Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
811 detections
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Detects HTTP beaconing and command-and-control (C2) communication patterns associated with the Exvicy malware family. This includes heartbeat polling, victim fingerprinting registration, and CAPTCHA handling over HTTP GET and POST requests to the '/api.php' endpoint.
Detects a suspicious sequence of command execution patterns characteristic of the Kothamine agent performing post-compromise system discovery. The rule triggers when multiple discovery commands (tasklist, ipconfig, taskkill) are executed by the same process instance within a 5-minute window, consistent with typical C2 behavior for reconnaissance.
Detects a suspicious sequence of command execution patterns characteristic of the Kothamine agent performing post-compromise system discovery. The rule triggers when multiple discovery commands (tasklist, ipconfig, taskkill) are executed by the same process instance within a 5-minute window, consistent with typical C2 behavior for reconnaissance.
Detects a suspicious sequence of command execution patterns characteristic of the Kothamine agent performing post-compromise system discovery. The rule triggers when multiple discovery commands (tasklist, ipconfig, taskkill) are executed by the same process instance within a 5-minute window, consistent with typical C2 behavior for reconnaissance.
Detects a suspicious sequence of command execution patterns characteristic of the Kothamine agent performing post-compromise system discovery. The rule triggers when multiple discovery commands (tasklist, ipconfig, taskkill) are executed by the same process instance within a 5-minute window, consistent with typical C2 behavior for reconnaissance.
Detects the Graphalgo Go-based remote access trojan (RAT) sending an initial system report containing device and user information to the Slack API. This activity occurs during the initial check-in phase before establishing a primary command and control channel.
Detects rapid, multi-category reconnaissance activity initiated by AI-agent binaries (e.g., Claude, Cursor, ChatGPT). The rule identifies sessions that perform four or more distinct discovery operations—spanning account, network service, system information, and network configuration discovery—within a short time window, indicating potentially malicious autonomous exploration by an AI agent. Covers T1046, T1087, T1083, T1016
Detects anomalous activity where AI assistant processes (e.g., Claude, ChatGPT, GitHub Copilot) execute a high volume of diverse discovery commands. The rule correlates multiple discovery categories, such as account, network service, system information, and network configuration discovery, occurring within a short timeframe to identify potential abuse of AI-integrated development tools for host reconnaissance.
Detects anomalous activity where AI assistant processes (e.g., Claude, ChatGPT, GitHub Copilot) execute a high volume of diverse discovery commands. The rule correlates multiple discovery categories, such as account, network service, system information, and network configuration discovery, occurring within a short timeframe to identify potential abuse of AI-integrated development tools for host reconnaissance.
Detects anomalous activity where AI assistant processes (e.g., Claude, ChatGPT, GitHub Copilot) execute a high volume of diverse discovery commands. The rule correlates multiple discovery categories, such as account, network service, system information, and network configuration discovery, occurring within a short timeframe to identify potential abuse of AI-integrated development tools for host reconnaissance.
Detects anomalous, rapid enumeration of system, network, process, and software configuration settings by AI coding assistant processes (e.g., Claude, Cursor, ChatGPT). This behavior often signifies an AI agent being coerced or configured to perform environment discovery or credential gathering, indicating potential compromise or abuse of the LLM-integrated development environment.
Detects anomalous discovery behavior originating from known AI agent and development tools (e.g., Claude, Cursor, Aider). The rule monitors for a rapid sequence of commands spanning multiple categories of enumeration (Network, File/Directory, Software, and System) within a short timeframe, which indicates an attempt to map the runtime environment, permissions, or system capabilities.
Detects anomalous discovery behavior originating from known AI agent and development tools (e.g., Claude, Cursor, Aider). The rule monitors for a rapid sequence of commands spanning multiple categories of enumeration (Network, File/Directory, Software, and System) within a short timeframe, which indicates an attempt to map the runtime environment, permissions, or system capabilities.
Detects anomalous discovery behavior originating from known AI agent and development tools (e.g., Claude, Cursor, Aider). The rule monitors for a rapid sequence of commands spanning multiple categories of enumeration (Network, File/Directory, Software, and System) within a short timeframe, which indicates an attempt to map the runtime environment, permissions, or system capabilities.
This rule detects HTTP POST requests to Vercel-hosted domains containing suspected phishing telemetry (such as device fingerprinting, keystrokes, and user agent collection) originated from a Google Sites frame. This is a common pattern for phishing kits masquerading as legitimate Ledger service pages to harvest credentials and hardware information.
Detects rapid, multi-category reconnaissance activity initiated by AI-agent binaries (e.g., Claude, Cursor, ChatGPT). The rule identifies sessions that perform four or more distinct discovery operations—spanning account, network service, system information, and network configuration discovery—within a short time window, indicating potentially malicious autonomous exploration by an AI agent. Covers T1046, T1087, T1083, T1016
Detects the execution of multiple distinct host reconnaissance commands (e.g., systeminfo, whoami, ipconfig, AV/EDR checks, and domain enumeration) within a short window (10 minutes) originating from the same parent process. This pattern is characteristic of automated reconnaissance collection, often performed during the initial phases of an attack or as part of a C2 workflow. The rule includes exclusions for common administrative, monitoring, and RMM tools to reduce false positives.
Detects reconnaissance commands related to system domain, locale, and environment settings following the execution of rnpkeys.exe from C:\ProgramData\keyroll, a behavior associated with the Sauron Loader. The rule identifies suspicious system discovery commands (nltest, whoami, etc.) or environment checks performed shortly after the loader's execution, indicating potential target verification before C2 registration.
Detects an accelerated sequence of attack phases—specifically recon, privilege escalation, lateral movement, and persistence—occurring on a single device within a short timeframe (15 minutes). This behavioral pattern indicates potential automated or script-orchestrated intrusion activity.
Detects Node.js processes, such as npm package postinstall hooks, spawning shell commands used for host enumeration. This includes accessing system environment variables, network configurations, and filesystem metadata, a pattern frequently utilized by malicious packages for initial reconnaissance post-installation.
Detects a sequence of distinct system and network reconnaissance commands typically performed by malware or RATs for environment fingerprinting. The rule triggers when three or more unique reconnaissance activities—such as querying antivirus status, enumerating network adapters, checking domain information, or listing installed software—occur from the same host within a 5-minute window.
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