Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
956 detections
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Detects potential Remus infostealer activity by monitoring unauthorized processes accessing AI agent credential directories (Claude, Cursor, OpenCode, Codex) or cryptocurrency wallet files, specifically when combined with .lnk shortcut file access behavior.
Detects suspicious processes accessing cryptocurrency wallet data files or web browser extension storage folders associated with popular crypto wallets. This behavior is indicative of credential theft or wallet data exfiltration by malware targeting digital assets.
This rule detects unauthorized access attempts by non-browser processes to specific browser extension storage directories. It focuses on directories associated with password managers, 2FA authenticators, and cryptocurrency wallets, as well as core browser credential files (e.g., Login Data, Cookies, logins.json). This behavior is characteristic of info-stealer malware, such as the Remus infostealer, attempting to exfiltrate sensitive data stored by browsers.
Detects a multi-stage, automated attack chain performed by AI-based development agents (e.g., Claude, Copilot, Cursor). The rule correlates process discovery, credential access, file collection (staging), and exfiltration over web services within a tight 15-minute window, identifying potential autonomous exploitation and data exfiltration. Covered T1046, T1552.001, T1078, T1005, T1567
Detects high-volume, potentially programmatic search activity in Microsoft 365 SharePoint, characterized by iterative pagination requests using the 'indexdocid' parameter. This behavior may indicate an automated effort to crawl or systematically exfiltrate document metadata or content via the SharePoint search interface, often associated with post-exploitation discovery or unauthorized data collection.
Detects high-volume, potentially programmatic search activity in Microsoft 365 SharePoint, characterized by iterative pagination requests using the 'indexdocid' parameter. This behavior may indicate an automated effort to crawl or systematically exfiltrate document metadata or content via the SharePoint search interface, often associated with post-exploitation discovery or unauthorized data collection.
Detects access to sensitive files (KeePass databases, SSH private keys, and VPN configurations) by processes other than their designated applications. This behavior indicates potential credential harvesting or configuration exfiltration by unauthorized processes.
Detects instances where AI-based coding or agent-driven tools (e.g., Cursor, Claude Code, AutoGPT) perform suspicious file archiving/packaging activities followed by network egress to unauthorized or known exfiltration-prone services. This helps identify potential data exfiltration by AI agents or compromised development environments.
Detects instances where AI-based coding or agent-driven tools (e.g., Cursor, Claude Code, AutoGPT) perform suspicious file archiving/packaging activities followed by network egress to unauthorized or known exfiltration-prone services. This helps identify potential data exfiltration by AI agents or compromised development environments.
This rule detects non-standard processes attempting to access sensitive web browser files (e.g., 'Login Data', 'Cookies', 'key4.db') that are typically only accessed by legitimate web browsers. It excludes known browser processes and trusted security or sync applications to identify potential credential theft attempts.
This rule detects non-standard processes attempting to access sensitive web browser files (e.g., 'Login Data', 'Cookies', 'key4.db') that are typically only accessed by legitimate web browsers. It excludes known browser processes and trusted security or sync applications to identify potential credential theft attempts.
Detects unauthorized processes attempting to access browser credential database files such as Login Data for Chromium-based browsers or logins.json and key4.db for Firefox. The rule filters out known browser processes to isolate potential credential harvesting or exfiltration activity.
Detects instances where browser processes (chrome.exe or comet.exe) access multiple files in sensitive or unexpected directories (e.g., System32, /etc/, Documents) without an associated user click event. This activity often indicates potential malicious scripts or automated data collection running within the context of a browser process.
Detects anomalous, high-frequency, and highly regular HTTP requests directed at Dahua camera infrastructure for the purpose of harvesting snapshots. The rule uses statistical analysis to identify automated collection patterns, such as a high volume of requests across multiple devices with low variance in request intervals.
Detects unauthorized access to sensitive browser files, specifically 'Login Data' (passwords) and 'Cookies', by processes other than authorized browser binaries (Chrome or Edge). This is a common indicator of credential harvesting or session hijacking attempts by malware or malicious actors.
Detects instances where AI-assisted coding tools or command-line interfaces spawn scripting runtimes (Node.js, Python) to access sensitive files such as SSH keys, cloud provider credentials, or Kubernetes configurations. This behavior may indicate an AI coding assistant being coerced or misconfigured to exfiltrate secrets from the development environment.
Detects when AI-powered coding assistant plugins or CLI tools (e.g., Claude, Copilot, Gemini) execute subprocesses that attempt to access sensitive configuration files, SSH keys, or cloud credential stores. This may indicate an AI tool being manipulated or misconfigured to exfiltrate sensitive local secrets.
This rule detects the presence of files and folders associated with the Rapuncel infostealer malware. It monitors DeviceFileEvents for specific SHA256 hashes known to be malicious, as well as specific file names related to data exfiltration and log collection (e.g., 'browser_decryption.log', 'sends.log'), and the creation of files within folders containing 'Filegraber'.
Detects instances where AI coding assistants or tools (e.g., Claude, Copilot, Gemini) invoke git.exe to clone or fetch repositories from non-standard (non-GitHub) hosts, followed by a checkout operation within a short timeframe. This behavior may indicate an attacker using automated tools to stage or exfiltrate sensitive code repositories to unauthorized infrastructure.
Detects instances where AI coding assistants or tools (e.g., Claude, Copilot, Gemini) invoke git.exe to clone or fetch repositories from non-standard (non-GitHub) hosts, followed by a checkout operation within a short timeframe. This behavior may indicate an attacker using automated tools to stage or exfiltrate sensitive code repositories to unauthorized infrastructure.
Detects instances where AI coding assistants or tools (e.g., Claude, Copilot, Gemini) invoke git.exe to clone or fetch repositories from non-standard (non-GitHub) hosts, followed by a checkout operation within a short timeframe. This behavior may indicate an attacker using automated tools to stage or exfiltrate sensitive code repositories to unauthorized infrastructure.
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