Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the 'auto-exfil' pattern associated with the TeamFiltration tool. The rule identifies a sequence of SharePoint Online file access immediately followed by a Microsoft Graph token request from the SharePoint Online Web Client Extensibility app. To reduce noise, it mandates a very short time delta between events (<= 60 seconds) combined with either the use of an IP address/ASN not previously seen for the account in the last 14 days, or a preceding failed sign-in attempt for the account.
Detects accounts showing a spike in requests to public generative-AI services compared to their historical baseline, combined with anomalous indicators like multiple source IPs, regions, or off-hours activity.
Monitors Azure AuditLogs for application consent events that grant high-privilege Microsoft Graph API scopes, such as Mail.Read, Files.ReadWrite.All, or Directory.ReadWrite.All. This activity is a common indicator of illicit consent grant phishing attacks, where adversaries trick users into granting permissions to a malicious OAuth application to gain persistent, unauthorized access to sensitive data without requiring direct user credentials or MFA.
Monitors Azure AuditLogs for application consent events that grant high-privilege Microsoft Graph API scopes, such as Mail.Read, Files.ReadWrite.All, or Directory.ReadWrite.All. This activity is a common indicator of illicit consent grant phishing attacks, where adversaries trick users into granting permissions to a malicious OAuth application to gain persistent, unauthorized access to sensitive data without requiring direct user credentials or MFA.
This rule detects potentially malicious inbox rule creation or modification in Office 365 Exchange. It flags rules that contain keywords associated with financial fraud (e.g., invoice, wire, payment) and include actions that hide evidence (e.g., moving messages to junk or deleting them). It further correlates these actions with suspicious user login activity, such as logging in from a new IP address or country within an hour of the rule change, which is a common indicator of a Business Email Compromise (BEC) account takeover.
Detects OAuth2 authorization code flow attempts in Entra ID (Azure AD) sign-in logs where the redirect URI is external to the Microsoft ecosystem, followed by an immediate token issuance event to that same suspicious endpoint. This behavior is indicative of 'ClickFix' or 'ConsentFix' phishing attacks, where users are manipulated into copying an authorization code from a legitimate Microsoft sign-in prompt and pasting it into an attacker-controlled application.
Detects anomalous sign-in behavior where the same Entra ID session or refresh token is reused from two geographically distant IP addresses within a short timeframe. This activity is correlated with a prior suspicious OAuth consent-grant or device-code authentication event on the same account, which is a common indicator of an 'EvilTokens' style session-token replay attack.
Detects modifications, creations, or deletions of critical CI/CD pipeline configuration files (GitHub Actions, GitLab CI, Jenkins, Azure Pipelines) across cloud service logs. The rule correlates these actions with the account's historical IP baseline to identify potentially unauthorized changes originating from anomalous locations.
Detects a sequence of potentially malicious local command execution (via PowerShell, cmd, or mshta) that mirrors the 'ClickFix' social engineering pattern, followed by an OAuth application consent grant or device-code authorization by the same user within a short timeframe. This behavior is indicative of an adversary attempting to bypass MFA by tricking a user into authorizing a malicious application after establishing local execution on their endpoint.
Detects potential consent phishing attempts by identifying when a user grants high-risk, persistent-access OAuth scopes (such as Mail or Files) to a new third-party application. The rule specifically excludes known first-party Microsoft apps and utilizes a lookback period to avoid alerting on applications that have already been consented to within the tenant, reducing noise from routine enterprise app usage.
Detects potential consent phishing attempts by identifying when a user grants high-risk, persistent-access OAuth scopes (such as Mail or Files) to a new third-party application. The rule specifically excludes known first-party Microsoft apps and utilizes a lookback period to avoid alerting on applications that have already been consented to within the tenant, reducing noise from routine enterprise app usage.
Detects potential consent phishing attempts by identifying when a user grants high-risk, persistent-access OAuth scopes (such as Mail or Files) to a new third-party application. The rule specifically excludes known first-party Microsoft apps and utilizes a lookback period to avoid alerting on applications that have already been consented to within the tenant, reducing noise from routine enterprise app usage.
Detects potential consent phishing attempts by identifying when a user grants high-risk, persistent-access OAuth scopes (such as Mail or Files) to a new third-party application. The rule specifically excludes known first-party Microsoft apps and utilizes a lookback period to avoid alerting on applications that have already been consented to within the tenant, reducing noise from routine enterprise app usage.
Detects instances where an IAM user creates a new access key or requests a session token, followed by subsequent API activity from a different source IP address or region within a one-hour window. This behavior is often associated with the creation of persistence mechanisms or credential theft.
Detects modifications to AWS IAM policies (user or role policies) that grant AdministratorAccess, PowerUserAccess, or wildcard permissions (*). This is a common indicator of privilege escalation or persistence, where an attacker grants themselves or another identity broad administrative access within the AWS account.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects a suspicious pattern where an AI coding agent or user creates a public GitHub repository with specific naming conventions (e.g., 'sweeper-demo', 'gitshot-images') and subsequently pushes content containing sensitive terms like 'screenshot' within a short timeframe. This behavior is indicative of potential data exfiltration of internal development screenshots to a public repository.
Detects cloud service principals identified as AI agents or assistants performing sensitive API operations such as IAM policy modifications or storage configuration changes. This pattern may indicate that an AI service account has been compromised or misused to perform reconnaissance, privilege escalation, or persistence, exceeding its intended scope of operation.
Detects unauthorized privilege escalation for AI agent identities within an orchestration platform. The rule triggers when an AI agent account receives an IAM role change, API scope grant, or tool permission update that lacks a corresponding human-approval audit event, or occurs shortly after the agent generates logs indicating potential prompt injection or anomalous behavior.
Detects the creation of scheduled tasks, recurring jobs, or webhook subscriptions by a user identity flagged as an AI_AGENT. This activity is monitored for persistence, especially when the event lacks a descriptive context or targets external networks, suggesting potential unauthorized agent behavioral drift or malicious persistence.
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