Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects a single authenticated user account or client performing a high volume of requests to sequential object IDs on the same API path within a short window. This pattern is characteristic of Broken Object Level Authorization (BOLA) or Insecure Direct Object Reference (IDOR) exploitation, where an attacker attempts to gain unauthorized access to data records that do not belong to them by iterating through predictable numeric identifiers.
Detects high-volume password spraying attempts targeting Microsoft 365, originating from the LSHIY LLC IPv6 address space (2a0a:d683::/32). The rule monitors for failed sign-ins using the OAuth ROPC flow via Azure CLI or similar tools, identifying high counts of distinct accounts targeted within a short time frame.
Detects potential zero-click LLM prompt injection attacks against Microsoft 365 Copilot. The rule correlates Microsoft 365 Copilot activity involving external/untrusted URLs or domains with recent inbound email activity to the same user. This pattern is designed to identify scenarios where an attacker leverages an inbound email to trigger a Copilot interaction with malicious external content, potentially leading to unauthorized data access or exfiltration.
Detects potential OAuth device code phishing attacks by identifying HTTP requests to the legitimate microsoft.com/devicelogin URL containing suspicious user_code or device_code parameters. This pattern indicates an adversary is using an OAuth device authorization grant flow to steal tokens or gain unauthorized access without the victim needing to provide credentials directly to the attacker.
This rule detects potential prompt injection attempts targeting AI systems by looking for specific keywords related to AI models (gpt, claude, copilot) in HTTP logs, combined with suspicious characters or commands commonly used in injection attacks (e.g., <script>, javascript:, eval(). The rule triggers if 5 or more such attempts are observed from a single IP within an hour.
This rule detects instances where a user clicks on a URL identified as potentially malicious (phishing-related) and subsequently has a risky sign-in event in Azure AD. The rule correlates URL click events from email with Azure AD sign-in logs, specifically looking for sign-ins marked as risky or originating from suspicious user agents (e.g., specific axios versions). The phishing URLs are identified by keywords such as 'azureapplicationregistration.pages.dev', 'chrnobinson.com', 'workers.dev', '.pages.dev', '.web.core.windows.net', '/oauth2/v2.0/authorize', 'client_id=', and 'scope=openid'.
This rule detects potential 'impossible travel' scenarios within Azure AD sign-in logs. It identifies users who successfully sign in to Office 365 from two geographically distant IP addresses within a one-hour window, suggesting a potential compromise or an attempt to bypass security controls.
This rule monitors for potential lateral phishing activity within an organization by identifying internal accounts sending high volumes of emails, correlating this with MailItemsAccessed audit events from unexpected IPs, and detecting OAuth token abuse patterns (such as granting consent or adding credentials) within the Exchange Online environment.
Detection for when multi factor authentication has been disabled, which might indicate a malicious activity to bypass authentication mechanisms.
Detects unauthenticated POST requests directed at the '/accessv2' endpoint of an Azure Application Gateway originating from non-internal IP addresses. This behavior is associated with the exploitation of vulnerabilities like CVE-2026-8037.
Detects suspicious activity related to OAuth2PermissionGrant operations, specifically looking for a high volume of successful consent grants by a single user within a short timeframe. This could indicate an attacker attempting to gain broad access to resources by granting permissions to a malicious OAuth application.
This rule detects device registration activities in Entra ID using the specific AppId associated with the DCL broker, which is commonly leveraged to register unauthorized virtual devices. This registration process is often used by adversaries to facilitate Primary Refresh Token (PRT) acquisition, enabling persistent access or bypassing conditional access controls.
Detects indicators of Device Code Lab's PRT Refresh capability, where an administrator's 'Revoke all sessions' (revokeSignInSessions) action is followed by a prt-refresh backend call that reactivates the attacker's session without new user interaction, bypassing standard OAuth refresh token revocation.
This rule detects potentially malicious reconnaissance or enumeration activity by identifying a high volume of Microsoft Graph API requests (GET requests) to sensitive directory endpoints (users, groups, directoryRoles, servicePrincipals) from a single application identity (AppId) and IP address within a short time window.
Detects Microsoft Entra ID (formerly Azure AD) sign-in logs where a single user account authenticates from two different countries within a 10-minute window, which is indicative of potential account compromise or credential sharing.
Detects the creation or update of an Azure Sentinel analytics rule. This can indicate administrative activity related to security monitoring configuration. Monitoring these changes is crucial for detecting potential tampering with detection capabilities or the introduction of malicious rules.
This rule detects suspicious sign-in attempts to Microsoft services (login.microsoftonline.com, graph.microsoft.com, outlook.office365.com) that occur within 30 minutes of a user clicking on a URL associated with these services. The sign-in is considered suspicious if it originates from a user agent commonly used by automated tools (e.g., axios, curl, python-requests, httpclient, Go-http-client) and is flagged with a 'atRisk' or 'high' risk level by Azure AD. This combination suggests a potential credential compromise following a phishing attempt, where an attacker might be using automated tools to leverage stolen credentials.
Detects Server-Side Request Forgery (SSRF) attempts using a double-slash URL manipulation technique. Adversaries append an absolute local file path (e.g., /etc/passwd or /proc/self/environ) after a GitHub blob URL to bypass URL validation logic commonly found in web proxies, API gateways, and serverless environments like GCP Cloud Run.
Detects anomalous device code authentication sessions originating from non-corporate IP addresses using common command-line user agents, which are immediately followed by a device registration event by the same user. This pattern is indicative of OAuth device code phishing, where an attacker tricks a user into authorizing a malicious application to access their account.
Detects anomalous non-interactive OAuth token requests against Microsoft Graph that claim multi-factor authentication (MFA) satisfaction from unmanaged devices. This behavior is indicative of Adversary-in-the-Middle (AiTM) token replay attacks, where captured session tokens are reused by an attacker to bypass authentication controls, consistent with tactics used by threat actors like Storm-2755 (Payroll Pirate).
Detects when a user or service principal is assigned the 'Owner' or 'Contributor' role at the Subscription scope in Azure. This activity is often associated with privilege escalation and persistent access techniques.
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