Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
5,879 detections
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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 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 outbound network connections to a known malicious IP address (45.94.31.112) associated with C2 beaconing. The rule identifies communication directed to specific API endpoints (/api/v3/r, /api/v3/s) originating from processes other than common web browsers, suggesting the use of dedicated beaconing or malware agents (e.g., direct WinHTTP usage).
This rule detects network connections to known cryptomining pool IP addresses and domain names, as well as file or process executions matching specific hashes associated with known miner samples. It monitors for communication to command-and-control (C2) servers potentially used for cryptomining operations.
Detects mshta.exe initiating outbound network connections, followed closely by the execution of a powershell.exe process with an unusually large command line, or PowerShell script block events containing large, potentially obfuscated scripts. This behavior is indicative of 'DeepLoad' or 'ClickFix' style staging, where legitimate binaries are leveraged to download and execute heavily obfuscated payloads.
Detects a sequence of activity where an endpoint performs multiple anti-analysis or sandbox evasion checks (using commands like wmic, powershell, or reg to query system information or look for debugger/VM artifacts) followed within 10 minutes by an outbound network connection to a domain that has not been observed from that specific device in the last 7 days.
Detects potential supply chain attacks where a common external script (e.g., a widget) is loaded across multiple unrelated domains, followed by correlation with suspicious user-executed commands indicative of 'ClickFix' tactics (copying and pasting malicious code from a browser-based overlay into the Windows Run dialog).
Detects a potential ClickFix delivery attack where a user navigates to an automotive-themed website, interacts with the system via the Windows Run dialog (RunMRU), and subsequently executes command-line interpreters (powershell, cmd, wscript, mshta) spawned by explorer.exe within a short time window.
Detects the execution of the Chisel C2 tool by matching its unique command-line grammar, specifically the 'client' subcommand combined with reverse remote ('R:') configurations. This detection strategy is resilient against binary renaming and infrastructure rotation by focusing on the tool's required argument structure rather than static IOCs like filenames or C2 addresses. It is specifically useful for identifying unauthorized remote tunnels used for persistence and data exfiltration.
Detects AI agent tooling (e.g., Copilot, Cursor, Ollama) that makes outbound network calls to known AI model providers followed by the execution of suspicious shell commands within a short duration. The rule flags high-severity activities such as download-cradles, credential reconnaissance, LOLBin usage, and persistence mechanisms. Informational alerts are generated for standard CLI activity within the same timeframe.
Detects AI agent tooling (e.g., Copilot, Cursor, Ollama) that makes outbound network calls to known AI model providers followed by the execution of suspicious shell commands within a short duration. The rule flags high-severity activities such as download-cradles, credential reconnaissance, LOLBin usage, and persistence mechanisms. Informational alerts are generated for standard CLI activity within the same timeframe.
Detects AI agent tooling (e.g., Copilot, Cursor, Ollama) that makes outbound network calls to known AI model providers followed by the execution of suspicious shell commands within a short duration. The rule flags high-severity activities such as download-cradles, credential reconnaissance, LOLBin usage, and persistence mechanisms. Informational alerts are generated for standard CLI activity within the same timeframe.
Detects instances where a single process on a device communicates with two or more distinct hosted LLM provider APIs (OpenAI, Anthropic, DeepSeek, Google) within a 24-hour window. This behavior is indicative of multi-model orchestration or 'consensus' techniques, which may be employed by sophisticated implants for automated tasking, data processing, or evasion.
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.
Detects instances where AI coding and agent tools (e.g., Claude Code, Cursor, Copilot CLI, Ollama, LangGraph) create archive or database files containing potentially sensitive data and subsequently initiate network connections to non-AI-provider or non-developer services (exfiltration services or non-standard port connections).
Detects unauthorized processes reading Chromium or Firefox cookie and login stores that specifically reference Claude.ai or Anthropic domains. This rule is designed to identify infostealer malware attempting to hijack active Claude sessions by analyzing process file access and command-line arguments, filtered against known-legitimate security, sync, and development tools. The detection logic mandates corroborating evidence of suspicious execution paths or subsequent outbound network activity.
Detects unauthorized processes attempting to read or copy sensitive browser data files (e.g., Cookies, Login Data, Local Storage) often targeted by info-stealing malware such as Vidar, LummaC2, or RedLine. The rule filters out legitimate browser-related processes and adds security context by requiring evidence of unsigned code, execution from suspicious locations (Temp/Downloads), or associated outbound network activity to reduce false positives.
Detects DNS queries, TLS SNI headers, and HTTP host headers associated with the known exfiltration domain 't.m-kosche.com' linked to the Mini Shai-Hulud malware.
Detects unauthorized execution of a Bun runtime executing an 'index.js' payload within a GitHub Actions workflow context, specifically targeting known compromised action paths (e.g., issues-helper, maintain-one-comment). The detection requires correlation with either sensitive environment/secret access or anomalous outbound network activity originating from the same process, indicating potential credential theft or C2 communication by a malicious CI/CD pipeline component.
This rule monitors network connections, file events, and process execution command lines for references to a list of known malicious URLs, including indicators associated with ClearFake, IClickFix, AMOS, Remus, and Mozi botnet payloads.
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