Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
This rule monitors for execution of suspicious files or processes and network communication associated with known malicious indicators (hashes, domains, and IP addresses) typically used by specific threat actors for command and control (C2) and payload delivery.
This rule identifies suspicious command and control (C2) activity by monitoring network connections to specific known malicious domains, detection of specific authentication tokens in process command lines, and the use of spoofed User-Agent strings associated with predefined C2 URI paths.
This rule identifies suspicious command and control (C2) activity by monitoring network connections to specific known malicious domains, detection of specific authentication tokens in process command lines, and the use of spoofed User-Agent strings associated with predefined C2 URI paths.
This rule identifies suspicious command and control (C2) activity by monitoring network connections to specific known malicious domains, detection of specific authentication tokens in process command lines, and the use of spoofed User-Agent strings associated with predefined C2 URI paths.
This rule monitors for network connections and process activities associated with known malicious indicators, including file hashes, C2 IP addresses, domains, and specific URLs. It maps these activities to identify potential command and control communication or other malicious network activity occurring on endpoints.
This rule monitors for network connections and process activities associated with known malicious indicators, including file hashes, C2 IP addresses, domains, and specific URLs. It maps these activities to identify potential command and control communication or other malicious network activity occurring on endpoints.
This rule monitors for network connections and process activities associated with known malicious indicators, including file hashes, C2 IP addresses, domains, and specific URLs. It maps these activities to identify potential command and control communication or other malicious network activity occurring on endpoints.
Detects the execution of the Windows FTP client (ftp.exe) using command-line arguments that include scripts (-s:), initiated by unconventional parent processes such as explorer.exe or cmd.exe. This behavior is often associated with the execution of automated FTP scripts for data exfiltration or malware delivery.
Detects anomalous PowerShell script execution originating from GitLab CI runners where the environment variables suggest unauthorized command execution, specifically identifying usage of 'IEX' to execute commands passed via the 'CMD' environment variable, often used in GitRunner C2 techniques.
Detects network traffic (DNS queries, TLS SNI, and HTTP Host headers) associated with the known TukTuk C2 infrastructure domain 'borjumaniya.store'.
Detects coordinated activity patterns across multiple distinct tenant environments within a one-hour window. The rule looks for shared infrastructure (C2 domains), malicious tool hashes, or specific agentic-CLI command line signatures (e.g., related to orchestration, reconnaissance, or exfiltration) that suggest an AI-orchestrated actor or automated attack campaign affecting multiple organizations simultaneously.
Detects outbound HTTPS connections to major generative AI inference endpoints originating from non-browser, non-development tool processes at regular intervals. This activity is indicative of beaconing behavior, where malware (specifically families like LAMEHUG) leverages LLM APIs for dynamic command generation, payload obfuscation, or C2 instruction retrieval, bypassing traditional security controls.
Detects coordinated activity patterns across multiple distinct tenant environments within a one-hour window. The rule looks for shared infrastructure (C2 domains), malicious tool hashes, or specific agentic-CLI command line signatures (e.g., related to orchestration, reconnaissance, or exfiltration) that suggest an AI-orchestrated actor or automated attack campaign affecting multiple organizations simultaneously.
Hunts network, HTTP, and email-URL telemetry for known ARToken infrastructure (operator backend IPs and phishing/panel domains). Bounded to a 30-day lookback and tiers matches by confidence: domain hits are high-confidence (attacker-registered infrastructure), while IP hits are medium-confidence since the IPs sit on shared DigitalOcean hosting that can be reassigned to unrelated tenants once ARToken's infrastructure is taken down. Empty/unparsed indicator fields are excluded to avoid spurious matches in the HTTP event parsing branch. No known file hashes are associated with this intel.
This rule monitors network, file, and process telemetry for matches against a predefined list of malicious IP addresses, domain names, and file hashes. It flags suspicious network connections to known C2 infrastructure and the presence or execution of known malicious files based on SHA256 and SHA1 indicators.
This rule monitors network, file, and process telemetry for matches against a predefined list of malicious IP addresses, domain names, and file hashes. It flags suspicious network connections to known C2 infrastructure and the presence or execution of known malicious files based on SHA256 and SHA1 indicators.
This rule monitors network, file, and process telemetry for matches against a predefined list of malicious IP addresses, domain names, and file hashes. It flags suspicious network connections to known C2 infrastructure and the presence or execution of known malicious files based on SHA256 and SHA1 indicators.
This rule monitors network traffic and DNS queries to identify endpoints attempting to connect to known cryptocurrency scam domains. It correlates data from DeviceNetworkEvents and DnsEvents to capture both direct network connections and DNS resolution attempts.
Detects known file hashes associated with SideCopy/ReverseRAT.
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