Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects when an AI agent (agentic identity as identified by Entra ID agentType) is added to a group. This activity could represent legitimate provisioning of agent-based workflows, but if unexpected, it may indicate potential privilege escalation or persistence via group-based role assignments.
This rule identifies potentially compromised Entra ID accounts by correlating multiple suspicious behaviors within a 14-day window. It aggregates four specific indicators: successful authentication following repeated MFA failures, impossible travel (sign-ins from multiple countries within a short timeframe), unusual hour logons (00:00-05:00), and sign-ins flagged with medium/high risk or reported as compromised. The rule triggers when an account exhibits two or more of these distinct anomalous behaviors.
Detects anomalous authentication behavior indicative of an Adversary-in-the-Middle (AiTM) phishing kit. The rule identifies multiple password submission attempts (failures) followed by a successful authentication within a short period, consistent with an attacker testing multiple harvested credentials against an active session.
Detects anomalous reuse of an authenticated Microsoft 365 session cookie shortly after a successful MFA-satisfied sign-in. The detection identifies scenarios where the subsequent access originates from a different IP address, device, or user agent without an intervening MFA challenge, which is a pattern indicative of session hijacking techniques like Adversary-in-the-Middle (AiTM) or session token replay.
Detects non-interactive sign-in events involving OIDC or external authentication tokens shortly after a known Coder registry compromise. The rule flags high-risk or at-risk single-factor authentication sessions, which may indicate the replay of stolen tokens harvested during the compromise window.
This rule identifies potentially compromised Entra ID accounts by correlating multiple suspicious behaviors within a 14-day window. It aggregates four specific indicators: successful authentication following repeated MFA failures, impossible travel (sign-ins from multiple countries within a short timeframe), unusual hour logons (00:00-05:00), and sign-ins flagged with medium/high risk or reported as compromised. The rule triggers when an account exhibits two or more of these distinct anomalous behaviors.
Detects successful authentication to Microsoft Teams or Slack where MFA was successfully completed, but the device is reported as unmanaged or non-compliant and is accompanied by sign-in risk signals. This behavior is consistent with Adversary-in-the-Middle (AitM) proxy attacks where an attacker captures credentials and session tokens, bypassing MFA, and using the hijacked session from an unrecognized device or location.
KQL Query
This rule monitors web server logs (IIS, W3C, and Azure Application Gateway) for incoming traffic that matches known malicious or automated vulnerability scanners, as well as requests for common system fingerprinting paths (such as /server-status or /.git/config). The rule aggregates these hits by source IP address to identify potential active reconnaissance or vulnerability scanning attempts.
This rule retrieves security anomaly events generated by Microsoft's identity protection or behavioral analysis systems for a specific user account over a defined time range. It leverages the 'Anomalies' table within Microsoft Sentinel to surface identity-related insights, activity patterns, and flagged risks.
Detects anomalous sign-in behavior shortly after a successful MFA-authenticated session in Microsoft 365. This rule flags scenarios where a subsequent session for the same user occurs within a short window (30 minutes) from a different IP, ASN, User-Agent, or device identifier, potentially indicating the replay of a stolen session cookie obtained via Adversary-in-the-Middle (AiTM) phishing.
Detects role assignments made directly by a user, bypassing PIM workflow direct assignments are permanent, don't require approval, and don't expire
This rule detects high-frequency account and email address enumeration attempts. It monitors syslog data for SMTP commands such as VRFY, EXPN, or RCPT TO, and analyzes Microsoft Entra ID (SigninLogs) for authentication failures specifically associated with error code 50034 (user not found). Both behaviors are indicative of an adversary attempting to validate user identities within an environment, often as a precursor to targeted phishing or brute-force attacks.
This rule detects OAuth authorization requests (targeting Microsoft or Google identity providers) that use 'prompt=none' (silent authentication) and redirect the user to an unexpected or untrusted domain. This pattern is commonly used in OAuth consent phishing or token theft attacks, where an attacker attempts to silently acquire an authorization code by redirecting it to a malicious application server instead of the legitimate service provider's domain.
Detects signs of Adversary-in-the-Middle (AiTM) phishing kits by identifying sequential, rapid-fire attempts to authenticate using multiple distinct MFA methods (such as push notifications, TOTP codes, or SMS) within a single sign-in session. These attempts are combined with explicit failure states (rejected passwords, rejected codes, or denied MFA requests), suggesting an attacker is relaying authentication challenges in real-time to a victim.
This rule monitors for high or medium-risk user events and sign-in activities within Azure Active Directory. It correlates data from both the AADUserRiskEvents and SigninLogs tables to identify potentially compromised user accounts.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
Detects successful device code authentication flows from users who have not utilized this authentication method within the past 14 days. This rule monitors Entra ID (Azure AD) sign-in logs and non-interactive logs, enriching results with Intune device compliance data and authentication protocol details to assist in identifying anomalous access patterns that may indicate credential abuse or device-code phishing.
Detects SSRF attempts targeting cloud metadata endpoints or internal/private network addresses.
This rule detects scenarios where a user account registers or adds a new device and subsequently performs a sign-in session within one hour that is either marked as high/medium risk or occurs via sensitive applications like the Azure Portal or Microsoft Graph. This pattern often indicates account compromise, where an attacker has registered a rogue device to gain persistent access or perform administrative tasks.
This rule detects potential session token replay attacks in Azure Active Directory by correlating interactive or single-factor sign-in events using 'python-requests' user agents (common in automated tooling) with subsequent 'Register device' and 'Register security info' (Windows Hello for Business) activity within a 48-hour window. This behavior often indicates an adversary attempting to register a device to a compromised account to maintain persistence or bypass MFA requirements.
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