Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous Entra ID sign-in patterns indicating potential session hijacking or stolen session cookie replay. The rule identifies pairs of successful sign-ins where the geographic distance and time elapsed suggest impossible travel, or where the device/browser context changes without a fresh MFA challenge, suggesting the bypass of authentication requirements via persistent session tokens.
Detects successful authentication attempts using legacy protocols or non-interactive refresh tokens for user accounts previously flagged within a 14-day window as being involved in infostealer or credential exposure events.
This rule detects potential session hijacking by monitoring for the reuse of session or refresh tokens from unrecognized devices, browsers, or user agents, particularly when such activity occurs without an interactive MFA challenge. This behavior is indicative of an attacker attempting to use stolen session cookies or tokens to access cloud resources.
Detects anomalous authentication patterns where multiple distinct user identities authenticate from the same source IP (often a VPN or proxy) within a short timeframe, characteristic of North Korean IT worker laptop-farm or identity-mule operations where a single operator manages multiple contractor accounts.
Detects user authentication events to recruitment, career, or applicant-tracking applications where the connection originates from an anonymizing proxy, VPN, or datacenter IP address. This behavior has been observed as a precursor to North Korean IT worker recruitment fraud, where attackers mask their true geographic location to gain unauthorized employment.
Detects user account sign-in attempts originating from a country not observed in the previous 30 days, or from an ISP flagged as a VPN, proxy, or hosting/cloud provider. This behavior is consistent with an adversary utilizing stolen credentials or session tokens through anonymity infrastructure to bypass conditional access policies.
Detects the reuse of session tokens from distinct network locations, devices, or user agents shortly after a successful MFA-protected login. This behavioral pattern is a primary indicator of Adversary-in-the-Middle (AiTM) phishing, where attackers capture session tokens via reverse proxy to bypass authentication controls.
Detects potential Adversary-in-the-Middle (AiTM) phishing activity where a user successfully authenticates to Microsoft 365 with MFA, followed shortly by a session from a different IP address reusing the same session ID without a repeated MFA challenge.
Detects potential Adversary-in-the-Middle (AiTM) MFA bypass attacks (quishing). The rule correlates receipt of an email containing an image attachment (potential QR code) but no URL, followed by a risky mobile sign-in event from a device that is unmanaged or lacks trust within a two-hour window.
Detects instances where a user account triggers a risky sign-in event (flagged by identity protection) and subsequently uses the same session or token to authenticate successfully from a different network location or IP address within two hours. This behavior suggests that a malicious actor may be leveraging a compromised session token that should have been revoked, potentially indicating a failure of continuous access evaluation or token revocation mechanisms.
Detects potential Adversary-in-the-Middle (AiTM) activity by identifying successful multi-factor authenticated sign-in events from the same user across different geographic regions and IP addresses within a one-hour timeframe, which is characteristic of session cookie replay attacks.
Detects the execution of cloud CLI tools (aws, az, gcloud) using Unix shells (bash, sh) to perform sensitive operations such as listing secrets, keys, or metadata, which may indicate credential discovery or exfiltration.
Detects AWS CloudTrail and Azure Active Directory (Entra ID) privilege-escalation actions (e.g., attaching policies, creating access keys, adding roles) performed by principals from rare source IPs or associated with low-frequency administrative actions, indicating potentially compromised or unauthorized account activity.
This rule detects potential illicit consent grants to OAuth applications within Azure AD. It identifies applications requesting high-risk scopes (such as Mail.Read, Files.ReadWrite.All, etc.) that are not verified by a publisher, are granted by non-admin users, and subsequently exhibit high volumes of graph API calls (suggestive of unauthorized data access or exfiltration).
Detects potential Golden SAML activity by correlating Azure AD SAML sign-in events for privileged accounts with a lack of corresponding server-side ADFS authentication logs, unusual SAML issuer URIs, lack of on-premises authentication logs, or evidence of direct access to ADFS token-signing certificate private key material.
Detects repeated, silent authentication events in Microsoft 365 where MFA challenges are absent, consistent with the use of stolen session or refresh tokens (e.g., EvilTokens) to maintain persistent, unauthorized access to user accounts.
Detects the granting of OAuth application permissions or app role assignments in Azure AD/Entra ID that include high-privilege scopes such as Mail.Read, Directory.ReadWrite.All, or offline_access. This behavior is characteristic of consent phishing attacks, where adversaries trick users into granting permissions to a malicious application to maintain persistent access to resources like email or tenant directories.
Detects instances where a user grants consent to an unverified OAuth application with high-privilege scopes (e.g., Mail.Read, Directory.Read.All), followed by an authentication event using that same application ID from a different IP address within 24 hours. This behavior is indicative of potential consent phishing or OAuth token abuse, where an adversary harvests tokens to maintain persistent, remote access to email or directory services.
Detects potential session hijacking where an Entra ID session is reused by a non-managed/non-compliant device from a different IP and country shortly after an initial authentication from a managed device. This pattern is consistent with infostealer malware stealing session tokens and replaying them on attacker-controlled infrastructure to bypass MFA.
Detects potential session hijacking where an Entra ID session is reused by a non-managed/non-compliant device from a different IP and country shortly after an initial authentication from a managed device. This pattern is consistent with infostealer malware stealing session tokens and replaying them on attacker-controlled infrastructure to bypass MFA.
Detects potential session hijacking where an Entra ID session is reused by a non-managed/non-compliant device from a different IP and country shortly after an initial authentication from a managed device. This pattern is consistent with infostealer malware stealing session tokens and replaying them on attacker-controlled infrastructure to bypass MFA.
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