Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
1,235 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 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 Azure AD user sign-ins from multiple distinct IP addresses or countries within a 1-hour window. This is a common heuristic used to identify potentially compromised credentials or impossible travel scenarios, where a single user account authenticates from geographically distant or disparate network locations in an unrealistic timeframe.
Detects an anomalous volume of artificial intelligence model inference API calls (e.g., AWS Bedrock, Azure OpenAI, Google Vertex AI) initiated by a single IAM principal or API key within a short time window. This activity is indicative of 'LLMjacking', where compromised cloud credentials are leveraged by threat actors to perform unauthorized, high-cost AI model inference tasks.
Detects a suspicious sequence of events where a user engagement (voice/video call) involving themes of urgency or helpdesk interaction is closely followed by a high-risk administrative action (e.g., password reset, MFA device enrollment, or financial transfer) by the same user, where the communication session context differs from standard activity, indicative of a deepfake-enabled vishing attack.
Detects sensitive cPanel/WHM administrative commands or system file modifications occurring within one hour of a suspected authentication bypass event, indicative of potential post-exploitation activity related to CVE-2026-41940.
Detects the execution of known remote access or remote monitoring software (such as TeamViewer, AnyDesk, or ScreenConnect) on corporate-issued Windows endpoints. The rule triggers on process execution patterns associated with unauthorized remote control, specifically looking for indicators of unattended access or silent installation commonly used by overseas actors to remotely operate company-issued laptops assigned to fraudulently hired identities.
Detects the execution of known remote access or remote monitoring software (such as TeamViewer, AnyDesk, or ScreenConnect) on corporate-issued Windows endpoints. The rule triggers on process execution patterns associated with unauthorized remote control, specifically looking for indicators of unattended access or silent installation commonly used by overseas actors to remotely operate company-issued laptops assigned to fraudulently hired identities.
Detects user sign-ins that utilize an 'External Authentication Method' within 3 days of a password reset event. This behavior may indicate an adversary has successfully established persistence using a rogue authentication provider (e.g., via a TrustSink or similar malicious configuration) that survives password remediation and is capable of capturing or intercepting subsequent authentication tokens.
Detects anomalous Entra ID sign-in patterns characterized by a single session ID replayed from multiple diverse source IP addresses and Autonomous System Numbers (ASNs) within a short timeframe. This behavior is indicative of Session Hijacking (AiTM/Adversary-in-the-Middle) where an attacker maintains persistence by proxying requests through a residential network to bypass conditional access policies and evade location-based threat detection.
Detects modifications to payroll direct deposit or payment election settings within Workday. This activity is a common indicator of payroll fraud or Business Email Compromise (BEC), where an attacker gains access to an employee's Workday account to redirect salary payments to an unauthorized bank account.
These rules monitor for suspicious WordPress authentication activity, including brute force and credential spraying attacks targeting XML-RPC endpoints and the standard wp-login.php interface. The rule set includes detections for high-frequency login attempts and subsequent indicators of potential successful authentication.
Detects instances where a removed GitHub organization member performed bulk repository access (cloning or downloading) shortly before their removal, potentially indicating exploitation of retained access by a departed employee or an adversary using a valid account before deprovisioning. The rule identifies activity occurring more than 24 hours prior to removal involving multiple repositories or multiple access actions.
Detects rapid, bulk cloning or downloading of GitHub repositories containing sensitive data (e.g., consensus algorithms, PII, internal blocklists). This behavior is characteristic of unauthorized data exfiltration, specifically tracking activity involving suspicious OAuth token prefixes (gho_) and rapid high-volume access to sensitive organizational assets within a short timeframe.
Detects successful authentication events for accounts that have been dormant for at least 90 days, correlated with suspicious activity markers such as recent failed sign-in attempts, access from an unfamiliar geographic location or ASN, or a complete absence of historical sign-in activity.
Detects successful authentication events for accounts that have been dormant for at least 90 days, correlated with suspicious activity markers such as recent failed sign-in attempts, access from an unfamiliar geographic location or ASN, or a complete absence of historical sign-in activity.
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
Detects patterns associated with the TeamFiltration backdoor module, specifically unauthorized OneDrive/SharePoint file modifications occurring shortly after an authentication from a previously unseen device/IP. The rule flags file changes (modifications, deletions, or renames) involving potential executable or script extensions, or those performed by the OneDrive SyncEngine app from a new source.
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