Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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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 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 the creation and immediate deletion of a GitHub OAuth token that is used to clone or fetch a large volume of private repositories within a short lifespan. This behavior is indicative of an adversary using a temporary, ephemeral token to perform rapid data exfiltration or mass reconnaissance on source code repositories.
Detects the creation and immediate deletion of a GitHub OAuth token that is used to clone or fetch a large volume of private repositories within a short lifespan. This behavior is indicative of an adversary using a temporary, ephemeral token to perform rapid data exfiltration or mass reconnaissance on source code repositories.
This rule detects scenarios where a device registration event occurs within 15 minutes of a device-code authentication sign-in for the same user. This pattern is indicative of potential account manipulation where an adversary registers their own device to an existing account to maintain persistent access or bypass multi-factor authentication (MFA).
Detects anomalous non-interactive sign-ins that bypass multi-factor authentication (MFA) requirements from a geographical location not previously seen in the user's historical sign-in baseline. This pattern is indicative of attackers using stolen OAuth access or refresh tokens to maintain persistence and bypass standard authentication controls.
Detects anomalous access to sensitive Microsoft Graph API endpoints (messages, mailFolders, contacts) following a device-code authentication. The rule specifically flags activity from non-standard or generic client applications, which is a pattern often associated with post-compromise proxying or token abuse, such as the 'ARToken' technique.
Detects potential post-authentication persistent actions (e.g., OAuth app grants, MFA changes, mailbox rule updates) performed shortly after a successful Google Workspace login, specifically flagging actions originating from IP addresses different from the login session to identify session hijacking or token replay (AiTM) activity. Includes suppression for known corporate IP ranges, trusted OAuth application consents, and recurring user behavior.
Detects anomalous administrative activity within Microsoft Exchange by identifying accounts performing multiple suspicious operations within a short timeframe. This rule flags activities like modifying transport rules, virtual directories, or management role assignments, which are often indicative of malicious persistence or configuration tampering, while excluding known authorized service accounts.
This rule correlates email sender activity with network, cloud, and identity logs by matching traffic against a specific IP range (160.79.104.0/21) identified as malicious or suspicious. The rule flags instances where this range appears as an email sender IP or as a remote/source IP address across various infrastructure indices, potentially indicating adversary communication or exfiltration.
This rule detects various event types (email, identity authentication, network connections, and cloud audit logs) originating from or interacting with the specific IP address range 160.79.104.0/22 to 160.79.111.0/22, which is associated with known malicious activity.
Detects rapid, sequential identity-validation API calls (such as GetCallerIdentity, GetSessionToken, or AssumeRole) performed across a large number of distinct AWS access keys from a single source within a short time window. This pattern is indicative of automated tooling validating a harvested corpus of AWS access keys to identify active credentials.
Detects rapid, sequential identity-validation API calls (such as GetCallerIdentity, GetSessionToken, or AssumeRole) performed across a large number of distinct AWS access keys from a single source within a short time window. This pattern is indicative of automated tooling validating a harvested corpus of AWS access keys to identify active credentials.
Detects successful authentication events in Microsoft Entra ID (formerly Azure AD) that utilize the 'device code' OAuth flow. This flow is often used by command-line utilities and headless applications to authenticate users on devices without a web browser, but it is also frequently abused by attackers to perform phishing and session hijacking.
This rule detects anomalous interaction with the Microsoft Graph API by monitoring for high-frequency requests across multiple functional categories (e.g., tenant, directory, privilege, application, repository, mailbox) from a single identity. A large number of distinct API paths across multiple categories in a short time frame is indicative of an attacker performing reconnaissance or automated environment enumeration.
Detects anomalous activity in Azure AD/Microsoft Graph API logs, where a specific user or application performs a high volume of requests across multiple sensitive administrative categories (such as directory roles, authentication methods, applications, and service principals) within a 30-minute window. This behavior is often indicative of reconnaissance or privilege escalation attempts by an adversary who has compromised an identity.
Detects file access or download operations performed by the python-httpx library within a specific cloud application context, which may indicate automated data retrieval or exfiltration attempts by scripts or custom tools.
Detects usage of the 'One Outlook Web' application (ApplicationId 20893) to access Microsoft 365 Exchange REST APIs. This activity is a potential precursor to high-volume mailbox data exfiltration and should be monitored for volumetric anomalies.
Detects instances where a large volume of data (greater than 5GB) is transferred through an anonymous proxy using specific cloud application IDs. This pattern is indicative of potential data exfiltration via third-party or obscured network channels.
Detects high-volume file download or data access events across SharePoint, OneDrive, and Exchange Online. This rule monitors for requests from Python-based HTTP libraries (httpx, requests, urllib) targeting Microsoft Graph API endpoints, which is a pattern indicative of automated bulk data collection or exfiltration, often observed in campaigns like Storm-3121 or Storm-3032.
Detects OAuth2 JWT bearer-grant token requests to Google's OAuth endpoint using the attacker-controlled service-account identity and Sheets API scope observed in the fake GlobalProtect campaign
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