Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
34 detections
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Detects user account sign-in attempts originating from a country not observed in the previous 30 days, or from an ISP flagged as a VPN, proxy, or hosting/cloud provider. This behavior is consistent with an adversary utilizing stolen credentials or session tokens through anonymity infrastructure to bypass conditional access policies.
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 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 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.
This rule identifies network connections or event logs originating from known residential and anonymous proxy providers, including Nodemaven, DataImpulse, Luminati (Bright Data), ProxyRack, Shifter, SOAX, and Yilu. Adversaries frequently use these proxy services to mask their true origin, evade IP-based geolocation blocks, and conduct malicious activity while blending in with legitimate traffic.
Detects potential cross-family Command and Control (C2) activity by correlating multiple network infrastructure indicators associated with the SilkParasite threat actor. The rule identifies source hosts that interact with at least two distinct indicator sets (specific malicious domains, shared TLS certificates, or cloned homepage content hashes) within a one-hour timeframe.
Detects activity associated with the 'MovieReaper' threat campaign by identifying known malicious file hashes, command and control (C2) IP addresses, and communication with identified malicious domains. This rule monitors process execution, file operations, and network connections within the campaign's active timeframe.
Detects activity associated with the 'MovieReaper' threat campaign by identifying known malicious file hashes, command and control (C2) IP addresses, and communication with identified malicious domains. This rule monitors process execution, file operations, and network connections within the campaign's active timeframe.
This rule monitors for network and email activity associated with known fraudulent AI reseller infrastructure. It aggregates data from device network connections, email URL inspections, and email header analysis to identify potential interactions with malicious domains known to facilitate AI-related fraud.
Detects activity associated with the 'MovieReaper' threat campaign by identifying known malicious file hashes, command and control (C2) IP addresses, and communication with identified malicious domains. This rule monitors process execution, file operations, and network connections within the campaign's active timeframe.
Detects activity associated with the 'MovieReaper' threat campaign by identifying known malicious file hashes, command and control (C2) IP addresses, and communication with identified malicious domains. This rule monitors process execution, file operations, and network connections within the campaign's active timeframe.
This rule detects activity matching known indicators of compromise (IOCs) associated with recent Russian espionage campaigns, including malicious domains, IP addresses, email senders, file names, and file hashes. It monitors network, sign-in, email, process, and file events across enterprise systems.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects Certificate Transparency log entries indicating the issuance of Let's Encrypt certificates where the issuer identifies as 'YE1' and the domain subjects match specific brand impersonation tokens, often associated with fraudulent disposable top-level domains.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects high-volume credential guessing attacks against applications, characterized by a large number of distinct source IP addresses and geographic locations. This pattern is indicative of attackers using residential proxy pools to distribute their attempts, effectively bypassing traditional rate limiting or per-IP WAF thresholds while targeting authentication or error oracles. The rule specifically filters for relevant failure codes and enforces constraints on IP/user diversity to reduce noise from single-point-of-failure events or legitimate infrastructure.
Detects phishing attempts related to 'Operation DoppelBrand' campaign using common email service providers (ESPs) to spoof legitimate-looking emails with fraud-themed subjects, such as invoices or payment requests, associated with the Brickstorm malware.
This rule detects network connections to known CRPx0 relay or Command and Control (C2) IP addresses, as well as DNS requests to domains associated with the CRPx0 infrastructure, including relay nodes, leak sites, and TLD-rotation services.
Detects Certificate Transparency log entries indicating the issuance of Let's Encrypt certificates where the issuer identifies as 'YE1' and the domain subjects match specific brand impersonation tokens, often associated with fraudulent disposable top-level domains.
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