-Technical-Challenge.zip (MD5: 1EA83E4E4592B01E4ACAB63EB867BEE5), was hosted in an Amazon S3 bucket at: https://oracle-challenge.s3[.]us-east-1.amazonaws[.]com/Front-Technical-Challenge.zip
It contained TaskFlow, an app for software engineering assessment built with Express, React, and Vite. The accompanying README instructed the candidate to review the application and fix defects in its frontend. It also claimed that server.js was bug-free and should not be modified, conveniently directing attention away from the only application source file the attackers had altered.
README file for a trojanized coding challenge app
The README also imposed a three-hour time limit and prohibited the use of AI assistants. Notably, an AI code-review assistant tasked with auditing the project would likely have flagged the suspicious first-line import of an unknown npm package and warned the targeted developer that the project was trojanized.
Rules and time limit included in the trojanized coding challenge app README file
The first line of server.js imported a trojanized npm package named colorized_terminal, version 2.1.0. The attackers bundled the package directly in the challenge task archive’s node_modules directory rather than publishing it to the npm registry. When imported, the package silently launched an implant from node_modules/.cache/.320697f1/index.js as a detached background process.
Retrospective threat hunting across our telemetry revealed the broader scope of the campaign. We identified three NodeRabbit variants with a shared code lineage; each was recovered from a system in a different country. The operators delivered the variants through similarly themed coding challenges and used two trojanized packages, colorized_terminal and pretty-log, both pinned to version 2.1.0.
The campaign also delivered PollCat, a second RAT with a substantially different structure, through a separate coding challenge lure. We’ll analyze PollCat later in this research.
Initial access
The infection chain begins with fake recruiter accounts contacting prospective targets on a job search platform. According to a publicly cited source, a threat actor posing as a talent acquisition specialist at a major technology company contacted a software engineer and advertised a job opening, inviting the target to complete a technical assessment.
The target received a link to a coding challenge hosted on Amazon S3 and was pressured to download and run the project immediately. This public post matches the delivery chain we reconstructed from our telemetry: recruiter outreach on a job search platform, a coding challenge presented as a technical assessment, and a trojanized project archive hosted on legitimate cloud infrastructure.
NodeRabbit RAT: the first variant
We discovered the first NodeRabbit variant on a system in Afghanistan. The malware was concealed within the TaskFlow assessment at node_modules/.cache/.320697f1/index.js and executed by the trojanized colorized_terminal package.
Once running, NodeRabbit generates a unique agent identifier from available host information. It calculates the SHA-256 hash of the hostname, username, operating system version, architecture, and MAC address, then truncates the result to its first 32 hexadecimal characters.
NodeRabbit binds a TCP listener to 127.0.0.1:48739. This listener acts as a single-instance mechanism. If the malware cannot bind to the port, it assumes that another instance is already running and terminates silently.
NodeRabbit uses a persistence mechanism for each operating system:
Operating system
Persistence mechanism
Windows
Copies itself to %APPDATA%\Microsoft\EdgeUpdate\msedge_update.js; clones the local node.exe to nodew.exe in the same folder and patches its PE subsystem from Console to Windows GUI to suppress the console window; creates HKCU\Software\Microsoft\Windows\CurrentVersion\Run\MicrosoftEdgeUpdate registry key executing nodew.exe msedge_update.js
Linux
Copies itself to ~/.config/microsoft-edge-update/msedge_update.js and creates an @reboot cron entry that invokes the script using the current Node.js executable.
macOS
Copies itself to ~/.config/microsoft-edge-update, creates ~/Library/LaunchAgents/com.microsoft.edgeupdate.plist configuration file pointing at the copy’s location with RunAtLoad and KeepAlive parameters, and attempts to load it.
The malware communicates with its command-and-control servers through three API endpoints, choosing from the following Azure-hosted C2 infrastructure addresses. On failure, it switches to the next C2 address:
NodeRabbit serializes each C2 request object as JSON and wraps it with AES-256-GCM. The AES key is the SHA-256 digest of an ASCII seed embedded into the agent. Every request uses a fresh 12-byte IV and a 16-byte authentication tag:
The malware sends encrypted requests using the following structure:
C2 responses are structured the same way and may contain a command to execute. We observed the first NodeRabbit variant supporting 11 commands:
Command
Functionality
sys:info
Return hostname, domain user information, username, and process ID.
proc:list
List running processes.
proc:start
Execute an arbitrary shell command.
fs:list
List a directory.
fs:read
Read a file in chunks and return Base64 data.
fs:write
Decode Base64 and write it at a chosen file offset.
fs:delete
Delete a file or recursively delete a directory.
fs:mkdir
Create directories recursively.
net:config
Enumerate adapters, MAC addresses, IP addresses, and DNS settings.
agent:sleep
Change the beacon interval.
script:exec
Write a base64 Node.js script to a randomly named .tmp file, execute it and delete it.
NodeRabbit RAT: the second variant
Retrospective threat hunting following the discovery in Afghanistan led us to a second infection on a system in Egypt. This sample is a more advanced NodeRabbit variant, launched through the trojanized pretty-log package instead of colorized_terminal.
Before running its core functionality, the malware checks whether the host resembles an analysis environment. It terminates if it detects limited system memory, a low CPU count, short system uptime, analyst-associated usernames or hostnames, or common analysis tools running on the system.
Before terminating, the malware generates benign HEAD requests to www.google.com, www.microsoft.com, and www.cloudflare.com, then exits without ever contacting its C2 infrastructure. Most likely, it attempts to look less suspicious by showing some benign activity before exiting.
Variant 2 implements partial corporate proxy support: it checks HTTP(S) proxy environment variables, Windows Internet Settings, including an explicit PAC URL, and WinHTTP configuration; tunnels its HTTPS C2 through HTTP CONNECT. It first tries to establish an unauthenticated connection. If it fails, it retries using URL-embedded basic credentials. Finally, it delegates Windows NTLM/Negotiate challenges to curl.exe --proxy-anyauth --proxy-user. It caches the proxy-discovery result, including when no proxy is found, for five minutes. If the polling loop detects a network-interface or IP-address change, it clears the cache and runs proxy discovery again on the next checkin.
To make sure a single instance is running, Variant 2 uses a host-specific port derived from the agent identifier instead of the fixed TCP port used by the first variant. It interprets the first four hexadecimal characters of the identifier as an integer and applies the following calculation: 41984 + (value mod 5000).
The resulting listener port falls between 41984 and 46983. Unlike the shared port used by Variant 1, this port varies depending on the infected host.
For persistence, Variant 2 masquerades as Intel Driver & Support Assistant. The exact persistence mechanism, once again, depends on the operating system.
Operating system
Persistence mechanism
Windows
Copies itself to %LOCALAPPDATA%\Intel\DSA\idriver_support.js. It then copies the local node.exe binary to IntelDSA.exe and changes its PE subsystem from Console to Windows GUI, suppressing the console window. Finally, it creates a scheduled task named IntelDriverSupportUpdate, which runs daily at 10AM and executes IntelDSA.exe with the dropped script.
Linux
Copies itself to ~/.config/intel-dsa/idriver_support.js and creates an @reboot cron entry.
macOS
Copies itself to ~/Library/Application Support/Intel DSA/idriver_support.js and creates the LaunchAgent com.intel.dsa.helper with RunAtLoad and KeepAlive enabled.
NodeRabbit RAT: the third variant
Further threat hunting identified a third NodeRabbit variant on a system in Ethiopia. Like the second variant, it is launched through the trojanized pretty-log package. It retains much of the previous variant’s functionality but introduces significant changes to its command-and-control configuration, command set, and persistence mechanisms.
The third variant communicates with its C2 infrastructure through a different set of API endpoints:
Method
Endpoint
Purpose
POST
/sdk/v2/ready
Register agent and host info
POST
/sdk/v2/config
Poll for commands
POST
/sdk/v2/events
Submit results
We observed the malware using a C2 chain composed of Azure- and Cloudflare-hosted domains.
For persistence, Variant 3 implements the following mechanisms depending on the operating system in use:
Operating system
Persistence mechanism
Windows
Attempts to copy the payload to ProgramData or LocalAppData, create a build-specific daily 10AM task, and start the copied payload. To choose the exact directory, it tries to list C:\Windows\System32\config. If successful, it selects ProgramData with /ru SYSTEM /rl highest; in case of a failure, it selects LocalAppData without explicit /ru or /rl settings.
macOS
Copies the payload to ~/Library/Application Support, creates and loads a RunAtLoad/KeepAlive LaunchAgent and starts the copied payload.
Linux
Copies the payload to ~/.local/share, attempts to add an @reboot cron entry, and starts the copied payload. If crontab -l fails, persistence is skipped.
WSL
Uses the payload copied for persistence on the main Linux system, as described above. Writes launcher.vbs under the Windows user profile, and creates a daily 10AM Windows task that relaunches it through wscript.exe and wsl.exe.
A new command, agent:servers, replaces the active in-memory C2 server list and can write the updated list to .sv.json. The third variant retains the original 11 commands and adds 12 new ones, bringing the total to 23.
New commands
Functionality
fs:drives
Enumerate accessible Windows drive letters or WSL-mounted drives
proc:exec
Execute a process
proc:kill
Kill process by PID or image name
agent:servers
Replace the active C2 and attempt to keep the new configuration
agent:getchain
Return the current C2
outlook:emails
Harvest account addresses from Outlook OST and PST artifacts
persist:check
Check selected VS Code, scheduled-task, and Run-key persistence indicators
persist:vscode
Attempt to install a fake VS Code extension and Windows Run value
persist:vscode:remove
Remove the fake extension
persist:projects:scan
Search recent and common development locations for Git repositories
persist:project:inject
Inject a launcher into a repository’s Git hooks
persist:project:remove
Remove the marked Git-hook launcher
Beyond the persistence mechanisms described above, Variant 3 introduces two additional persistence mechanisms that relaunch the malware through common developer workflows.
1. Malicious VS Code extension
The persist:vscode command first copies the payload to its build-specific install path. If a compatible extension directory exists, it creates a fake extension displayed as GitHub Copilot Helper, with the description AI coding assistant helper service and the activation event on StartupFinished.
The extension’s extension.js file attempts to start the installed payload as a detached Node.js process. To look less suspicious to the user, it uses a trusted publisher name borrowed from local extension metadata or a trustedPublishers value found in state.vscdb. However, no signature or trusted status is copied.
Separately, the handler tries to disable Workspace Trust if the VS Code User directory exists. On Windows, it attempts to establish persistence using a current-user Run registry key value even if the extension directory is missing.
2. Git hook injection
Git-hook persistence works in two steps. First, persist:projects:scan checks recent VS Code workspace paths directly. Under common locations such as ~/projects and ~/source, it checks only the first 60 immediate children, not the root itself, and returns no more than 20 repositories.
For a selected repository, persist:project:inject appends a marked launcher to .git/hooks/post-merge and .git/hooks/post-checkout by default. The marker is # shepherd-persist; the line following the marker attempts to start the installed payload with Node in the background. A later Git operation must trigger one of those hooks, and the referenced Node executable and payload must still exist.
PollCat RAT
While tracking NodeRabbit infections, we discovered another malicious tool we dubbed PollCat, which is also distributed under the guise of a programming challenge. The sample we obtained resides inside RankChallenge-react, a React code-fixing challenge presented as a time-limited developer assessment. Running the project invokes npm i && node index.js, which starts the local application and attempts to open the challenge in the user’s browser.
Although the visible exercise is not a security CTF, the project uses CTF terminology in several places. The root package is named ctf-server, the backend prints CTF server running, the frontend uses several ctf-* storage keys, and the tutorial refers to path/to/ctf. These repeated labels, together with instructions that do not fully match the delivered application, are consistent with an AI-assisted or template-generated project. One possible explanation is that the attacker prompted an AI coding assistant to create a CTF-style React platform and later inserted the malicious components.
README instructions and challenge overview included in the trojanized React coding project
The PDF tutorial contained in the same archive as the project tells the target to click Continue, enter a six-digit OTP code, and complete the challenge within a one-hour session. It states that codes are supplied by the recruiter, are single-use, and expire quickly; the visible login page also claims that codes rotate every 30 seconds. In the delivery scenario described by the investigation, the threat actor posing as a recruiter could provide the code directly to the targeted developer. This gives the operator control over access to the lure, while the expiring code and countdown create a sense of urgency, pressuring the target to run the project and complete the assessment quickly, potentially accelerating the infection process.
One-hour session window enforced by the trojanized coding challenge
The bundled .env file contains the JWT signing secret, OTP service URL, and OTP client ID.
Configuration embedded in .env file of the trojanized coding project, including the OTP service URL and client identifier
The application forwards submitted codes to an attacker-managed domain registered in late June-2026: https://lifespotify[.]com/api/users/b879746e-fed9-4211-a6da-4d8223681267/otp/validate.
That said, PollCat starts independently of the OTP authentication process. During application startup, app.js loads requireAuth.js, which imports and immediately starts the malicious requireObjects.js component. PollCat can therefore begin C2 registration and command polling while the application is still loading, before the user enters an access code.
A failed OTP validation prevents the user from accessing the protected challenge features, but PollCat continues running in the background. A successful OTP validation issues a JWT and creates another worker that starts an additional PollCat instance. The first authenticated request also triggers the persistence attempt.
Persistence starts when the first request carrying a valid JWT reaches the protected middleware. PollCat then uses one of the following methods:
Operation system
Persistence mechanism
Windows
Writes package.json and requireObject.js to %APPDATA%\Microsoft\Network, runs npm install, and creates a daily task named NetSync_<username> and scheduled for 09AM that runs the worker with Node.js.
Linux
Writes the worker to ~/.node_packages, runs npm i, and appends both a daily 09AM cron line and an @reboot line.
macOS
Uses the same ~/.node_packages copy and cron path, then creates and loads ~/Library/LaunchAgents/com.harsh.requireobject.plist with RunAtLoad and a daily 09AM trigger.
Once active, PollCat identifies the host as 129--<hostname> and iterates over the following C2s until registration succeeds:
After registration, PollCat sends host information to /gate/hello, polls /gate/fetch for commands, and returns results through /gate/submit. All endpoints in use are presented in the table below.
Method
Endpoint
Purpose
POST
/beacon
Register the client and obtain a socketId and optional timing values.
POST
/gate/hello
Submit host, user, domain, OS information, and its current privilege level.
GET
/gate/fetch?token=<socketId>
Poll for commands.
POST
/gate/submit
Submit a Base64-encoded command-result structure.
GET
/vault/<uuid>
Retrieve a hosted file and write it to the victim machine.
PUT
/vault/push/
Upload a local file or file chunk to the C2.
POST
/gate/track
Report chunk-upload progress.
By default, PollCat RAT polls every two minutes with up to five seconds of jitter. Commands and results are stored as little-endian binary records and carried as Base64 text.
PollCat RAT declares 22 commands, but three of them have no implementation:
Command
Functionality
0x02 (DIR)
List a directory.
0x03 (MV)
Move a file or directory.
0x04 (RUN)
Execute a shell command.
0x05 (TASKLIST)
List running processes.
0x06 (DEL)
Delete a file or directory.
0x07 (UPLOAD)
Download a file from the C2 to the victim’s machine.
0x08 (DOWNLOAD)
Upload a local file to the C2.
0X09 (DRIVES)
List drives, volumes, or mount points.
0X0A (TERMINATE)
Terminate a process by PID.
0X0B (RUNDLL)
Load a DLL and call an exported function on Windows.
0X0C (MKDIR)
Create a directory.
0X0D (ZIP)
Create or extract a ZIP archive.
0X0E (CHUNKED_DOWNLOAD)
Upload a local file in chunks.
0X0F (RUN_HIDDEN)
Start a hidden background process.
0X20 (EVAL_JS)
Execute JavaScript supplied by the C2.
0X30 (SYSTEM_CHECK)
Collect process and software inventory.
0XA1 (WS_DOWNLOAD)
Defined but not implemented.
0xB0 (REQUEST_ELEVATION)
Defined but not implemented.
0XB1 (PERSIST)
Defined but not implemented.
0xF0 (SET_SLEEP_TIME)
Change the polling interval.
0XF1 (SET_IDLE_TIME)
Store an idle-time value.
0xF2 (SET_JITTER_TIME)
Change polling jitter.
The command names UPLOAD, DOWNLOAD, and CHUNKED_DOWNLOAD are written from the C2’s perspective. UPLOAD sends a C2-hosted file to the victim’s machine, while the two download commands transfer victim files back to the C2.
EVAL_JS runs JavaScript supplied by the C2 and gives that code access to Node.js modules, files, processes, networking, and child-process functions. SYSTEM_CHECK collects the names of running processes and lists files and folders from:
%SystemDrive%\Program Files
%SystemDrive%\Program Files (x86)
%LOCALAPPDATA%
%LOCALAPPDATA%\Programs
%APPDATA%
%USERPROFILE%
%APPDATA%\Microsoft\Outlook
%LOCALAPPDATA%\Microsoft\Olk\Attachments
%USERPROFILE%\Documents
It also searches for folders matching 24 hardcoded strings corresponding to security software vendor names: ‘Google’, ‘Microsoft’, ‘Palo Alto Networks’, ‘Cisco’, ‘VMware’, ‘Fortinet’, ‘Citrix’, ‘CheckPoint’, ‘Juniper Networks’, ‘LogMeIn’, ‘Sophos’, ‘Symantec’, ‘Trend Micro’, ‘McAfee’, ‘Kaspersky Lab’, ‘ESET’, ‘Bitdefender’, ‘Avast Software’, ‘CrowdStrike’, ‘SentinelOne’, ‘Malwarebytes’, ‘BraveSoftware’, ‘Tencent’, and ‘Naver’.
When PollCat finds a matching folder, it lists that folder’s root contents. It does not recursively scan the entire product directory. The detailed inventory, including process names, directory listings, and collected paths, is sent as JSON to POST /api/system-details/result.
Infrastructure
Mirage Kitten continues to rely on Azure Websites and Cloudflare-backed domains to hinder infrastructure discovery and tracking. More importantly, the use of Microsoft Azure subdomains for C2 helps the traffic blend into legitimate organizational network activity. In some cases that we encountered during our research, the actors even incorporated the targeted organization’s name into the Azure subdomain, making C2 communications appear more like normal business traffic originating from an employee machine during regular business days.
Based on our analysis of Mirage Kitten’s infrastructure, we identified certain patterns across several command-and-control channels, including msmanagementgrp[.]com and visitfinancedentists[.]com
Further investigation based on these patterns led to the discovery of approximately 11 additional infrastructure assets attributed to the same group.
Domain
Creation date
Registrar
healthful-hub[.]com
2026-07-03
NameCheap, Inc.
neumedicahealthcare[.]com
2026-07-03
NameCheap, Inc.
optimumhealthcredit[.]com
2026-07-03
NameCheap, Inc.
healthfullyrecipes[.]com
2026-06-30
NameCheap, Inc.
refreshhealthandwellness[.]com
2026-06-09
NameCheap, Inc.
healthvitalitycare[.]com
2026-05-18
NameCheap, Inc.
aceofspadesmanagement[.]com
2026-05-18
NameCheap, Inc.
glmediaagency[.]com
2026-05-18
NameCheap, Inc.
digimediaskill[.]com
2026-05-18
NameCheap, Inc.
healthyweightplan[.]com
2026-05-18
NameCheap, Inc.
mens-health-online[.]com
2026-05-15
NameCheap, Inc.
Victims
Based on our telemetry, we identified victims in fintech, aviation and aerospace sectors across the Middle East and Africa – specifically, in Egypt, Ethiopia and Afghanistan.
We also observed submissions of ZIP archives with trojanized projects containing NodeRabbit and PollCat to an online multi-scanner originating from several countries, including India, Türkiye, Israel, Iraq, Germany, and Ireland.
Attribution
We attribute this activity to Mirage Kitten with a high degree of confidence based on the following observations:
Structural similarities with the Retrograde/MiniFast native DLL backdoor (MD5:810F8E3B88EB05F710C09552941D6F56)
Initial C2 handshake and session establishment logic. Both PollCat and Retrograde/MiniFast follow a similar C2 handshake flow. Each builds a JSON request body containing host information and sends it via an HTTP POST request. Notably, both treat HTTP 400 as a successful handshake response rather than an error, parsing the response body to extract a socketId, which is then stored and used as the session token for subsequent C2 communication.
Similar C2 handshake and socketId session establishment logic in MiniFast/Retrograde and PollCat
Host registration. Both PollCat and Retrograde/MiniFast register the infected host with the C2 server by sending a structurally similar JSON request body containing the session token and host information.
Command fetching similarities. The similarities extend to command retrieval. Both PollCat and Retrograde/MiniFast periodically poll the C2 server using an HTTP GET request containing the previously assigned socketId as a token. Retrograde/MiniFast uses GET /agent/poll?token=<socketId>, while PollCat follows the same pattern with GET /gate/fetch?token=<socketId>, demonstrating a closely aligned C2 communication structure.
Beacon timing similarities. PollCat and the Retrograde/MiniFast share identical beacon timing defaults: a polling interval of 120,000 ms (0x1D4C0), a jitter of 5,000 ms (0x1388), and a retry timeout of 60,000 ms (0xEA60). This further highlights the structural similarities between the two C2 communication implementations.
Command set similarities. PollCat and Retrograde/MiniFast share several commands and command IDs. Notably, PollCat declares REQUEST_ELEVATION (0xB0) and PERSIST (0xB1) but does not implement them. In MiniFast, both are functional: 0xB0 performs UAC elevation, while 0xB1 creates the WindowsSecurityUpdate scheduled task for persistence.
Command set similarities between MiniFast/Retrograde and PollCat, including shared command identifiers
Proxy authentication similarities. NodeRabbit delegates corporate-proxy NTLM/Negotiate authentication to curl.exe --proxy-anyauth --proxy-user, using the victim’s logon session. Retrograde/MiniFast native DLL implements the same approach natively through WinHttpQueryAuthSchemes and WinHttpSetCredentials with NULL credentials. This shared proxy-aware C2 design suggests the same development approach across both malware families.
Speaking of victimology, the attacks are consistent with Mirage Kitten’s known geographic targeting, with the group maintaining a strong focus on entities across Africa and the Middle East, this time with a particular focus on the aviation and FinTech sectors.
As for the operational infrastructure, Mirage Kitten has historically hosted its initial ZIP lures on legitimate third-party services. Previously, it used onlyoffice.com for this purpose. In this activity, the group shifted to Amazon S3 buckets.
Finally, the combination of Azure Websites and Cloudflare‑backed domains has been a hallmark of Mirage Kitten’s TTPs, which we have observed across NodeRabbit and PollCat.
Conclusions
Mirage Kitten’s latest activity marks a notable evolution in the group’s tooling: NodeRabbit and PollCat are the group’s first Node.js/JavaScript-based implants, departing from its usual native malware deployed through DLL search-order hijacking. The shift to cross-platform scripting gives the operators a single codebase that runs on Windows, Linux, and macOS, with payloads that blend naturally into developer workstations.
The delivery mechanism, however, remains consistent with Mirage Kitten’s historical tradecraft: the use of recruiter personas on LinkedIn to target critical sectors across the Middle East and Africa for cyberespionage purposes. We continue to track the group’s activity and will report on new developments in future publications.
Attackers typically try to pass off malware as legitimate applications or as potentially unwanted programs that users deliberately search for and download, such as cheats or cracks. They often rely on ad and affiliate networks to deliver their creations to victims’ devices. This post examines a less conventional case: a well-known backdoor distributed under the guise of adware. The attackers may have chosen this distribution method because the adware was signed by the developer. On top of that, users often manually add these apps to exclusions, so their useful features don’t get blocked.
Some time ago, a client asked us to analyze a file with the MD5 hash c24e99f9437feacaa63766a3cde3fe3d and add it to our detection database. We initially classified it as adware, but a cursory analysis turned up suspicious network activity, which prompted us to dig deeper. It turned out the sample did far more than serve ads. In fact, its advertising functionality doesn’t even work; instead, it triggers an infection chain that delivers the ValleyRAT backdoor.
Malicious installer
The file the client shared with us turned out to be an installer that performed different actions depending on the two-letter suffix used in the file name, positioned just before the numeric string.
Installer name
What it does
FS_SETUP_DD_173.exe
Installs DingTalk, a workplace collaboration platform
FS_SETUP_GG_173.exe
Installs Google Chrome
FS_SETUP_HY_173.exe
Opens hxxps://meeting[.]tencent[.]com/download/
These actions are most likely designed to divert the user’s attention away from the sample’s malicious functionality. Regardless of the file name, the installer deploys a modified Chinese desktop wallpaper management tool called QN Wallpaper (hxxps://qnwallpaper[.]keansoft[.]cn/) and adds it to the registry’s autorun entries.
The original version of QN Wallpaper is genuine adware: on installation, it delivers bundled partner apps to the device and then displays ad banners to the user. In this case, however, the attackers use it to carry out DLL sideloading, a technique that allows malicious code to run under the guise of a signed process by way of a malicious DLL.
The QN Wallpaper modules, along with the malicious components, are unpacked to C:\Program Files\QNWallpaper\5.4.0.1662\<random string of letters and digits>. The following files are saved in that directory:
File name
MD5
Purpose
1.zip
7ad1e3ef4e6d9d636c9e7e967733850e
Archive containing the adware files QnWallpeper.exe and QnwPlayer.exe, along with the modules needed to run them
7z.dll
96b4c1d0683dce22bd3223e1e40689c1
7z archiver library
7z.exe
9b86d3ab6cef15c633933fbbeab39c0a
Archiver
chrome_elf.dll
edfdc30cbd85879776b8f735ea7de1f1
Library used to launch Electron-based applications
libcef.dll
07ddbbe2c71c45577a7a4fbcdba0df91
Malicious library
PeLoader
48826d5ca845979d2e6ebd66dc1aae90
File containing the encrypted backdoor
QnWallpaper.exe
6c158c0f8e029342192d4f0d72e102b7
Adware module
QnwPlayer.exe
9a71d6a41cd258b9e89cdc5fc224de73
Adware module
<random string of letters and digits>Nedca.exe
c24e99f9437feacaa63766a3cde3fe3d
Malicious installer copy
After unpacking, the installer uses the DisableAntiSpyware registry key to disable Windows Defender and then launches QnWallpaper.exe.
Disabling Windows Defender
DLL Sideloading via libcef.dll
QnWallpaper.exe has dependencies in libcef.dll, so this library gets loaded when the process starts. QnWallpaper.exe also launches QnwPlayer.exe, which likewise calls libcef.dll.
QnWallpaper and QnwPlayer won’t actually function correctly, because the functions exported from libcef.dll are put into an infinite sleep. However, in case that sleep is ever interrupted, the attackers have implemented a function that loads all the necessary functions from the original library into memory, provided it can locate that library on the system.
Example of an exported function
Loading functions from the original libcef.dll
The malicious functionality in libcef.dll is invoked by a call to DllMain, which runs automatically when the library is loaded. That said, alongside the original exports, the library also contains a function named RunDLL, which likewise initiates execution of the malicious code. QnWallpaper never calls this function. We suspect the attackers intended to invoke it manually via rundll32 or planned to use a separate executable for this purpose, one that wasn’t included in the package downloaded by the sample.
The RunDLL function
Running the malicious code
When the library is loaded, code runs that ensures QnWallpaper.exe persists at startup: it adds a file extension association and drops a file with the corresponding extension in C:\Documents and Settings\<username>\Start Menu\Programs\Startup\.
This is followed by a chain of wrapper functions whose main job is to call the next one. Execution eventually reaches the function that contains the actual malicious code. For convenience, we’ll refer to it as mw_entry.
Inside mw_entry, the malware checks two things:
Whether the current user belongs to the Administrators group
Which process the DLL is running inside
Checking for administrator privileges
If the user isn’t a member of the Administrators group, the program attempts to obtain administrator privileges by using the runas utility.
Relaunching the process to obtain administrator privileges
Once it has administrator privileges, the malicious code determines which process the DLL has been loaded into, and selects the payload accordingly:
If the library is running inside QnWallpaper.exe, the payload is loaded from the PeLoader file.
Encrypted payload
If the library is running inside QnwPlayer.exe, the payload is loaded from libcef.dll resources.
Retrieving the payload from a resource
Both payloads are AES-encrypted DLLs that contain the ValleyRAT backdoor. The only difference between them is their configuration, specifically, the C2 server addresses. After decryption, libcef.dll checks the magic signatures in the resulting PE file’s headers to confirm the sample is valid. If this check fails, the library releases its resources and takes no further action.
Validating the PE file headers after decryption
If the headers check out, libcef.dll loads the payload into the process’s memory space and hands control over to the backdoor by calling DllMain.
Calling DllMain
ValleyRAT
ValleyRAT begins its operation by parsing its configuration, which consists of key:value pairs concatenated into a single string. To obfuscate this configuration, the attackers wrote the string in reverse.
Obfuscated configuration
During parsing, the backdoor restores the correct character order and reads the key values one by one. The set of keys is the same regardless of which process the backdoor is running in.
Parsing the configuration
Some of the configuration fields are listed below:
Key
Description
p?
C2 server IP address
o?
C2 server port
t?
Protocol (1: TCP, 0: UDP)
dd
Sleep duration before executing the main code
cl
Sleep duration after receiving the corresponding command from the server
bz
Configuration creation date
bh
Whether to mark the current process as critical (so that terminating it triggers a blue screen of death) Possible values: 1: yes, 0: no
ll
Whether to check for running security/traffic-analysis tools/processes (1: check, 0: do not check)
sh
Whether to inject code into svchost that will restart the malicious process (1: inject, 0: do not inject)
The backdoor uses several techniques to protect its process. Some are configuration-dependent, while others are always applied:
Injecting code into svchost to restart the process: a configurable option. The backdoor allocates memory inside the svchost process, injects code into it, and sets PAGE_NOACCESS permissions on the memory page containing the injected data. It then creates a suspended thread, waits 60 seconds, grants read, write, and execute permissions on the page, and resumes the thread.
Injecting code into svchost
The function injected into the process has a single job: restart the backdoor if its execution is interrupted for any reason.
Injected function
Marking its own process as critical (so that terminating it triggers a blue screen of death): a configurable option.
Setting its own process as critical
Restarting on an unhandled exception. This protection mechanism is always active, regardless of the backdoor’s configuration.
Restarting on exceptions
The backdoor also has spyware functionality. While running, it tracks keystrokes and the currently focused window by using functions from the DirectInput8 library. It also captures clipboard contents. All collected data is saved to a file on disk.
Capturing clipboard data
If the ll key in the configuration is set to 1, ValleyRAT periodically checks for active windows belonging to applications that could be used to analyze processes or traffic. Window enumeration is done via the EnumWindows function, using the following callback:
Window name checks
After completing these checks, the backdoor collects system information, including:
Host name
Host IP addresses
User idle time
Detailed Windows version information (ProductName, EditionId, DisplayVersion)
Number of CPU cores
Free disk space
Graphics adapter
Currently focused window and its title
System bitness
Language settings
Path to the system directory
On command, the backdoor can perform the actions typical of this malware category:
Rebooting the computer
Shutting down the computer
Taking a screenshot
Wiping logs
Updating its C2 addresses
Downloading additional modules
Sending keylogger logs along with clipboard contents
Snippet of the command handler
Let’s take a closer look at the module-loading functionality. Upon receiving the corresponding command with a link from its operator, the backdoor downloads the file at that link and executes it. The download can come from either the C2 server or a third-party address.
The DownloadPeFile function is responsible for downloading a PE file
The DownloadAndExecute function calls DownloadPeFile, then launches the downloaded module
Additional modules can take the form of purpose-built dynamic libraries or shellcode. If the payload is shellcode, the backdoor uses process hollowing with svchost to launch the module.
Implementation of the process hollowing technique
If the module is a dynamic library, the backdoor loads the PE file into its own process, calls DllMain, and searches for a Main function among the exported functions. Once Main has been called, the library is unloaded from memory.
Calling DllMain after the backdoor loads the PE file
Targets and attribution
Over the course of 2026, we detected the ValleyRAT backdoor and its associated malware more than 100,000 times, with more than 1500 unique users affected, primarily in China and India.
This attack geography, combined with the use of the ValleyRAT backdoor, points to Silver Fox, a known operator of this malware family, as the likely group behind the campaign.
Conclusion
This case is a clear example of how adware and affiliate networks can turn out to be far more dangerous than they appear. ValleyRAT is a sophisticated backdoor capable of collecting sensitive data such as keystrokes and clipboard contents, taking screenshots, and delivering additional malicious modules. The attackers exploited a well-known adware application to run the backdoor under the guise of a signed process, which complicates detection.
Motivated by both cyberespionage and financial gain, Silver Fox targets organizations across multiple countries. To stay protected, organizations should keep employee cybersecurity awareness up to date and enforce clear policies on the use of third-party software on work devices.
For individual users, we recommend avoiding the installation of software with a questionable reputation, and, even more importantly, never adding such software to your security solutions’ exclusion lists.
Australian authorities have charged two alleged TeamPCP members after software supply chain attacks exposed over 500,000 credentials and at least 300GB of data.
In Q2 2026, the percentage of ICS computers on which malicious objects were blocked continued to decrease, falling to 19.15%, its lowest level since 2022.
Percentage of ICS computers on which malicious objects were blocked, Q3 2023–Q2 2026
Regionally, the percentages ranged from 8.1% in Northern Europe to 27.9% in Africa.
Regions ranked by percentage of attacked ICS computers
The figures increased in five regions over the quarter, most notably in East Asia (by 2.0 pp) and Africa (by 0.5 pp).
East Asia saw increases in percentages for all threats except miners. The region ranked first in terms of growth for malicious scripts and phishing pages, spyware, and viruses. East Asia also led in terms of growth in threats from the internet. The percentage of ICS computers on which email threats were blocked also increased.
Selected industries
The biometrics sector (26.44%) has traditionally 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. Biometric systems are characterized by the availability of internet access, extensive email use for data exchange and approvals (e.g. access granting), and, in many cases, minimal cybersecurity controls within the organizations that use them.
Industries ranked by percentage of ICS computers on which malicious objects were blocked
The biometrics sector ranked first among industries in terms of the following threat categories: malicious scripts and phishing pages, malicious documents, spyware, ransomware, and worms. The sector is also leading among industries in terms of email threats. At the same time, unlike other industries, the percentage of affected ICS computers for email threats in biometrics exceeds that for internet threats.
In all selected industries, the global average follows a downward trend.
Threat categories
In Q2 2026, Kaspersky security solutions blocked malware from 10,904 different malware families of various categories on industrial automation systems.
Over the quarter, the percentage of ICS computers on which malicious objects of the following categories were blocked increased: denylisted internet resources, malicious documents, worms, ransomware, and malware for AutoCAD.
Percentage of ICS computers on which the activity of malicious objects from various categories was blocked
Malicious scripts and phishing pages (JS and HTML)
Malicious scripts and phishing pages remained in first place in the threat category rankings based on the percentage of ICS computers on which the respective threats were blocked. In Q2 2026, the global average dropped to 5.42%.
Over the quarter, the figure for this category only increased in East Asia, rising by 0.93 pp to 4.86%. This is the second-highest figure in the region in the last three years.
In East Asia, the percentage of ICS computers affected by malicious scripts and phishing pages increased in all the industries surveyed, except construction. The highest figures were recorded for biometrics (9.01%) and building automation (6.49%).
Denylisted internet resources
In Q2 2026, denylisted internet resources rose in the threat category rankings from third to second place, displacing spyware. Globally, the percentage of ICS computers on which denylisted internet resources were blocked has been increasing for two quarters in row and reached 4.31%.
The figures increased in all regions over the quarter, most notably in Russia (by 1.33 pp). Moreover, Russia ranked first (5.17%) among the regions in terms of denylisted internet resources. Since 2022, the region has topped these rankings twice before, both times in Q2: in 2022 and 2024.
Among the selected industries in Russia, the highest figures for the denylisted internet resources were in the electric power (6.61%) and engineering and ICS integration (5.62%) industries.
Malicious documents (MSOffice + PDF)
Malicious documents ranked fourth in the threat category rankings by the percentage of ICS computers on which they were blocked. The percentage for this category decreased over the previous three quarters, reaching its lowest level in three years. However, in Q2 2026, it increased to 1.77%.
Over the quarter, the figures for malicious documents increased in seven regions, most notably in South America (by 1.35 pp) and Southern Europe (by 0.48 pp). These two regions are among the top three in terms of malicious documents, malicious scripts and phishing pages, as well as threats from email clients.
South America ranked second in the rankings of regions in terms of malicious documents. In Q2 2026, the percentage of ICS computers in the region on which this threat was blocked was 3.56%, which was the fourth highest in three years.
Among the selected industries in South America, the highest percentage of ICS computers on which malicious documents were blocked was in biometrics (6.67%).
Southern Europe ranked first in the rankings of regions in terms of malicious documents. In the previous quarter, the percentage of ICS computers in the region on which this threat was blocked was the lowest in three years, but in Q2 2026 it increased to 3.63%.
Among the selected industries in Southern Europe, the highest percentage of ICS computers on which malicious documents were blocked was once again in biometrics (11.48%).
Spyware
Spyware ranked third in the threat category rankings based on the percentage of ICS computers on which it was blocked. The percentage for this category (3.30%) is the lowest since 2022.
Over the quarter, the figures increased in three regions, most notably in East Asia (by 0.53 pp) and Southeast Asia (by 0.42 pp).
East Asia ranked third based on the figures for spyware (4.77%), behind Africa and Southeast Asia. This is the region’s highest rate since Q2 2025. Among the countries and territories in the region, the highest percentage of ICS computers on which spyware was blocked was in mainland China (6.61%). Among the selected industries in East Asia, the highest figures for spyware were in the electric power (11.75%) and manufacturing (5.87%) industries. In all the industries surveyed, the figures are higher than the regional average.
Southeast Asia ranked second after Africa in the ranking of regions in terms of spyware, with 5.32%. Among the selected industries in Southeast Asia, the highest figures for spyware were in biometrics (8.93%) and manufacturing (7.32%). The figures increased in all industries over the quarter.
Ransomware
The percentage of ICS computers on which ransomware was blocked decreased in the previous three quarters but increased to 0.16% in Q2 2026.
During the quarter, the percentage increased in all regions, except Western and Southern Europe and North America (Canada). Africa led the ranking in terms of growth for this metric.
In Q2 2026, Africa ranked first among the regions in terms of the percentage of ICS computers on which ransomware was blocked (0.29%). The only time the figure in the region was higher in the past three years was Q2 2025 (0.31%).
Among the selected industries in Africa, the highest figures for ransomware were in the electric power industry (0.72%) and biometrics (0.52%). Over the quarter, the figures increased in all industries, except manufacturing and construction. The biggest increase was recorded in the electric power industry.
In Russia, the percentage of ICS computers on which ransomware was blocked in biometric systems has increased for three consecutive quarters, reaching 1.22%. This is the highest level of ransomware across all industries in all regions.
Miners
In Q2 2026, the percentage of ICS computers on which miners were blocked was the lowest since 2021, for both miners in the form of executable files for Windows (0.48%) and web miners running in browsers (0.14%).
The figures for both categories decreased in all regions, except for Africa where figures for miners in the form of executable files for Windows increased slightly.
On average, the oil and gas industry led the rankings among the selected industries both in terms of miners in the form of executable files for the Windows OS (0.66%) and in terms of web miners (0.34%).
Worms
In Q2 2026, the percentage of ICS computers on which worms were blocked increased to 1.43%.
In Q2 2026, the Middle East (2.11%) was second (after Africa) in the rankings of regions in terms of worms, displacing Central Asia and the South Caucasus.
Among the selected industries in the Middle East, the highest percentage of ICS computers on which worms were blocked was in building automation (2.90%). Over the quarter, the figures increased in all industries.
Australia and New Zealand ranked 12th among the regions in terms of the percentage of ICS computers on which worms were blocked (0.41%). Over the past three years, the figure in this region was only higher in Q2 2024 (0.42%). The figures increased in all the surveyed industries in the region, most notably in manufacturing and electric power. As a result, for these industries they exceeded the regional average by 2.9 and 2.3 times, respectively.
Viruses
In Q2 2026, the percentage of ICS computers on which viruses were blocked decreased to 1.29%.
The top three regions for this metric remain unchanged: Southeast Asia (6.03%), Africa (4.22%), and East Asia (3.14%). These same regions lead the rankings in terms of malware for AutoCAD.
The figures increased in three regions: East Asia, Australia and New Zealand, and Africa, where it has been growing for four consecutive quarters and reached its highest value since 2022.
Among the selected industries in Africa, the highest percentage of ICS computers on which viruses were blocked was in construction (5.47%).
East Asia ranked third among the regions in terms of viruses, reaching the highest level in the region for the past three years. Among the countries and administrative regions of East Asia, mainland China is the clear leader in terms of viruses (5.07%).
Among the selected industries in East Asia, the highest percentage of ICS computers on which viruses were blocked was in construction (5.93%).
In Australia and New Zealand, the increase in the percentage of ICS computers on which viruses were blocked was primarily due to a 4.3-fold increase in the figure for the electric power industry: from 0.29% to 1.24%. For a region where the percentage of attacked ICS computers for all threats is 0.12%, this is a very high value.
Malware for AutoCAD
In Q2 2026, the percentage of ICS computers on which malware for AutoCAD was blocked increased to 0.31%.
The most notable increase over the quarter was observed in Africa. After more than doubling in the previous quarter, the figure for the region continued to rise (although not so dramatically), reaching 1.02%.
Among the selected industries across all regions, the highest percentage of ICS computers on which malware for AutoCAD was blocked was in construction in East Asia (6.38%) and in Southeast Asia (4.05%).
Main threat sources
In Q2 2026, of all the threat sources, the percentage increased only for email.
Percentage of ICS computers on which malicious objects from various sources were blocked
Internet
The percentage of ICS computers on which threats from the internet were blocked decreased to 7.61%, reaching its lowest level since 2021.
Over the quarter, the percentage increased in three regions: East Asia by 0.8 pp (to 6.3%), South Asia by 0.3 pp (to 10.4%), and Russia by 0.3 pp (to 6.4%).
Among the selected industries across all regions, the highest percentage of ICS computers on which threats from the internet were blocked was in biometrics (13.03%) and engineering and ICS integration (12.16%) in South Asia.
Email
The percentage of ICS computers on which email threats were blocked increased to 2.84%.
In Q2 2026, the percentage of ICS computers on which email threats were blocked increased in South America by 1.0 pp (to 5.2%) and in Africa by 0.7 pp (to 4.3%).
Among the selected industries across all regions, the highest percentage of ICS computers on which email threats were blocked was in biometrics (19.14%) and building automation (12.49%) in Southern Europe.
Removable media
The percentage of ICS computers on which threats from removable media were blocked continued to decrease, reaching 0.24%, the lowest value for the period under review.
Among the selected industries across all regions, the highest percentage of ICS computers on which threats from removable media were blocked was in the electric power industry in East Asia (1.34%) and biometrics in Africa (1.29%).
Network folders
The percentage of ICS computers on which threats from network folders were blocked continued to decrease. In Q2 2026, it was the lowest for the period under review, at 0.023%.
The only region to see an increase in the percentage of ICS computers on which threats from network folders were blocked during the quarter was Africa. This was mainly due to an increase in the building automation figure to 0.05%.
Among the selected industries across all regions, the highest percentage of ICS computers on which threats from network folders were blocked was in biometrics (0.23%), building automation (0.17%), and engineering and ICS integration (0.13%) in East Asia.
The more experienced a hacker becomes, the harder they are to detect. Beginners are often noisy and leave plenty of traces behind. As they gain experience, they learn to think like defenders and understand how detection actually works.
Today, we’re going to look at a tool that can hide your processes. It’s Zapper. We’ve already seen reports of it being used by hackers to masquerade their long running processes and make them look legitimate.
What is Zapper?
Zapper is a tool created by Hacker’s Choice. Unlike a lot of crude hiding methods, it actually works well. Zapper doesn’t need root privileges to run and it can work even as a static binary, one you can rename too.
Not only can you hide the command line itself, but the environment variables of a process too, along with what’s in /proc/<PID>/environ. The tool doesn’t depend on LD_PRELOAD or libc tricks, it uses ptrace() to manipulate the ELF Auxiliary Vector instead. The performance overhead is tiny, so you won’t even notice it.
Using Zapper
First you need to get the binary. Let’s use the command from the project repository:
Defenders often monitor traffic and certain keywords may trigger alerts. So it’s best to rename the tool and then host it on your C2.
bash$ > mv zapper systemd-control
Here we renamed the binary to systemd-control. On many Linux distros, the actual systemd components live inside /lib/systemd, so placing the renamed file there and changing the timestamps can make it hard to catch, unless someone’s monitoring that directory too. That’s basically why you as a defender can’t rely purely on filename based detection.
The help menu has plenty of examples and shows some creative ways you can use the tool:
bash$ > ./systemd-control -h
Hackers can hide binaries along with their child processes. They can create hidden tmux sessions to maintain persistence on a server without showing up in normal process listings. They can also leave the program name exposed but strip all the command line options, making the process look generic.
For the demonstration we’ll hide an nmap scan and all its arguments:
bash$ > exec ./systemd-control -f -a '[kworker/2:2-events_power_efficient]' nmap IP -Pn -sV -sC > /dev/shm/scan.txt &
This command makes it look like a kernel worker thread. Most admins would just ignore it. While it’s running, you won’t find it anywhere with ps or any other tool. The scan results were saved in /dev/shm/scan.txt, that proves it worked.
bash$ > ps aux | grep nmap
# no nmap in ps
bash$ > cat scan.txt
You should try it on a pentest to emulate a realistic threat and see whether defenders can catch it.
Summary
Zapper can help when you need to hide a suspicious long running process. It masquerades them as something legitimate that every admin would just skip past. The commands and arguments can’t be found in /proc either. You don’t need root to work with it, so it’s suitable for a lot of engagements. With all these qualities, it gained popularity fast and has already been seen in DFIR reports on cyberattacks.
If you like Linux and want to advance your skills, consider joining our Advanced Linux for Hackers training.
Attackers are distributing a new Android malware called “WindRelay” via phone-based social engineering attacks, according to researchers at Group-IB. The attackers call the victims, impersonating bank employees and instruct them to install a malicious app. In one instance observed by Group-IB, the scammers carried out the entire attack in just thirteen minutes.
While monitoring Android threats in June 2026, we discovered a new piece of Android malware. What struck us as unusual was that it installed like an ordinary user app yet made no attempt to disguise itself as legitimate software: it had no user interface at all. This led us to suspect the app might be reaching users’ devices without their knowledge. Further investigation confirmed that hypothesis and allowed us to reconstruct the entire infection chain.
Key findings:
We identified new Android malware: a multi-stage downloader whose ultimate purpose is ad fraud and creation of a proxy botnet.
The malware spread through the built-in updaters of Android-based automotive head unit firmware. This is the first documented case of malware found on a car head unit with an infection chain specific to that type of device.
We attribute this activity, with high confidence, to the MoYu Group, an actor linked to the BADBOX botnet.
Kaspersky solutions detect the threats described below under the following detection names:
HEUR:Trojan-Dropper.AndroidOS.Agent.vu
HEUR:Trojan-Downloader.AndroidOS.Agent.ov
HEUR:Trojan-Proxy.AndroidOS.Zhima.*
HEUR:Trojan.AndroidOS.Vo1d.*
Head unit firmware overview
A head unit is a system that combines multimedia functions with partial control over certain vehicle functions. Head units may come as part of a car’s factory equipment or as an aftermarket upgrade. The main attack vectors for these systems are compromise via physical access and vulnerabilities in the head unit’s OS or components, both of which we’ve covered previously.
In some cases, head units run on Android, primarily because it’s convenient for manufacturers: Android’s source code already accounts for use cases within automotive head units. Android also allows manufacturers to add their own system applications during the build process, which they can use for a range of purposes: customizing the UI, adding system components tailored to the vendor’s needs, and more.
Most apps developed for Android devices can also run on an Android-based head unit, and that is true for malware as well. That said, it’s hard to imagine certain categories of smartphone-targeted malware being used to attack a head unit. Banking Trojans are a good example: since mobile banking is used almost exclusively on smartphones, infecting a head unit with a banking Trojan would be a waste of the attacker’s resources.
It’s worth noting that head units often include SIM card slots and can connect to the internet, enabling features like navigation and software updates. Since a head unit typically holds nothing of value to an attacker, one of the more likely attack scenarios using “classic” Android malware is infecting the device to recruit it into a botnet – similar to attacks on IoT devices.
During our research, we found exactly that kind of malware. The design of firmware for DoFun head units enabled attackers to distribute malware. We notified the vendor about the distribution scheme, and they subsequently reported fixing the security issues.
Below is the entire infection chain:
Head unit infection scheme
Let’s look at exactly how these head units became infected.
The TWCore app
TWCore is a legitimate system application responsible for collecting analytics data and updating the head unit software. Let’s take a closer look at how the update function works.
The process is fairly simple. An MQTT message broker hosted on the subdomain cardoor[.]cn sends a message containing information about the APK files that need to be downloaded and installed on the head unit. Notably, the object describing this message includes an installNotExists field, a Boolean flag that can be set to true or false. This flag allows TWCore to install apps that weren’t originally present on the device.
TWCore only checks whether an app is already installed on the device when installNotExists = false
The APK file is downloaded to <TWCore external cache dir>/push/apk/ for installation.
The path TWCore uses to download APK files
Our telemetry revealed previously unknown malware at these file paths. On top of that, our data indicates that in every observed case, the malware was installed by an app with the package name com.tw.core, which matches the TWCore package name.
Next, we’ll break down the malware installed by TWCore: the JarService dropper.
Stage 1: the JarService dropper
As mentioned earlier, JarService is a small dropper app with no UI of any kind. It decrypts data stored as encrypted blocks within the Trojan’s code. Each block is XOR-encrypted with a single-byte key that shifts linearly from block to block. The decrypted data contains serialized information about the payload version and entry point, along with the malware’s own code for further loading.
Decrypting and deserializing information about the stage 2 payload
In the version of JarService we analyzed, the entry point for the next-stage payload was the wa method of the com.c.j.qbh class.
Stage 2: the loader
This stage’s payload is a malicious loader. Its code contains encrypted strings that are later used as class names to execute the stage 3 payload using the reflection mechanism. The loader sends implant information to one of the attackers’ servers via a POST request. Example of a request to the C2 server:
The Trojan uses the link in the dexUrl field of the data object to download serialized data for loading the next stage. This data begins with a single-byte integer, a key used to decrypt the strings in the loader’s code. Immediately following this number is a four-byte floating-point value used to XOR-decrypt the stage 3 payload, which itself is located after these keys.
Decrypting the stage 3 payload
In the decrypted payload, the entry point is the init method of the com.ast.sdk.BillingMain class, shown in the screenshot below.
Entry point of the stage 3 payload
While analyzing this stage, we noticed that the download link for the next-stage payload includes a version number. We decided to try other version numbers to retrieve different payload versions, and ultimately obtained seven distinct variants, which we list under “Indicators of Compromise” at the end of this report. The earliest version, numbered 3.57, uses a different decoding algorithm than the one described above. This may indicate that an earlier version of the infection chain used a different loader between JarService and the stage 3 payload.
Stage 3: clicker / reverse proxy loader
In this stage, the malware sends a POST request to /cpc/api/task every 90 minutes by default, containing information about the infected device (display resolution, device model, the SSID of the connected Wi-Fi network, MAC address, and so on) along with the Trojan’s configuration version. If the configuration is outdated, the C2 server returns an updated configuration containing new C2 addresses and new paths for sending HTTP requests. An example of a response is shown below. Note that at the time of our research, the most up-to-date configuration version was 3.82.
If the configuration version doesn’t need updating, the C2 server instead returns integer command identifiers, which the attackers refer to as productId. The Trojan maps each identifier to command information, which it stores as a serialized JSON object using the SharedPreferences API. Each identifier also has its own version, expressed as a UNIX timestamp. If the C2 response includes an unknown productId or one whose version is outdated, the malware sends a GET request to the attackers’ server at /cpc/api/xml to retrieve the command contents for all such identifiers. The C2 server responds with command information for each unknown identifier. An example of a response is shown below.
The command information includes a tagName field, which is the command name. The code maps each name to the corresponding class responsible for executing it.
List of executable commands
At the time of our research, the attackers had implemented nine commands. The table below lists command names, brief descriptions, and arguments. The functionality of these commands suggests that the malware can be used to display ads, commit ad fraud (serving as a clicker), and download additional malicious code.
Command name
Description
Arguments
return
Return a value from SharedPreferences.
key: the key whose value should be returned
copy
Set the contents of the clipboard.
text: the key whose value from SharedPreferences is returned as the clipboard contents url: a link for downloading gzip-compressed data (optional); this data is then concatenated with the value of the text key, with (5 spaces) used as a separator
http
Make a POST/GET HTTP request to a specified resource and, if instructed, save the response in SharedPreferences under a specified key.
url: the resource address method: the HTTP method name (optional) startLabel: a marker for the start of the data to save from the resource (optional) endLabel: a marker for the end of the data to save from the resource (optional) valueLabel: the key under which to save the value (optional) header: a dictionary of headers for the HTTP request (optional) content: the content of the POST request (optional)
web
Open a link in the WebView and execute arbitrary JavaScript code within it.
url: the link to open in the WebView js: base64-encoded JavaScript code to execute in the WebView; used when the url parameter is empty or absent corejs: JavaScript code to execute when the resource loads in the WebView (optional) param: a string dictionary of parameters for launching the WebView client: if this key is present, WebViewClient is used to handle redirects manually time: task timeout
loadlib
Not fully implemented at the time of publishing this report.
–
loadlib2
Download and execute arbitrary code.
url: the address to download the payload from name: the name of the module being downloaded md5: the MD5 hash of the payload clear: a comma-separated list of payload names to delete (optional) params: an array of parameters to launch the payload with className: the class name of the payload entry point method: the name of the virtual method at the payload entry point cmethod: the name of the static method used to instantiate the entry-point class (optional) thread: a flag; the payload runs in a separate thread if this flag is not set reload: a flag that, when set, restarts already loaded modules
loadlib3
Not fully implemented at the time of publishing this report.
–
deeplink
Open a resource in the browser.
url: a link to the resource
traceroute
Check resource availability via an ICMP ping.
host: comma-separated list of resources to check
However, attackers use only a relatively small subset of these commands in real-world attacks. As shown in the example C2 response above, at the time of publishing this report the attackers were using the loadlib2 and http commands. The payload downloaded via the loadlib2 command is a reverse proxy module named “zhima”, which researchers from the Nokia Deepfield Emergency Response Team independently discovered in TV set-top boxes around the same time as we did and also described in their report. This confirms that the attackers’ ultimate goal is building a proxy botnet.
While investigating this stage of the attack chain, we noticed that the zhima download link also included a version number. As with the previous stage, we tried other possible version numbers and found eight variants of the zhima module, the earliest of which was version 57. The complete list of identified zhima modules is provided under “Indicators of Compromise” below.
Attribution
While analyzing the complete infection chain, we noticed that the stage 2 loader created a thread with the meaningful name mosdk-host-loader. We decided to investigate what mosdk referred to in that name. This led us to a malicious app installed on various TV set-top boxes with the package name com.abc.nexus (3AD4BF5A86D26FFBF09CAE42AF330A98). It consists of several components (including a dropper similar to JarService), each used by the attackers to covertly monetize the device’s computing power. Each malicious component in the app corresponds to its own service, and the service containing the launch code for the JarService-like dropper is named AdmoyuService. In light of this and the name of the malicious thread found in the payload code, we concluded that moyu in the service name referred to MoYu Group, one of the actors linked to the BADBOX malware platform, which had been described by researchers at HUMAN. This assessment is further supported by extensive overlap between the malware’s network infrastructure and that of MoYu Group, which was independently identified by researchers from the Nokia Deepfield Emergency Response Team around the same time as our own research. Based on these similar naming patterns and prominent infrastructure overlap between the activity of MoYu Group and the attacks described in this report, we attribute it to the same actor with high confidence.
While investigating the malware downloaded by TWCore, we noticed that the domain admin.uipoxy[.]com resolved to the IP address 128.14.210[.]58, one of the C2 servers for the zhima reverse proxy module. It appears that the URL hxxp://admin.uipoxy[.]com/proxy/u/login hosts the zhima admin panel. Interestingly, this panel allows anyone to register as long as they have a valid invite code.
The malware operator registration page
During registration, users are prompted to review the terms of use and privacy policy. Both documents are hosted on links under the pxyedge[.]com domain, which belongs to PXYEDGE, a vendor specializing in the sale of residential proxies.
We found several similarities in the authentication APIs across all of these sites:
The sign-in page was hosted on an admin.* subdomain.
The sign-in page was located at /proxy/u/login.
The signup page was located at /proxy/register?channelKey=<invitation code>.
Based on this, we believe these services are connected to MoYu Group.
Conclusion
Despite efforts by cybersecurity professionals and law enforcement to shut down the BADBOX botnet, individual actors linked to it continue their malicious activity, infecting devices worldwide. Delivery methods for this kind of malware vary widely, from downloads via pre-installed backdoors to infected builds of IPTV apps. The case examined here demonstrates an even more sophisticated delivery method: distribution through the legitimate update functionality of a system application. Attackers are also actively expanding into new platforms. This malware is the first known malicious app targeting head units, which means these platforms now require protection against malware as well.
Hackers with the North Korean threat actor Famous Chollima are posing as recruiters on LinkedIn and attempting to trick users into falling for ClickFix attacks, according to researchers at SOCRadar.
CoolClient is a backdoor family attributed to the HoneyMyte APT group (also known as Mustang Panda) that has been used in their cyber-espionage campaigns targeting organizations across Asia and Russia. It supports such capabilities as keylogging, clipboard theft, credential harvesting, file management, system reconnaissance, and plugin-based extensions.
Since its first public disclosure by Sophos in 2022 and subsequent analysis by Trend Micro in 2023, CoolClient has continued to evolve. In 2025, we analyzed a newer variant that introduced clipboard theft and HTTP traffic interception for credential harvesting.
In late 2025 and 2026, our latest investigation reveal another major evolution. The newest CoolClient variant can deploy a signed kernel-mode driver as a Windows service and communicate with it through IOCTL requests. The driver enhances the malware’s stealth by hiding the CoolClient process, protecting related files and registry entries, and preventing them from being inspected or modified. The overall design is comparable to the kernel-mode enhancements previously observed in ToneShell, but the CoolClient driver exposes dedicated IOCTL handlers that allow the user-mode backdoor to communicate directly with the driver.
We have observed this updated CoolClient variant and its accompanying driver in intrusions across multiple countries in Asia, including Pakistan, Mongolia, and Myanmar.
Technical analysis
In the observed campaign targeting Myanmar, HoneyMyte used PlugX as the initial post-compromise implant to deploy the CoolClient components. Before deploying the malware, the actor added both a folder exclusion and a file exclusion to Microsoft Defender for the fake Windows Defender installation directory and the renamed sideloader executable (defender.exe).
The actor then created a fake Windows Defender installation directory, copied the CoolClient components into it, and renamed a legitimate Sangfor executable, usually named Sang.exe, to defender.exe to serve as the DLL sideloader.
When executed, defender.exe sideloads the malicious libngs.dll, initiating the CoolClient execution chain described in the following sections.
CoolClient components
Similar to previous variants, the latest CoolClient user-mode component follows a multi-stage execution chain, with each component performing a distinct role during execution.
Component
Description
defender.exe / Sang.exe
Legitimate Sangfor application abused for DLL sideloading
libsrapc.dll
Benign dependency required for the Sangfor application to execute normally
libngs.dll
First-stage loader that decrypts and loads the next stage into memory (First stage)
loadcert.ini
Encrypted DLL implementing the core CoolClient functionality, including command handling, process injection, driver deployment, and persistence (Second stage)
cert.ini
Final-stage implant responsible for C2 communication and backdoor functionality (Final stage)
time.ini
CoolCleint configuration file
Our previous CoolClient analysis focused primarily on the final-stage implant (main.dat), including its backdoor commands and plugin framework, while the first-stage loader (libngs.dll) and second-stage component (loader.dat) received only a brief overview. In the latest variant CoolClient, loader.dat and main.dat have been renamed to loadcert.ini and cert.ini, respectively. This article revisits those earlier stages, focusing on the second-stage component and the newly introduced kernel-mode driver that extends CoolClient with rootkit capabilities.
Overview of the new variant of CoolClient
First stage: libngs.dll
Execution begins when the legitimate Sangfor application (defender.exe or Sang.exe) loads the malicious libngs.dll through DLL sideloading. As in previous CoolClient variants, the malware continues to abuse the same Sangfor application to execute its first-stage loader.
To make the DLL appear legitimate, libngs.dll exports numerous dummy functions. Each export simply calls OutputDebugStringA with its corresponding function name before immediately invoking ExitProcess, serving no functional purpose other than mimicking the expected export table of the legitimate DLL.
Dummy export functions in libngs.dll invoking OutputDebugStringA and ExitProcess
The actual malicious logic is executed from DllMain (DllEntryPoint). Although heavily obfuscated through control flow flattening and numerous unconditional jumps, the routine ultimately performs a straightforward task: loading, decrypting, and executing the encrypted second-stage DLL, loadcert.ini.
The loader resolves the required Windows APIs, reads loadcert.ini into memory, and decrypts it using a 0x32-byte repeating XOR keystream derived from a transformed seed value of 0xA4. After decryption, the DLL is loaded directly into memory, and execution is transferred to loadcert.ini.
Second stage: loadcert.ini (before synchost.exe injection)
The second-stage DLL, loadcert.ini, is responsible for preparing the execution environment before the malware transitions into its injected process. It first determines its execution context by checking whether the current module is synchost.exe.
If the DLL is running under the original sideloaded process (for example, Sang.exe), it performs the initial setup, including persistence, UAC bypass, registry modifications, and process injection.
If the DLL is already executing inside synchost.exe, it follows a different execution path that decrypts time.ini, deploys the kernel-mode driver, and loads the final-stage implant (cert.ini).
Command handler
The command handler remains largely unchanged from previous CoolClient variants, with one notable difference: the malware now injects into synchost.exe instead of write.exe.
Execution is controlled through three command-line parameters:
Parameter
Purpose
install
Performs the initial setup, including persistence, privilege checks, and preparation for the injected execution path.
work
Executes the primary second-stage functionality from the injected synchost.exe process, including driver deployment and third-stage loading.
passuac
Continues execution after privilege elevation.
If no parameter is supplied, the malware creates a new Sang.exe process with the install parameter using CreateProcessW.
Establishing AutoRun persistence
When executed with the install parameter, CoolClient creates an AutoRun entry under:
The registry value, named goopdate, launches Sang.exe (or defender.exe, depending on the deployment) with the work parameter whenever the user logs on.
Process injection into synchost.exe
Upon establishing the AutoRun registry entry, CoolClient decrypts loadcert.ini using a 0x32-byte repeating XOR keystream derived from the hardcoded base key 0x4D.
The decrypted DLL is then injected into a newly created suspended instance of synchost.exe. The malware allocates memory in the target process, writes the decrypted payload, redirects the thread context to the injected code, resumes execution, and finally terminates the original process with ExitProcess.
From this point onward, execution continues entirely within synchost.exe, where the malware proceeds with kernel-mode driver deployment before loading the final-stage implant (cert.ini).
Service installation
When executed with the install parameter, CoolClient establishes an additional persistence mechanism by installing itself as a Windows service. Before doing so, it verifies that it has sufficient access to the Service Control Manager and that no 360 Total Security software processes (360sd.exe, zhudongfangyu.exe, or 360desktopservice64.exe) are running.
Function to check for running 360 Total Security software processes
If both checks succeed, the malware decrypts time.ini to retrieve the service configuration, including the service name and description. It then checks whether the service media_updaten already exists. If found, the existing service is stopped and deleted before a new one is created.
The new service is configured to execute Sang.exe<.code> with the work parameter using CreateServiceA. The malware then starts the service by executing "sc start media_updaten" via WinExec.
Administrator privilege check
If the service installation path is not taken, CoolClient checks whether the current process is running with administrator privileges by verifying membership in the local Administrators group.
When administrative privileges are available, the malware relaunches itself with the passuac parameter before continuing with the remaining execution flow.
Elevated relaunch and UAC bypass
To continue execution with elevated privileges while concealing its true parent process, CoolClient implements an RPC-based process creation technique similar to the method described by Google Project Zero. The technique combines RPC process creation with parent process ID (PPID) spoofing to launch a new elevated instance of itself.
The malware first checks for the presence of escanmon.exe. If the process is running, it constructs the path to C:\Windows\System32\winver.exe and establishes a connection to the local ncalrpc endpoint (201ef99a-7fa0-444c-9399-19ba84f12a1a). It then invokes NdrAsyncClientCall to launch winver.exe through the RPC interface.
Authenticated RPC binding used during the RPC-based UAC bypass
After winver.exe is created, CoolClient retrieves its debug object using NtQueryInformationProcess, detaches the debugger through NtRemoveProcessDebug, and terminates the process. The obtained debug object is later reused during the remainder of the UAC bypass routine.
Next, the malware repeats the same RPC-based process creation technique to launch computerdefaults.exe. It associates the previously obtained debug object with the current thread using DbgUiSetThreadDebugObject, waits for the resulting process creation event through WaitForDebugEvent, and duplicates the process handle using NtDuplicateObject, obtaining a handle with full access rights.
Finally, CoolClient relaunches itself as Sang.exe passuac using CreateProcessW with an extended startup attribute list. By configuring PROC_THREAD_ATTRIBUTE_PARENT_PROCESS through UpdateProcThreadAttribute, the duplicated process handle is assigned as the parent of the new process. As a result, the new Sang.exe passuac instance executes with an elevated context while appearing to have been spawned by the trusted Windows process instead of the original CoolClient process.
Second stage: loadcert.ini (Injected Execution)
After being injected into synchost.exe, loadcert.ini follows its injected execution path, where it deploys the kernel-mode driver and launches the final-stage implant (cert.ini). If administrative privileges are unavailable, the malware skips driver deployment and proceeds directly to the third-stage injection.
Kernel-Mode driver deployment
The deployment routine begins by decrypting time.ini. CoolClient then verifies that it has sufficient privileges to install a kernel-mode driver by checking for full access to the Service Control Manager (SCM) and the presence of SeTcbPrivilege.
If both conditions are met, CoolClient extracts an embedded LZMA-compressed driver from loadcert.ini, decompresses it, and writes it to disk as msagent.sys in the same directory as cert.ini, for example:
Next, the malware checks whether a service named msagent already exists. If present, the existing service is stopped and deleted before a new driver service is created and started, loading the kernel-mode component into the operating system.
Driver initialization
After the driver is loaded, CoolClient establishes communication with it by opening the device \\.\msagent using CreateFileW. The user-mode component then initializes the driver by issuing three DeviceIoControl requests.
IOCTL
Purpose
0x222120
Registers the current CoolClient process with the driver.
0x2221E0
Sends the configured C2 IPv4 address to the driver.
0x2220F0
Registers filesystem and registry paths that should be protected or hidden.
The first request (0x222120) registers the current CoolClient process as a trusted process within the driver. The request includes the process ID, an operation code, and a flag that marks the process as trusted, allowing it to interact with protected files, registry keys, and processes.
The second request (0x2221E0) passes the configured C2 IPv4 address extracted from time.ini.
Finally, 0x2220F0 registers the CoolClient installation directory (for example, C:\Program Files\Microsoft\Windows Defender\) together with the service registry path (\Registry\Machine\SYSTEM\CurrentControlSet\Services\media_updaten). These entries allow the driver to protect the malware’s files and registry objects from inspection, modification, and deletion.
As part of the initialization, CoolClient updates the HKLM\SYSTEM\RNG\Wid_H1deF5Dirs registry value by appending its installation directory if it is not already present. This registry value is later used by the driver when applying its hiding and protection mechanisms.
The implementation of these IOCTL handlers and the corresponding driver functionality are discussed in the msagent.sys section.
Cert.ini process injection
Once the driver has been initialized, CoolClient proceeds to launch the final-stage implant (cert.ini). Before creating the target process, the malware enumerates active WinStation sessions to identify a suitable interactive user session.
After selecting a session, CoolClient duplicates its access token, updates the session identifier, and creates a new synchost.exe process using CreateProcessAsUserA. The decrypted cert.ini DLL is then injected into the suspended process using the same memory allocation, thread context modification, and ResumeThread technique described earlier.
This marks the final transition in the execution chain, where the third-stage implant takes over C2 communication and the remaining backdoor functionality.
Msagent.sys driver
Analysis of the deployed kernel-mode driver reveals an embedded PDB path:
The path contains several notable strings, including “Nanjing Laboratory” (南京实验室) and “Zhang Xuejie Yunnan m” (张雪杰云南m), which likely refer to the driver’s development environment. However, our OSINT analysis did not identify any information linking these strings to a known organization, developer, or threat actor.
The driver is digitally signed with a certificate issued to "Nanjing Ranyi Technology Co., Ltd.", with serial number 3E 62 DC 5D 8D 61 2A 26 33 E7 6B DF D6 07 19 DD. The certificate was valid from August 2013 to September 2014.
We identified several older malicious drivers signed with the same certificate that were compiled around 2013. However, we found no evidence directly linking those samples to the CoolClient activity described in this article.
Driver configuration
During initialization, the driver loads its stealth configuration from the registry key \REGISTRY\MACHINE\SYSTEM\RNG. The configuration defines which system objects should be hidden or protected and controls the driver’s operating mode.
Registry configuration loaded by the driver during initialization
Two REG_DWORD values control the driver’s operating mode:
Registry Value
Default
Description
Hid_State
1
Enables the driver’s rootkit functionality.
Hid_StealthMode
0
Controls additional stealth features used by selected driver routines.
In addition, the driver loads several REG_MULTI_SZ values that define the objects to be hidden or protected.
Registry Value
Purpose
Wid_H1deF5Dirs
Directories to hide
Wid_H1deF5Files
Files to hide
Wid_H1deRegKeys
Registry keys to hide
Wid_H1deRegValues
Registry values to hide
Hid_IgnoredImages
Processes to ignore
Hid_ProtectedImages
Processes to protect
Together, these registry values determine which filesystem paths, registry objects, and processes are managed by the driver’s protection mechanisms.
After loading the configuration, the driver converts the registry entries into internal lookup structures that are shared across its various protection components.
These structures are later referenced by the filesystem minifilter, registry callback, process callback, object callback, image load callback, and IOCTL handlers to determine whether a file, registry object, or process should be hidden, protected, or ignored.
Preparation for process hiding
Next, the driver dynamically locates the ActiveProcessLinks (LIST_ENTRY) field within the EPROCESS structure instead of relying on hardcoded offsets. It first validates several predefined offsets and, if none match, performs a linear scan of the EPROCESS structure to identify the correct location. This approach allows the driver to remain compatible across different Windows versions, where the layout of EPROCESS may differ.
The driver validates candidate ActiveProcessLinks layouts before enabling process hiding
Once the correct offset has been identified, it is stored for later use by the process hiding routines. During process hiding and restoration, the driver uses IOCTLs 0x22219C and 0x2221A0 to unlink and relink entries in the Windows active process list, effectively hiding or restoring processes on demand.
Process, object, and image load callbacks
After preparing its process tracking structures, the driver initializes several AVL trees and populates them with configuration entries loaded from the registry, including Wid_H1deF5Dirs, Wid_H1deF5Files, Wid_H1deRegKeys, Wid_H1deRegValues, Hid_IgnoredImages, Hid_ProtectedImages, and Hid_HideImages.
These AVL trees provide efficient lookups for protected files, registry objects, and tracked processes, and are shared by the callback routines and IOCTL handlers.
The driver then registers three types of kernel callbacks that form the foundation of its protection and monitoring mechanisms:
Object callbacks using ObRegisterCallbacks
Process creation and termination callbacks using PsSetCreateProcessNotifyRoutineEx
Image load callbacks using PsSetLoadImageNotifyRoutine
Registration of object, process, and image load callbacks during driver initialization
After registration, these callbacks maintain the driver’s internal tracking structures as processes, threads, and images are created or loaded.
Object callbacks
To protect selected processes, the driver registers object callbacks for process (PsProcessType) and thread (PsThreadType) objects using ObRegisterCallbacks with an altitude of 1203. These callbacks intercept requests to open process and thread handles. If the target process is protected, the driver reduces the access rights granted to the requesting process, preventing operations such as process termination, code injection, and other forms of process manipulation. In this sample, the protected process is the injected CoolClient code running inside synchost.exe.
Process and image load callbacks
The driver registers process creation and termination callbacks using PsSetCreateProcessNotifyRoutineEx, together with an image load callback via PsSetLoadImageNotifyRoutine.
When a process is created, its image name is compared against the configuration lists Hid_IgnoredImages, Hid_ProtectedImages, and Hid_HideImages. Matching processes are added to the driver’s internal tracking structures, allowing them to be protected, hidden, or managed through subsequent IOCTL requests. When a tracked process terminates, its entry is removed from the tracking structures.
The image load callback monitors modules loaded into tracked processes and updates the driver’s internal state to support subsequent protection and hiding operations.
To ensure that processes already running before the driver is initialized are also tracked, the driver performs a one-time enumeration of all active processes after registering the callbacks and adds any matching processes to the tracking structures.
MiniFilter registration
To protect files and directories, the driver registers a filesystem minifilter. During initialization, it creates internal path filter lists, loads the configured directory and file entries (Wid_H1deF5Dirs and Wid_H1deF5Files), and creates the required minifilter registry entries under HKLM\SYSTEM\CurrentControlSet\Services\msagent\Instances. To avoid altitude conflicts, the driver dynamically assigns a filter altitude and retries registration until a unique value is obtained.
Retrying minifilter registration with incrementing filter altitude values until FltRegisterFilter succeeds
The driver then activates the minifilter using FltRegisterFilter. The filter works together with the IOCTL interface, which dynamically adds, removes, or clears protected path entries (0x2220F0, 0x2220F4, and 0x2220F8). During filesystem operations, the minifilter compares accessed paths against its internal path lists and denies access to matching entries, effectively hiding protected files and directories from users and applications.
Registry callback registration
To protect registry keys and values, the driver registers a registry callback using CmRegisterCallbackEx with an altitude of 320000. During initialization, it creates separate lookup structures for protected registry keys and values, then populates them using the configured entries from Wid_H1deRegKeys and Wid_H1deRegValues.
Registration of the registry callback using CmRegisterCallbackEx with an altitude of 320000
Once registered, the callback intercepts registry operations and compares the target key or value against the protected entries. For enumeration requests, matching keys and values are removed from the results before they are returned to user mode, effectively hiding them from registry viewers. For direct access requests, such as opening, modifying, or deleting protected registry objects, the callback returns STATUS_ACCESS_DENIED, preventing the operation.
Before applying these restrictions, the driver verifies whether the requesting process is trusted. Processes registered through IOCTL 0x222120, including the CoolClient user-mode component, bypass the filtering logic and retain unrestricted access, while all other processes remain subject to the driver’s registry protection rules.
IOCTL command dispatcher
To communicate with the user-mode component, the driver creates a device object named \Device\ToolTool together with the symbolic link \DosDevices\ToolTool to allow the user-mode CoolClient component to communicate with the driver through DeviceIoControl requests.
The driver implements 33 IOCTL handlers, although the analyzed CoolClient sample uses only three during normal execution:
0x222120: registers the current CoolClient process with the driver.
0x2221E0: passes the configured C2 IPv4 address.
0x2220F0: registers filesystem and registry paths for protection.
The remaining IOCTL handlers were not invoked by the analyzed sample.
IOCTL
Handler
Functionality
0x222000
0x140001E04
Enable or disable the rootkit.
0x222004
0x1400020B0
Query the current rootkit state.
0x2220F0
0x140002320
● Register protected filesystem or registry paths
● Used by CoolClient to register its installation directory and service registry key.
0x2220F4
0x1400034DC
Remove a protected filesystem or registry path.
0x2220F8
0x140003464
Clear all protected filesystem and registry path entries.
0x222118
0x1400024B0
Register process or path protection entries.
0x22211C
0x140002A20
Query registered protection entries.
0x222120
0x140003794
Update process protection entries. Used by CoolClient to register itself as a trusted process.
0x222124
0x14000362C
Remove a protection entry.
0x222128
0x14000349C
Clear all process protection entries.
0x222130
0x14000265C
Register a protected process by PID.
0x222134
0x140010E88
Inject shellcode into a target process using NtCreateThreadEx.
0x222138
0x14000F498
Hide a kernel module by unlinking it from PsLoadedModuleList.
0x222144
0x14000270C
Delete a file.
0x222148
0x14000286C
Decrypt an embedded buffer and write it to disk.
0x22214C
0x1400027F4
Read and decrypt an encrypted file.
0x222168
0x140002780
Unmap the image section of a target process.
0x22216C
0x140013984
Terminate a process by PID.
0x222194
0x140011F50
Remove Protected Process Light (PPL) protection.
0x222198
0x140002940
Create or modify a registry value.
0x22219C
0x140010630
Hide a process by unlinking it from the active process list.
0x2221A0
0x140010670
Restore a previously hidden process.
0x2221A4
0x14000F8A0
Hide a module within a process.
0x2221A8
0x14000F954
Restore a hidden module.
0x2221AC
0x140016368
Enumerate and restore kernel notification callbacks.
0x2221B0
0x140016458
Disable or restore kernel notification callbacks.
0x2221B4
0x140012408
Manually load a secondary kernel driver.
0x2221B8
0x14001262C
Debug/test handler.
0x2221BC
0x1400165F6
Write to an arbitrary kernel address.
0x2221C0
0x14000BB00, 0x14000BB78
Enables deny-rootkit mode by registering image-load monitoring and enabling the patching logic.
0x2221C4
0x14000BB6C, 0x14000BB10
Disables deny-rootkit mode by clearing state and unregistering/removing the monitoring logic.
0x2221E0
0x1400126C0
Register a C2 IPv4 address.
0x2221E4
0x140012E50
Delete a C2 IPv4 address.
After initializing the IOCTL dispatcher, the driver releases the temporary configuration buffer that was previously loaded from \REGISTRY\MACHINE\SYSTEM\RNG.
Kernel module enumeration and hiding
To support kernel module hiding, the driver resolves the address of the non-exported kernel variable PsLoadedModuleList at runtime using MmGetSystemRoutineAddress. This global linked list maintains information about all loaded kernel modules and drivers, allowing the rootkit to enumerate and manipulate module entries.
Driver initialization routine resolving the address of PsLoadedModuleList for subsequent kernel module hiding
This functionality is exposed through IOCTL 0x222138, which accepts a module name or path from the user-mode component. When a matching module is found, the driver locates the corresponding entry in PsLoadedModuleList and unlinks it by updating its Flink and Blink pointers. As a result, the hidden module no longer appears in standard kernel module enumeration routines.
Nsiproxy hooking and data filtering
The driver also hooks the Nsiproxy driver to filter network-related data returned to user mode. This functionality is connected to IOCTL 0x2221E0, which allows the user-mode component to register C2 IPv4 addresses with the driver.
To install the hook, the driver obtains a reference to \Driver\Nsiproxy using ObReferenceObjectByName and replaces one of the Nsiproxy handler pointers with its own filtering routine. The hook preserves the original handler and forwards execution after processing the returned data.
Installing the Nsiproxy hook by resolving \Driver\Nsiproxy and replacing the original handler with the driver’s filtering routine
When the hooked routine processes network information, the driver compares the returned entries against its registered C2 address list. Matching IP addresses are removed before the data is returned to user mode, preventing applications that rely on Nsiproxy-provided network information from seeing the malware’s C2 addresses.
Finally, the driver registers a DriverUnload routine to release allocated resources when the driver is unloaded.
Victimology
The latest CoolClient variant continues to target organizations consistent with previously observed HoneyMyte activity. Based on our investigations, we identified victims in Myanmar, Mongolia, Pakistan, and Russia, including confirmed government entities.
Across the observed intrusions, CoolClient was consistently deployed as a secondary backdoor following a PlugX infection, indicating that HoneyMyte continues to use PlugX as its initial post-compromise implant before transitioning to CoolClient.
Attribution
Our analysis confirms that the investigated malware is a new CoolClient variant associated with the HoneyMyte threat group. While the overall execution flow remains consistent with previously documented CoolClient variants, this sample introduces a previously undocumented kernel-mode driver that significantly expands the malware’s stealth capabilities.
The deployment chain observed in this investigation is also consistent with previous HoneyMyte campaigns, in which PlugX serves as the initial foothold before CoolClient is deployed as a secondary backdoor, further reinforcing the attribution.
Conclusion
The latest CoolClient variant represents a significant evolution of the malware. Rather than operating solely as a user-mode backdoor with plugin support, it now deploys and communicates with a kernel-mode driver that extends its capabilities beyond earlier versions. Through this driver, CoolClient can hide and protect processes, files, and registry objects, as well as filter selected network information, making detection and analysis considerably more difficult.
HoneyMyte has previously introduced kernel-mode functionality in ToneShell. The addition of a kernel-mode driver to CoolClient suggests that the group continues to expand its use of rootkit capabilities to improve stealth, persistence, and defense evasion during post-compromise operations.
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