Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects repeated, small outbound HTTP/HTTPS requests to an external destination, a behavior characteristic of scripted command-and-control (C2) beaconing where a client periodically polls a server for instructions.
Detects large HTTP POST requests (exceeding 100KB) directed to public LLM API endpoints such as OpenAI or Anthropic. This behavior may indicate potential bulk data exfiltration or unauthorized sharing of sensitive data with external AI providers.
Detects the ClosedQuorum 'unhook' evasion technique where a process patches ntdll's EtwEventWrite to suppress ETW telemetry, occurring within a 5-minute window of the same process initiating outbound network connections to known LLM C2 provider APIs or Discord webhooks used for AI-arbitrated decision cycles.
Detects instances where a non-browser process initiates connections to commercial LLM provider APIs (DeepSeek, OpenRouter, Mistral) followed by a connection to Discord CDN/Webhook endpoints within a 15-minute window. This behavior is indicative of a process acting as an autonomous C2 agent that exfiltrates data after receiving instructions or processing information via an LLM.
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 installation of unauthorized AI-related browser extensions followed by outbound network communication from the browser process to known external AI service API endpoints within one hour. This behavior is indicative of potential data exfiltration via shadow AI tools, bypassing standard enterprise DLP controls.
Detects the execution of 'LevelInstaller.exe' with specific installation arguments ('--action install --force --key') in conjunction with the presence of the 'level.exe' binary in its designated Program Files directory. The rule optionally identifies related scheduled task creation for 'Level Watchdog' and network activity associated with the 'level.io' domain or specific IP address.
This rule detects potentially malicious activity involving the execution of Node.js scripts initiated by system script proxies (wscript, cscript, msiexec) within specific paths, often associated with subsequent installation of VBScript agents or direct network communication with a known command-and-control IP address.
This rule detects rundll32.exe executing a DLL from the ProgramData directory and subsequently establishing five or more outbound network connections to external IP addresses over non-standard ports (excluding 80 and 443) within a one-hour window. This behavior is indicative of a potential malware beaconing or data staging activity using a proxy binary to evade detection.
This rule detects potential Cobalt Strike SMB beacon activity by identifying the creation of suspicious named pipes (commonly associated with Cobalt Strike) and correlating them with low-jitter, uniform outbound network communication patterns typical of command and control (C2) beaconing behavior.
Detects the installation of AI-related packages (e.g., mcp, tiktoken_mcp) via common package managers (pip, npm, docker) followed by an outbound network connection from the same host within 10 minutes. This behavior is consistent with supply chain attacks where trojanized AI/MCP components are used to initiate command-and-control communication shortly after deployment.
Detects a suspected device-code phishing attack where a user visits a known malicious lure domain and shortly thereafter completes a successful Microsoft 365 device-code authentication. This rule correlates network events with sign-in logs within a 10-minute window to identify session hijacking attempts that bypass traditional MFA.
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 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 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 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 coordinated activity indicative of destructive malware propagation similar to NotPetya. The rule identifies a three-stage sequence on a single host: execution of a DLL via rundll32.exe, followed by file writes to administrative network shares (C$/ADMIN$), and remote process creation via WMI (WmiPrvSE.exe), correlated with a high volume of SMB connections.
This rule performs a sweep across device file and network events for indicators of compromise (IOCs) associated with the UAT-11587/Antino campaign. It detects malicious file hashes, specific C2 domain connections, and known lure URLs (HTA/WSF) identified by Cisco Talos.
This rule performs a sweep across device file and network events for indicators of compromise (IOCs) associated with the UAT-11587/Antino campaign. It detects malicious file hashes, specific C2 domain connections, and known lure URLs (HTA/WSF) identified by Cisco Talos.
This rule performs a sweep across device file and network events for indicators of compromise (IOCs) associated with the UAT-11587/Antino campaign. It detects malicious file hashes, specific C2 domain connections, and known lure URLs (HTA/WSF) identified by Cisco Talos.
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