Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects bulk read operations on AWS Secrets Manager or similar cloud secret stores where the accessed resources contain keywords related to cryptocurrency custody, private keys, or wallet material. This pattern is indicative of unauthorized exfiltration attempts by threat actors such as Slim Spider targeting digital asset infrastructure.
Detects anomalous reconnaissance activity targeting sensitive Microsoft Graph control-plane endpoints, including directory roles, MFA settings, application registrations, service principals, and OAuth consent configurations. The rule identifies high-volume access across multiple distinct sensitive endpoints within a short time frame, which is indicative of an adversary enumerating infrastructure to identify opportunities for privilege escalation, persistence, or bypass of security controls.
This rule detects successful or attempted sign-ins to Microsoft Entra ID using the OAuth 2.0 device authorization grant flow. This specific authentication flow is increasingly leveraged by adversaries in passkey-themed phishing campaigns to obtain valid access and refresh tokens without requiring direct credential or cookie theft. By monitoring for this protocol usage, security teams can identify potential attempts to bypass traditional authentication mechanisms.
Detects instances where a user grants high-privilege permissions (Mail.Read, Files.ReadWrite.All, offline_access) to an OAuth application within 24 hours of a risky sign-in event. This pattern is commonly observed in AiTM (Adversary-in-the-Middle) or consent-phishing attacks designed to establish persistent access to cloud resources.
Detects high-volume AI/LLM inference or GPU-compute provisioning activity from a single identity within a short duration. This behavior is indicative of LLMJacking, where compromised cloud credentials are used to spin up unauthorized, resource-intensive AI workloads for profit.
Detects high-volume AI/LLM inference or GPU-compute provisioning activity from a single identity within a short duration. This behavior is indicative of LLMJacking, where compromised cloud credentials are used to spin up unauthorized, resource-intensive AI workloads for profit.
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 Microsoft Intune MDM enrollment events occurring shortly after an OAuth 2.0 device code authentication for the same user. This pattern is indicative of an adversary using stolen OAuth tokens or Primary Refresh Tokens (PRT) to perform rogue MDM enrollment, a technique used to maintain persistence and bypass standard security controls such as password resets.
Detects rapid succession of a successful device code authentication followed by the acquisition of a Primary Refresh Token (PRT) within 80 seconds for the same user. This pattern is indicative of device code phishing (or 'quishing'), where an adversary tricks a user into entering an authorization code into a malicious application to steal their session.
The following analytic detects when a user in an Azure AD environment grants consent to an OAuth application. It leverages Azure AD audit logs to identify events where users approve application consents.
This activity is significant as it can expose organizational data to third-party applications, a common tactic used by malicious actors to gain unauthorized access.
If confirmed malicious, this could lead to unauthorized access to sensitive information and resources. Immediate investigation is required to validate the application's legitimacy, review permissions, and mitigate potential risks.
This activity is significant as it can expose organizational data to third-party applications, a common tactic used by malicious actors to gain unauthorized access.
If confirmed malicious, this could lead to unauthorized access to sensitive information and resources. Immediate investigation is required to validate the application's legitimacy, review permissions, and mitigate potential risks.
Detects high-privilege administrative actions, such as adding collaborators, transferring repository ownership, generating personal access tokens, or pushing code, performed on GitHub repositories classified as 'plugin' types. This rule monitors for potential supply chain compromise or unauthorized access within plugin development workflows.
Detects rapid access to multiple Microsoft 365 collection applications (Office, OneDrive, Teams) by a user account from specific AWS EC2 IP ranges identified as associated with the TeamFiltration tool. This behavior is consistent with automated exfiltration of email, chats, and files.
Detects high-volume account existence checks targeting the Microsoft Teams API. The rule identifies anomalous authentication attempts characterized by the use of outdated Electron/Chrome user-agent strings associated with the TeamFiltration tool, specifically targeting the Microsoft Teams API AppId (1fec8e78-bce4-4aaf-ab1b-5451cc387264).
Detects high-volume account existence checks targeting the Microsoft Teams API. The rule identifies anomalous authentication attempts characterized by the use of outdated Electron/Chrome user-agent strings associated with the TeamFiltration tool, specifically targeting the Microsoft Teams API AppId (1fec8e78-bce4-4aaf-ab1b-5451cc387264).
Detects rapid access to multiple Microsoft 365 collection applications (Office, OneDrive, Teams) by a user account from specific AWS EC2 IP ranges identified as associated with the TeamFiltration tool. This behavior is consistent with automated exfiltration of email, chats, and files.
This rule detects potential CI/CD security compromises in GitHub by monitoring for modifications to workflow permissions that grant 'write-all' access, access to sensitive workflow secrets via 'pull_request_target' from forked repositories, and the registration of new self-hosted runners. These actions are common indicators of supply chain attacks aimed at poisoning pipeline execution or exfiltrating build secrets.
Detects high-volume, rapid enumeration of core Microsoft Graph directory endpoints (users, groups, applications, and servicePrincipals) by a single identity or session. This behavior is indicative of reconnaissance tools such as AADInternals, ROADtools, or TokenTactic being used to map out a cloud environment's directory structure.
Detects high-volume, rapid enumeration of core Microsoft Graph directory endpoints (users, groups, applications, and servicePrincipals) by a single identity or session. This behavior is indicative of reconnaissance tools such as AADInternals, ROADtools, or TokenTactic being used to map out a cloud environment's directory structure.
Detects Microsoft Entra ID service principal (app-only) sign-in events where an application accesses a resource or tenant that has not been observed in the previous 30 days. This is often an indicator of cross-tenant impersonation abuse or credential misuse, particularly related to Actor Tokens.
Detects Microsoft Entra ID service principal (app-only) sign-in events where an application accesses a resource or tenant that has not been observed in the previous 30 days. This is often an indicator of cross-tenant impersonation abuse or credential misuse, particularly related to Actor Tokens.
Detects the creation or modification of Microsoft Power Automate flows that integrate internal Microsoft 365 services (SharePoint, OneDrive, Exchange) with external communication or exfiltration targets (HTTP requests, external email addresses, or common external web services). This behavior is often indicative of automated data exfiltration.
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