Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects instances where a user experiences an interrupted sign-in event (Azure AD error code 50199) followed closely by a successful sign-in from the same user account. This pattern is often indicative of Adversary-in-the-Middle (AiTM) phishing, where an attacker intercepts an authentication request, prompts the user, and replays the captured session material.
Detects potential account compromise by identifying a specific sequence of behavior: reconnaissance of sensitive users (HR/Payroll) via Microsoft Graph API calls, followed by the creation of inbox rules (e.g., forwarding) by the same user account within a 12-hour window.
Detects anomalous, automated non-interactive sign-in activity in Microsoft 365 where a session token is replayed from a new source IP address approximately every 8 hours. This pattern is characteristic of automated token-refresh tooling, such as that associated with Storm-2755, utilizing specific user-agents (Firefox 131.0/151.0 or python-requests) that deviate from the user's typical browser fingerprint.
This rule detects non-interactive sign-in events to common Microsoft services (e.g., OfficeHome, Outlook) where the User-Agent string contains 'axios/1.7.9'. This pattern is frequently associated with Adversary-in-the-Middle (AiTM) phishing kits that use the Axios library to automate token replay attacks by simulating browser sign-in requests.
Detects non-interactive sign-in events to M365 that claim to be from the Outlook client application but utilize suspicious or unexpected User-Agent strings (e.g., Python requests, specific Firefox versions). This behavior is often indicative of programmatic access or automated tools used by attackers to harvest credentials or interact with mailboxes, bypassing standard browser-based authentication controls.
Detects Microsoft Entra OAuth 2.0 device authorization grant flow completion immediately followed by non-interactive API access from automated user agents like python-requests. This behavior is indicative of device code phishing kits, where an attacker tricks a user into entering a code and then programmatically hijacks the resulting session token.
Detects sign-in events using the OAuth 2.0 device code flow, which is a mechanism often abused in phishing campaigns (such as GhostCode) to lure users into authorizing malicious applications or granting access tokens without needing their actual credentials.
Detects suspicious non-interactive Entra ID sign-in events using the 'python-requests' User-Agent against sensitive Microsoft resources such as Microsoft Graph, Device Registration, or Intune. This activity is indicative of automated token abuse, particularly in the context of device-code phishing kits (e.g., GhostCode), where an attacker uses stolen session information to interact with Microsoft APIs.
Detects a suspected EvilTokens attack sequence where a user clicks a phishing URL and subsequently initiates a browser session to the Microsoft device-code authorization page (devicelogin) within 15 minutes, with the phishing lure domain appearing in the browser context.
Detects a suspected EvilTokens attack sequence where a user clicks a phishing URL and subsequently initiates a browser session to the Microsoft device-code authorization page (devicelogin) within 15 minutes, with the phishing lure domain appearing in the browser context.
Detects a suspected EvilTokens attack sequence where a user clicks a phishing URL and subsequently initiates a browser session to the Microsoft device-code authorization page (devicelogin) within 15 minutes, with the phishing lure domain appearing in the browser context.
Detects potential device code phishing patterns where a successful OAuth device-code authentication is rapidly followed by Microsoft Graph resource access from the same account. The rule identifies suspicious polling sessions (e.g., EvilTokens) by monitoring for successful device-code sign-ins and immediate, subsequent Graph API activity. It filters known first-party applications and incorporates risk-based triggers and reconnaissance behavioral patterns to minimize false positives.
Detects anomalous post-authentication reconnaissance activities against the Microsoft Graph API, specifically the enumeration of directory objects, roles, or service principals. The rule triggers when a user account performs multi-endpoint enumeration via the Graph API within 30 minutes of a successful authentication session initiated via a device code flow that was flagged with elevated risk signals. This behavior is consistent with post-compromise reconnaissance techniques such as 'EvilTokens', where an adversary attempts to map the environment after gaining access.
Detects automated post-compromise mailbox reconnaissance following an anomalous OAuth device code sign-in that exhibits high-risk indicators. The rule identifies programmatic access to a high volume of mail items within a short window following suspicious token issuance, which is characteristic of automated scanning or data exfiltration tooling.
This rule detects a correlation between a successful user login from an IP address not previously seen for that specific user in the last 14 days, followed immediately (within 1 hour) by sensitive administrative operations performed by the same user, such as adding members to roles or modifying application permissions.
Detects potential password spraying activity in Azure Active Directory by identifying a single source IP address that authenticates against multiple distinct user accounts within a short time frame. The rule flags instances where there are numerous authentication attempts across many users, characterized by a low per-user failure count followed by at least one successful authentication, which is indicative of a successful password spray attempt.
Detects potential password spraying activity in Azure Active Directory by identifying a single source IP address that authenticates against multiple distinct user accounts within a short time frame. The rule flags instances where there are numerous authentication attempts across many users, characterized by a low per-user failure count followed by at least one successful authentication, which is indicative of a successful password spray attempt.
Detects a suspicious sequence of events where a user modifies the Entra Authentication Methods Policy to register an external authentication method (EAM) provider, followed immediately by the same user associating a new FIDO key with their account. This behavior can be indicative of an adversary setting up a persistence mechanism via a malicious or unauthorized MFA provider.
Detects the creation of an application registered with a specific Microsoft external authentication provider URI, immediately followed by the configuration of its service principal with reply URLs pointing to external tunneling services like ngrok. This sequence is indicative of an attacker attempting to register a rogue MFA provider to intercept authentication requests.
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 scenarios where a user registers a new WebAuthn/Passkey credential and subsequently performs a sign-in from a different network or device shortly after, preceded by a sign-in from a risky or non-passkey-based method. This pattern is often associated with credential abuse or MFA registration hijacking.
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