Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
771 detections
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Detects user-granted OAuth consent in Microsoft Entra ID (formerly Azure AD) involving high-risk scopes such as Mail.Read, Files.ReadWrite.All, or offline_access. This pattern is characteristic of illicit consent-grant phishing, where attackers entice users to authorize malicious applications to bypass multi-factor authentication (MFA) and establish persistent, programmatic access to sensitive mailbox and file resources.
Detects AI coding assistants and LLM agent frameworks attempting to access, read, or export sensitive credential files, registry hives, or application secrets. The rule monitors both file system operations on known secret locations and process execution patterns indicative of credential dumping or API token retrieval by these tools.
Detects the use of common command-line tools (curl, wget, python, etc.) to interact with known cloud provider metadata service IP addresses or URL paths, often performed by shell processes. This behavior is frequently associated with initial reconnaissance or attempts to steal identity tokens from cloud-based virtual machines.
Detects sign-in activity using the OAuth 2.0 device code flow, followed by subsequent authentication attempts from the same account originating from anomalous, previously unseen geographic locations or using unfamiliar applications. This pattern is indicative of a device code phishing attack where an adversary lures a user into authorizing a malicious device or application and subsequently hijacks the resulting session to access resources from a different location.
Detects endpoint DNS resolution for the 'mysignins.microsoft.com' domain. This domain is frequently used in Adversary-in-the-Middle (AiTM) phishing attacks to facilitate user interaction with legitimate Microsoft portals while the attacker intercepts session tokens.
This rule detects potential OAuth token theft resulting from device code phishing (e.g., N0va phishkit). It monitors for a successful OAuth device-code authentication followed within 5 minutes by a secondary successful sign-in for the same user from a different IP address, different browser client, or different user agent, which is a common indicator of an adversary-in-the-middle (AiTM) session hijacking attempt.
Detects phishing emails containing lures that direct users to the Microsoft device login portal to enter an attacker-supplied code. The rule correlates the delivery of these emails with subsequent successful device-code based authentication events, identifying potential token theft via the OAuth device code flow.
Detects the granting of OAuth application permissions, specifically targeting applications with names containing terms like 'ai', 'copilot', or 'chatbot'. The rule looks for high-privilege scopes such as Mail, Files, or Directory access, which are common indicators of consent phishing or the use of malicious AI-branded applications to gain persistent access to sensitive data in the M365 environment.
Detects non-interactive sign-in events to common Microsoft 365 applications (OfficeHome, Outlook, My Sign-Ins, My Profile) where the User-Agent identifies as an automated HTTP client library (Axios or Python-requests). This behavior is often indicative of programmatic access via stolen session cookies or application tokens, commonly seen in adversary activity such as payroll-related business email compromise.
Detects anomalous Microsoft 365 session behavior where a single SessionId persists across multiple sign-ins that originate from rotating IP addresses and ASNs. The detection identifies signs of potential session token theft, specifically looking for traffic matching the Microsoft Outlook client app signature paired with non-standard user agents (e.g., Firefox or Python requests) that exhibit recurring sign-in attempts at approximately 8-hour intervals, which is typical for automated token refresh cycles.
Detects anomalous sign-in attempts to the OfficeHome application where an OAuth 90014 error (nonce mismatch/invalid) is returned. The detection specifically monitors for requests originating from mobile browsers on Windows 10 user agents, which is indicative of potential adversary-in-the-middle (AiTM) phishing activity attempting to bypass or intercept authentication tokens.
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 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 potentially malicious OAuth device code sign-ins by identifying sign-in events that exhibit anomalous characteristics, such as atypical geographic locations, rare client-application combinations, unmanaged/noncompliant device status, or elevated risk signals associated with the account. This detection helps identify account compromise or malicious OAuth consent activity often associated with 'EvilTokens' or device-code phishing attacks.
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 potential abuse of stolen OAuth session tokens, where refresh tokens are used to authenticate after a user has performed a password reset. This rule identifies accounts that continue to sign in from previously unseen devices or IP addresses within 24 hours post-password reset, a technique consistent with session persistence mechanisms used by adversary tools and platforms like EvilTokens.
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects anomalous outbound email activity from an account that recently performed an OAuth device code sign-in characterized by elevated risk levels. The rule identifies potential token abuse by looking for a high volume of emails with either a significant percentage of external recipients or patterns indicative of bulk mailing, common in phishing campaigns that leverage compromised identities (e.g., EvilTokens).
Detects anomalous network polling patterns consistent with 'EvilTokens' or similar adversary-in-the-middle (AiTM) OAuth phishing kits. The rule identifies web browsers performing high-frequency, low-interval polling (3-6s) against non-reputable/unseen domains (the attacker-controlled status endpoint) immediately preceding or following successful Microsoft OAuth device-code authentication sequences.
Detects anomalous network polling patterns consistent with 'EvilTokens' or similar adversary-in-the-middle (AiTM) OAuth phishing kits. The rule identifies web browsers performing high-frequency, low-interval polling (3-6s) against non-reputable/unseen domains (the attacker-controlled status endpoint) immediately preceding or following successful Microsoft OAuth device-code authentication sequences.
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