Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects Windows PE files that contain string indicators associated with the Diaoyu loader as reported in the Shadow Campaigns research. The rule keys on multiple distinctive strings, including references to WordPress themed artefacts, a GitHub raw content host, and Diaoyu specific markers, and requires an MZ header plus either two or more indicators or specific high confidence string pairs.
This rule detects Python processes that are executed with command-line arguments indicative of silent execution or output redirection to null devices, combined with execution from a temporary directory. This pattern was observed in the dYdX PyPI package compromise, where a RAT ran undetected using these techniques.
This rule detects the execution of processes whose SHA256 hash matches a known hash associated with the MOONRISE RAT malware. It queries DeviceProcessEvents for the last 24 hours and filters for processes with matching SHA256 hashes.
This rule identifies network connections to known command and control (C2) infrastructure and typosquatted domains associated with the ValleyRAT malware, specifically those used in the Huorong impersonation campaign. It looks for connections to a hardcoded malicious IP address or a list of malicious domains.
Detects the execution of an executable from a subdirectory under %ProgramData% that matches the 'knz_' naming convention used by the MIMICRAT loader. MIMICRAT uses this directory to stage its Lua-based loader (zbuild.exe). The rule specifically looks for unsigned executables to reduce false positives.
This rule set detects various stages of the OysterLoader malware activity, including its registration and login attempts to a command and control (C2) server, specific C2 communication patterns via HTTP URIs, and connections to known OysterLoader C2 domains and IP addresses. The rules look for specific HTTP URI paths like "/reg" and "/login" combined with distinct User-Agent strings ("WordPressAgent" and "FingerPrint"), as well as specific API paths under "/api/" and hardcoded C2 domains and IP addresses.
Detects network connections to phishing domains mimicking Windows 11 download pages used to distribute infostealer malware.
Detects the creation of files matching SHA256 hashes of known malware (SparkRAT, VShell, webshells) observed in the CVE-2026-1731 exploitation campaign. This rule specifically looks for file creation events where the SHA256 hash of the created file matches one of the predefined malware hashes.
This rule detects the MIMICRAT custom RAT by identifying specific byte patterns within files or memory. These patterns were published by Elastic Security Labs and are indicative of the malware's presence.
This rule detects suspicious activity related to a malicious Notepad++ updater, specifically looking for command strings that indicate data exfiltration to 'temp.sh' using 'curl.exe'. It identifies the presence of 'temp.sh/upload', '--user-agent', 'temp.sh/', '/list', and 'curl.exe' within the analyzed content, suggesting an attempt to upload data or list contents to a temporary sharing service.
Identifies network connections or DNS queries to known phishing domains mimicking Windows 11 update sites, which are used to distribute infostealer malware. These domains are highly specific to this campaign.
Detects the execution of executables that masquerade as common collaboration tools (e.g., Teams, Zoom, Adobe) but have characteristics of the TrustConnect RAT. TrustConnect uses large (approx. 35MB) .NET Core single-file executables where the internal/original filename is a .dll, which is a mismatch from the .exe process name.
Detects PowerShell one-liners using Invoke-RestMethod (irm) or Invoke-WebRequest (iwr) piped to Invoke-Expression (iex) to download and execute the TrustConnect or DocConnect RAT.
Detects outbound network connections to known Command and Control (C2) domains and IPs associated with the TrustConnect and DocConnect malware infrastructure.
Detects creation of the LunarApplication directory used by an infostealer to stage credential and cryptocurrency theft.
This rule detects attempts to download the 'clawd.bot' or 'openclaw.ai' installation scripts using various command-line tools. It specifically looks for the use of 'curl', 'wget', 'aria2c', 'fetch', 'powershell', 'pwsh', 'certutil', 'bitsadmin', or 'mshta' when their command lines contain either 'clawd.bot/install.sh' or 'openclaw.ai/install.sh'. This activity is indicative of potential malware deployment or initial access attempts related to the OpenClaw/Clawd threat.
This YARA rule detects the Arkanix Stealer by identifying specific strings found within its code or related artifacts. It looks for a combination of unique user agent strings, domain names associated with its command and control infrastructure, API endpoints used for session creation or data exfiltration, a secret key, and a staging identifier. The rule requires at least one domain, one endpoint, and one of the distinctive user agent, key, or staging hints to trigger, aiming to reduce false positives by combining multiple indicators.
Detects modifications to the Text Input Processor (TIP) registry key with unusually large binary data, which can be indicative of malware hiding persistent code. This specific registry key is not commonly used for storing large amounts of data, making large writes suspicious.
Detects processes masquerading as legitimate software making HTTP requests to specific API endpoints associated with the TrustConnect/DocConnect RAT C2.
Detects a specific obfuscated PowerShell command-line pattern used by the LunarApplication malware to execute scripts from the %TEMP% directory while bypassing execution policies. This rule looks for PowerShell processes with specific flags to bypass execution policy and accept piped input, combined with distinctive randomized script extensions (.yiz.ps1 or .unx.ps1) typically used by this malware.
This rule detects Python scripts that use base64 decoding and execution, specifically looking for the 'import base64' statement appearing early in the file, followed by 'exec(base64.b64decode(' and ').decode('utf-8'))'. This pattern is indicative of a common method for obfuscating and executing malicious Python payloads, often seen in malware like KongTuke.
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