Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
11,847 detections
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Detects lateral movement activities involving the use of PsExec-style tools or the manual creation of remote services to execute commands. This behavior often leverages SMB admin shares (ADMIN$, C$) to drop and execute binaries or scripts, a technique frequently observed in ransomware campaigns and red team engagements.
Detects the execution of legitimate developer utilities msbuild.exe, regasm.exe, and regsvcs.exe in manners consistent with malicious proxy execution. This includes the use of inline tasks in project files, remote network-sourced project files, or specific command-line arguments (such as /codebase or /unregister) that suggest the abuse of these binaries to execute arbitrary code or bypass application control mechanisms, while excluding known legitimate developer-related parent processes and build workflows.
Detects a non-browser process initiating network connections to four distinct commercial LLM API providers (DeepSeek, OpenRouter, Mistral, and Google Gemini) within a 5-minute interval. This behavior is indicative of a C2 pattern where an adversary uses multiple LLM backends to perform plurality-vote or redundant queries, bypassing typical browser-based AI aggregation services.
Detects the execution of the 'sckit' Go implant, a malicious binary associated with trojanized '@memtensor/memos-cloud-openclaw-plugin' or 'MemoryOS' packages. The rule identifies instances where this binary is spawned as a child process of a language runtime (Node.js or Python) when the execution originates from specific directory paths associated with these packages, or when the parent process command line indicates these packages are being initialized.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
This rule detects the execution of browser automation and testing tools (such as Playwright, Puppeteer, Selenium, and various browser drivers) when initiated by common, non-development-related parent processes like Microsoft Office applications, Explorer, or service hosts. This behavior is indicative of potential malicious activity, such as automated credential harvesting or unauthorized web interaction initiated by a compromised document or process.
Detects execution of PowerShell or Python scripts characterized by common patterns found in AI-generated code, including specific obfuscation techniques (base64, string manipulation), boilerplate error handling structures, verbose comments, and generic variable naming conventions. High scores indicate a higher probability of automated or obfuscated script execution.
Detects the execution of high-privilege administrative, firewall, or file-system commands by processes identified as autonomous agent runtimes (e.g., LangChain, AutoGPT) or Robotic Process Automation (RPA) tools. This rule surfaces potential unauthorized infrastructure changes or automated abuse by agents when direct change management validation is absent.
Detects potential exploitation of AI agent frameworks, such as Semantic Kernel, where plugin or tool invocation primitives are abused to execute arbitrary commands or manipulate files via path traversal. The rule monitors for AI-hosting processes (e.g., python.exe, node.exe) spawning shell child processes or file-related commands containing path traversal sequences (e.g., '..\..\') paired with file operation keywords.
Detects autonomous AI coding-agent processes (e.g., Claude Code, Cursor, Aider) spawning shell or git processes to perform potentially destructive actions such as recursive file deletion, forced git pushes, database manipulation, or unauthorized access to sensitive credential files, indicating agentic 'excessive agency' or compromise.
Detects the execution of known living-off-the-land binaries or network utilities initiated by or involving processes related to the Semantic Kernel framework (e.g., SKAgent, kernel.run). This pattern is often indicative of automated execution, potentially associated with agent-based activity or malicious orchestration leveraging AI framework components.
Detects the use of PowerShell to remove the 'Zone.Identifier' NTFS Alternate Data Stream from a file, effectively bypassing Mark-of-the-Web (MOTW) security protections. This behavior is often associated with the 'Unblock-File' cmdlet and is used by adversaries to execute downloaded malicious files without security warnings.
This rule detects a suspicious process execution chain where a Chrome browser process launches cmd.exe, which subsequently spawns a setup executable (setup.exe or setup.tmp), leading to the execution of 7za.exe or a Python script/artifact. This pattern is indicative of a multi-stage malware execution chain, often involving the extraction or execution of payloads dropped via web-based sources.
This rule detects potential ClickFix/InstallFix attacks where a user is socially engineered to copy and paste a malicious command from a website that mimics a legitimate developer tool installation (e.g., Claude Code, NotebookLM). The detection flags the use of common download-and-execute cmdlets (e.g., irm, iwr, iex) within common Windows shell interpreters while excluding known legitimate vendor install domains.
This rule detects potential ClickFix/InstallFix attacks where a user is socially engineered to copy and paste a malicious command from a website that mimics a legitimate developer tool installation (e.g., Claude Code, NotebookLM). The detection flags the use of common download-and-execute cmdlets (e.g., irm, iwr, iex) within common Windows shell interpreters while excluding known legitimate vendor install domains.
Detects the simultaneous activation of three or more distinct browser profiles on the same device within a one-hour window. This behavior is used as a proxy for browser session hijacking or 'browser sync' attacks, where an adversary bridges a compromised personal identity into a managed corporate browser environment.
Detects the simultaneous activation of three or more distinct browser profiles on the same device within a one-hour window. This behavior is used as a proxy for browser session hijacking or 'browser sync' attacks, where an adversary bridges a compromised personal identity into a managed corporate browser environment.
Detects the simultaneous activation of three or more distinct browser profiles on the same device within a one-hour window. This behavior is used as a proxy for browser session hijacking or 'browser sync' attacks, where an adversary bridges a compromised personal identity into a managed corporate browser environment.
Detects the simultaneous activation of three or more distinct browser profiles on the same device within a one-hour window. This behavior is used as a proxy for browser session hijacking or 'browser sync' attacks, where an adversary bridges a compromised personal identity into a managed corporate browser environment.
Detects the simultaneous activation of three or more distinct browser profiles on the same device within a one-hour window. This behavior is used as a proxy for browser session hijacking or 'browser sync' attacks, where an adversary bridges a compromised personal identity into a managed corporate browser environment.
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