Detections

Explore public detection logic contributed by the community across SIEM and rule languages.

3,651 detections

Detects the presence of files known to be associated with malicious activity by matching their SHA256 hashes against a list of known bad indicators.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
202
macOS malware used by JINX-0164 against cryptocurrency developers
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
002
Detects suspicious modifications to .github/workflows YAML files, unauthorized git commits with backdated timestamps, usage of noreply.github.com bot author names, and git push commands initiated by node.exe. This activity is indicative of the IronWorm malware attempting to manipulate CI/CD pipelines and exfiltrate secrets.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
102
This rule detects instances where npm or node.js processes are used to execute or spawn setup-related binaries or specific GitHub precheck scripts. This behavior is often associated with software deployment, CI/CD pipelines, or potentially malicious automation within development environments.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
macOS malware used by JINX-0164 against cryptocurrency developers
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
002
macOS malware used by JINX-0164 against cryptocurrency developers
avatar
Ankit Mehta@Secvyn
avatar
Detections.ai Community
4 months ago
002
This rule monitors for suspicious activity associated with npm or Node.js processes. This includes potential credential misuse during npm publish or login, unauthorized build-time execution via node-gyp, and the use of unconventional preinstall/postinstall hooks that spawn external binaries or scripts, which are often indicative of software supply chain attacks.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects suspicious 'npm publish' or 'npm login' commands executed as child processes of 'node' or 'npm'. This pattern indicates programmatic execution from within package install hooks (such as preinstall or postinstall scripts) instead of manual developer interaction, a behavior characteristic of malicious npm supply chain attacks (e.g., IronWorm) aiming to trojanize packages using stolen tokens.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects instances where a Node.js process accesses, creates, or modifies sensitive files such as SSH private keys, AWS credentials, or application configuration files (.npmrc, .pypirc, .docker/config.json). This behavior is often indicative of credential theft or unauthorized configuration access by a compromised Node.js application.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
102
Detects anomalous behaviors associated with malicious npm package self-upgrades, where node.exe modifies its own source files within node_modules or spawns npm pack commands to replace existing dependencies with malicious versions.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects Node.js processes accessing sensitive AWS credential or configuration files. This behavior is indicative of unauthorized information gathering, often associated with infostealer malware payloads delivered via malicious npm packages.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
202
Detects reconnaissance activity originating from npm or Node.js processes, specifically targeting system information (OS, network, user context, and hardware identifiers). This activity is associated with supply chain compromise attempts where malicious npm postinstall scripts or inline Node.js execution are used to enumerate the host environment.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects persistence mechanisms associated with the MYRA RAT. This includes Linux/macOS crontab modification using specific schedules or shell profile writes initiated by node/npm processes, as well as Windows scheduled task creation or task manipulation via schtasks.exe initiated by node/npm processes.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects Tailscale installation, configuration, and mesh network enrollment activity. The rule monitors for the execution of Tailscale processes with enrollment flags, DNS lookups to Tailscale coordination servers, WireGuard UDP traffic on port 41641, and connections to the Tailscale CGNAT IP address space. This activity is often used by adversaries to establish persistent, encrypted remote access.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects Node.js or npm processes that access multiple SSH-related files within a short timeframe while also establishing external network connections, which is consistent with credential exfiltration patterns.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
This rule detects potentially malicious activity related to Node.js environments. It monitors for the execution of Node.js or NPM commands involving specific sensitive files ('sync-peer.cjs', 'peer-math.js') or suspicious packing destinations, as well as the creation of 'index.js' or 'package.json' files within a 'node_modules' directory, which can indicate software supply chain manipulation or malicious dependency installation.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
This rule detects when a Node.js or NPM process accesses multiple sensitive browser credential files (Login Data or Cookies) within a short window, while simultaneously reading shell history files (bash_history, zsh_history, or fish_history). This behavior is characteristic of an automated credential harvester or infostealer script executing within a Node.js environment.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
Detects Node.js processes accessing paths associated with cryptocurrency wallets and browser extension storage (MetaMask, Phantom, Exodus, Electrum). This behavior is characteristic of infostealer malware attempting to exfiltrate seed phrases, keys, or wallet configuration data.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
102
This rule detects network connections to specific deep link patterns associated with messaging applications like Telegram, WhatsApp, and Signal. Such deep links can be used in phishing attempts or to initiate actions on a user's device through these applications.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
002
Detects processes making HTTP/HTTPS requests to localhost on ports 40341 or 40342 for '/metadata'. This pattern can indicate local service discovery, inter-process communication, or potentially malicious activity attempting to interact with local services, possibly for credential access or privilege escalation.
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Ankit Mehta@Secvyn
Bharat Cyber Guardians
4 months ago
202
This rule monitors for high frequency network connections (more than 50 requests) initiated from internal endpoints to external (non-RFC1918) IP addresses over port 443. This pattern may indicate beaconing activity, command and control (C2) communication, or significant data exfiltration to an external host.
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Ibrahim Saud@tektrix
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Detections.ai Community
4 months ago
002
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