Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects high-volume file access, preview, or download activity from SaaS applications (SharePoint, OneDrive, Exchange Online) originating from IP addresses classified as anonymous proxies. The threshold is set to 1000 events within a 2-hour window, which is indicative of automated, high-speed data exfiltration rather than standard user behavior.
Detects anomalous, high-volume enumeration of SharePoint and OneDrive resources via Microsoft Graph API by monitoring for repeated access patterns involving /sites, /drives, or /drive endpoints combined with search, directory traversal, and pagination parameters.
Detects anomalous or high-volume activity related to Microsoft Graph API calls targeting email messages, mail folders, or attachments. This behavior is indicative of potential unauthorized bulk email collection or exfiltration attempts, often observed in account compromise scenarios where an attacker enumerates and downloads mail contents.
Detects anomalous or high-volume activity related to Microsoft Graph API calls targeting email messages, mail folders, or attachments. This behavior is indicative of potential unauthorized bulk email collection or exfiltration attempts, often observed in account compromise scenarios where an attacker enumerates and downloads mail contents.
Detects anomalous, high-volume file access (downloading, accessing, or previewing) in cloud applications that originates from an IP address identified as an anonymous proxy. This behavior is indicative of potential data exfiltration or unauthorized mass data collection.
This rule detects potentially malicious interaction with specific GCP service account identifiers and client IDs. It monitors multiple log sources—including cloud audit logs, sign-in activity, security logs, and device network events—to identify unauthorized access, command and control communication, or data exfiltration attempts targeting Google API services (specifically oauth2.googleapis.com and sheets.googleapis.com).
Detects anomalous certificate-based authentication attempts to Jasmine network services characterized by rapid, impossible-travel scenarios or geo-inconsistent session patterns. This behavior is indicative of a stolen certificate being reused from a different geographic location or network, bypassing standard authentication patterns.
Detects anomalous certificate-based authentication attempts to Jasmine network services characterized by rapid, impossible-travel scenarios or geo-inconsistent session patterns. This behavior is indicative of a stolen certificate being reused from a different geographic location or network, bypassing standard authentication patterns.
Detects a GitLab personal access token/response indicating Owner-level (access_level 50) group access combined with the broad 'api' scope on the sensitive gnutls/gnutls project -- the excessive standing-privilege pattern that turned one leaked token into a 55-project exposure.
Detects the gitlab-triage automation tool being invoked with a personal access token scoped to the broad 'api' permission rather than a narrower issue/MR-only scope, inflating the blast radius if the token leaks.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
Detects anomalous sign-in behavior where a device code authentication flow is initiated from one location, but the resulting session is replayed from a different IP address in a different country within a one-hour window. This behavior is indicative of an adversary capturing an authentication token via a device code phishing or relay attack and attempting to use it from their own infrastructure to bypass conditional access policies and MFA.
This rule detects potential OAuth 2.0 device code phishing attempts by monitoring network activity for requests to common Microsoft OAuth device authorization endpoints. It flags requests that utilize a specific hardcoded client_id associated with known suspicious application registrations, combined with requested scopes for graph.microsoft.com and a Python-based user agent. This behavior is indicative of an adversary attempting to gain unauthorized access by tricking a user into authorizing a malicious application.
This rule detects potential OAuth 2.0 device code phishing attempts by monitoring network activity for requests to common Microsoft OAuth device authorization endpoints. It flags requests that utilize a specific hardcoded client_id associated with known suspicious application registrations, combined with requested scopes for graph.microsoft.com and a Python-based user agent. This behavior is indicative of an adversary attempting to gain unauthorized access by tricking a user into authorizing a malicious application.
Detects instances where a user successfully authenticates using the OAuth Device Code flow followed by subsequent mailbox operations (such as reading, sending, or deleting items) from a different IP address within a 10-minute window. This behavior is a strong indicator of adversary-in-the-middle phishing attacks where an attacker captures a session token and utilizes it from a remote location.
This rule monitors Entra ID Audit Logs for device registration events where the display name of the registered device matches a specific naming pattern used by the GhostCode phishing kit. The pattern typically consists of three dash-separated words, a dash-separated hex string, and an optional suffix, which is indicative of automated phishing-based device enrollment.
This rule monitors Entra ID Audit Logs for device registration events where the display name of the registered device matches a specific naming pattern used by the GhostCode phishing kit. The pattern typically consists of three dash-separated words, a dash-separated hex string, and an optional suffix, which is indicative of automated phishing-based device enrollment.
Detects suspicious Microsoft Intune device enrollment activities characterized by the use of a spoofed User-Agent (matching Microsoft Office/Outlook strings) and rapid, multiple enrollment attempts within a short timeframe. This behavior is associated with adversary use of device-code phishing kits to enroll rogue devices using stolen session tokens.
Detects a successful user authentication event following a Microsoft OAuth 2.0 device authorization grant flow. This detection identifies scenarios where a user may have been phished into entering an attacker-supplied device code on a malicious Microsoft device login page, resulting in the attacker successfully obtaining OAuth tokens.
Detects anomalous device registration activity where a single user principal registers three or more distinct devices within a short duration (2 minutes). This behavior is characteristic of device-code phishing attacks where adversaries abuse stolen device authorization codes to register multiple rogue devices, potentially for PRT (Primary Refresh Token) acquisition.
Detects malicious OAuth 2.0 device authorization grant requests directed at Microsoft services. This rule identifies usage of specific App IDs associated with the Microsoft Authentication Broker combined with the 'offline_access' Graph scope, a pattern indicative of GhostCode-style phishing campaigns designed to steal access and refresh tokens.
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