Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects the invocation of local AI/LLM CLI utilities (e.g., ollama, llama-cpp) by potentially malicious or automated parent processes. It specifically flags scenarios where non-interactive or scripting-based processes (such as WScript, PowerShell, or Python) attempt to use these AI tools, particularly when the command line includes keywords related to sensitive data discovery, such as 'password', 'token', or 'private key'. This behavior is characteristic of infostealer activity (e.g., QUIETVAULT) attempting to use AI tools for automated reconnaissance and credential extraction.
Detects macOS.Gaslight DPRK-aligned implant registering a LaunchAgent plist using the com.apple.system.services.activity label to masquerade within Apple's com.apple.* namespace for persistence. Key behavioral indicators include file writes to ~/Library/LaunchAgents with the spoofed label and use of __NSGetExecutablePath for binary path resolution.
Detects the use of legitimate command-line utilities such as rclone, AWS CLI, AzCopy, curl, and wget to upload data to cloud storage endpoints, which is a common technique used for data exfiltration.
Detects Node.js process querying Ethereum blockchain for C2 address.
Detects suspicious usage of the Bun runtime, specifically when it is spawned by common Node.js development processes (like npm or node-gyp) or downloaded from non-official sources using command-line tools or browsers. This behavior is associated with the Miasma malware campaign, which abuses the Bun runtime for malicious operations.
Detects high volumes of network connections initiated by common file sharing processes such as AirDrop, sharingd, NearShare, or QuickShare. This behavioral pattern, characterized by a large number of successful connections or numerous unique remote IP addresses, may indicate unauthorized mass data collection, reconnaissance, or potential lateral movement attempts.
This rule detects potential supply chain compromise in Node.js projects by monitoring for the execution of known malicious npm package install/preinstall/postinstall scripts. It identifies unauthorized access to sensitive developer credential files (such as .ssh, .git-credentials, and .npmrc) and suspicious network outbound connections associated with identified malicious package scopes.
Detects outbound network connections from internal hosts to domains associated with the Polymarket Trap / Miasma infostealer campaign, including dedicated servers (stitch-production.org, log-taker.store) and vercel.app serverless endpoints used for credential exfiltration.
This rule monitors for file system operations (creation, modification, deletion, or renaming) performed by a Node.js process when interacting with sensitive directories and files associated with web browser extensions and cryptocurrency wallets. This pattern is commonly observed in credential and private key theft activities where malicious scripts attempt to exfiltrate wallet data.
This rule detects when a Node.js process spawns common command-line interpreters (e.g., cmd.exe, powershell.exe, bash) with command-line arguments indicative of potentially malicious activity. This includes common software development script names, build-related tasks, or obfuscated command execution patterns. The rule excludes processes signed by trusted publishers like Microsoft or the OpenJS Foundation.
This rule detects a high volume of network connections (10 or more within an hour) from a single process to remote URLs containing 'artifact' or 'maven' on standard HTTP (port 80) or HTTPS (port 443) ports. This activity could indicate legitimate software development or build processes, but also potentially malicious activities such as supply chain compromise, data staging, or exfiltration of development-related artifacts.
This rule detects when a node.exe process, commonly used for executing npm lifecycle hooks (such as preinstall, postinstall, or various .cjs scripts), spawns suspicious child processes including shells (cmd.exe, powershell.exe, sh, bash) or scripting engines (wscript.exe, cscript.exe). This pattern is frequently observed in malicious npm packages designed to achieve code execution on a developer's machine during the package installation or build process.
This rule monitors for the Node.js process (node.exe or node) accessing common sensitive configuration files, SSH keys, cloud credentials, or environment files such as .ssh/id_rsa, .aws/credentials, .npmrc, and .docker/config.json. Such activity is often indicative of an adversary attempting to perform credential theft or environment discovery after gaining initial access via a compromised Node.js application.
This rule detects the execution of Node.js processes ('node' or 'node.exe') with command-line arguments that match known patterns often associated with software installation scripts, post-installation tasks, or peer verification activities. While these file names can be legitimate, they are also commonly leveraged by attackers for malicious script execution or persistence.
Detects unauthorized access to sensitive cryptographic files, such as SSH private keys, GPG secret keys, or Windows certificate store files, by unauthorized or anomalous processes (specifically node/npm or processes within /tmp). This is followed by potential outbound exfiltration via an external network connection or the mass access of multiple sensitive files within a short timeframe.
This rule detects command line execution containing keywords associated with offensive security tools (e.g., 'metasploit', 'exploit', 'shellcode', 'payload') in conjunction with external resource indicators such as HTTP/HTTPS or FTP URLs, suggesting the download and potential execution of malicious payloads.
Detects the execution of 'aws sts get-caller-identity' spawned by IDE-related processes such as VS Code extension hosts or Amazon Q language servers. This pattern may indicate cloud credential reconnaissance performed by a malicious MCP (Model Context Protocol) server or compromised development extension (CVE-2026-12957).
Detects command lines that reference known supply chain attack targets or commonly used package management tools like npm and pypi, which can be indicators of supply chain compromise.
This rule detects potential data exfiltration attempts by monitoring for network connections to URLs containing suspicious substrings (bit, onion, .cc, .su) over common web and DNS ports (53, 80, 443, 8080). It flags high-frequency unique connection attempts from a single device, which may indicate command-and-control (C2) traffic or data exfiltration over covert channels.
This rule detects endpoint DNS queries or network connections to the suspected phishing domain 'gasparinutrition.com' initiated by common web browsers or email clients. This provides visibility into potential user interaction with malicious sites that would otherwise be missed by email security gateways.
This rule detects activity associated with the malicious 'Search for perplexity ai' browser extension (ID: flkebkiofojicogddingbdmcmkpbplcd). It specifically identifies DNS queries and network connections to the malicious domain 'perplexity-ai.online' initiated by common web browser processes, as well as file system evidence of the extension's presence.
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