Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects the dropping of a 24-character hexadecimal JavaScript payload followed by the creation of a '.pkg_history' or '.pkg_logs' marker file within a one-minute timeframe. This behavior is indicative of the Mastra NPM supply chain compromise.
C2 Connection Detection
YARA-L
Detects network connections to known C2 infrastructure using specific ports
Detects Python deleting runtime scripts, compiled modules, screenshots, and credential archives from temporary or profile paths. This rule specifically looks for file deletion or creation events where the target file matches common Python script/module extensions (.py, .pyc, .pyd, .so) or archive/image extensions (.zip, .7z, .png, .jpg) within temporary or user profile directories, and the process responsible is identified as Python.
Detects IP geolocation lookups used to gather target network information
Detects the creation of files with a '.vile' extension within the Google Chrome extensions directory. This directory path is often used by attackers to install unauthorized or malicious browser extensions to maintain persistence, steal credentials, or pivot within the browser session.
Detects the execution of 'moladb_hash_crack.py', a script known to be used by the MuddyWater APT group for credential operations, specifically hash cracking. This rule identifies process command lines containing the script's filename.
Identifies execution of 'c2_fixed.py' or 'c2_fixed_v2.py' used in MuddyWater C2 operations. These scripts are associated with the MuddyWater threat group for command and control activities.
Detects the execution of Python or Node.js processes that include command-line arguments indicative of base64 decoding or zlib decompression, often used for deobfuscating and executing malicious payloads in memory.
This rule detects suspicious process execution patterns associated with malicious activities in GitHub Actions environments, specifically flagging the use of JavaScript runtimes (node, bun) to execute malicious payloads, git operations related to pull request data exfiltration (pwn-request), and the creation of orphan branches characteristic of the Miasma campaign.
Detects the execution of Node.js build processes (node-gyp) or npm build commands involving native module compilation. These patterns are often indicative of legitimate development workflows but are also leveraged by attackers to compile malicious native add-ons or execute arbitrary code in a build environment.
Detects anomalous network communication with a known C2 domain associated with the Miasma worm, or attempts by JavaScript runtime processes (node, bun) to access sensitive developer-related files (SSH keys, cloud credentials, browser data) without an authorized IDE parent process.
This rule detects unauthorized or suspicious file access to sensitive configuration, credential, and identity files by 'node.exe' or 'bun.exe' processes. It flags instances where these runtime processes access multiple unique sensitive files, excluding those officially associated with the Node.js or OpenJS Foundations, which is a common indicator of credential exfiltration or reconnaissance by malicious scripts in an environment.
Detects anomalous process execution patterns associated with supply chain compromises (specifically Miasma/Mini Shai-Hulud 'Phantom Gyp'), where node-gyp build processes or npm lifecycle scripts trigger the execution of unexpected scripts or unauthorized runtimes like Bun.
Detects known malicious file hashes associated with Miasma/Mini Shai-Hulud malware, as well as suspicious npm-lifecycle behaviors including binding.gyp shell execution, runtime staging of the Bun engine, and suspicious Bun-related downloads from GitHub.
This rule detects potentially unauthorized or suspicious command execution originating from AI development assistant processes such as Claude, Cursor, Amazon Q, or Node-based environments. It specifically monitors for the invocation of shell commands (e.g., bash, sh -c) or package managers (npx) that interact with sensitive AI assistant configuration files (e.g., .amazonq, mcp.json), which could indicate an adversary attempting to leverage AI integration paths for unauthorized command execution or persistent configuration manipulation.
Detects instances where the 'git clone' command is executed, followed by the creation of a configuration file at '.amazonq/mcp.json'. This pattern may indicate the setup or configuration of Amazon Q developer tools on an endpoint, which could be abused for unauthorized access or information gathering if performed by an unauthorized user or process.
This rule detects network connections to known malicious IP addresses or attempts to resolve specific domains associated with malicious activity. It monitors for outbound network traffic patterns identified as potential indicators of compromise (IOCs) linked to command and control (C2) servers.
This rule detects network activity involving connections to known malicious IP addresses or DNS domains ('govtop.one') and subsequent attempts to download specific suspicious file payloads, such as archives or image files often associated with malicious activity. This activity is indicative of potential command and control communication or initial malware ingress.
Detects when development tools such as VS Code, VS Code OSS, or Node.js spawn a shell (bash/sh) to execute network-related commands (aws, curl, wget, npx). This behavior is characteristic of an adversary leveraging a developer's environment to download payloads, interact with cloud resources, or perform reconnaissance.
Identifies the use of the macOS ditto utility to compress stolen datasets into a single archive, specifically preserving resources, as observed in AMOS malware activity.
Detects the script escalating privileges using the stolen password via sudo to strip quarantine extended attributes from the payload.
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