Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects potentially unauthorized or anomalous activations of highly privileged Entra ID roles (e.g., Global Administrator). The rule identifies activations that lack a business justification, occur during unusual hours (outside of 06:00-22:00), or exhibit burst patterns of repeated activation/deactivation cycles which may indicate automated credential abuse or persistence attempts.
Detects a suspicious sequence of events where a user performs a device-code authentication followed by a device registration or PRT issuance within a 30-minute window. This behavior is indicative of an adversary using an OAuth device code flow to phish an initial access token, subsequently using it to register an adversary-controlled device for persistent access or to bypass Conditional Access policies.
Detects modifications or additions to Multi-Factor Authentication (MFA) security information for high-value users, specifically targeting those with executive titles (Director, VP, President, etc.). This behavior is frequently associated with account takeover attempts where an attacker registers their own MFA device to a compromised privileged account to maintain persistence.
This rule detects activity associated with the 'Ghostcode' threat campaign by monitoring multiple telemetry sources. It identifies connections to known malicious IP addresses and domains, patterns consistent with phishing kit hosting, and specific URL structures used in credential harvesting or payload delivery. The rule correlates sign-in logs, device network events, DNS queries, and email telemetry to identify potential compromise.
Detects anomalous cloud authentication events occurring within a 3-hour window after suspected unauthorized access to sensitive configuration or credential files on a Vite development server. The rule flags sign-ins with high risk, anomalous location, or missing device compliance information, excluding trusted corporate locations and devices, serving as an indicator of potential post-exfiltration account takeover.
Detects network requests to the Microsoft authentication service specifically targeting the /common/oauth2/deviceauth endpoint, which is used in the OAuth 2.0 Device Authorization Grant flow. While legitimate for device authentication (e.g., CLI tools, smart devices), this flow can be abused by adversaries for phishing attacks to bypass traditional credential-based MFA, allowing them to gain persistent access to a user account once the target authorizes the code.
This rule detects potential API abuse by identifying high-frequency API calls using the 'python-requests' user agent that occur within a short time window (120 seconds) immediately following a successful device code authentication event. This behavior is indicative of automated token theft or session hijacking where an adversary attempts to perform unauthorized actions quickly using tokens obtained via device code phishing.
Detects successful Microsoft Intune enrollment events initiated using the Device Code authentication protocol in Azure AD/Entra ID. This flow is often abused by adversaries to perform OAuth device code phishing, allowing them to gain unauthorized access to cloud resources by tricking users into authorizing a malicious application on their own devices.
Detects an Azure AD Device Code authentication event followed within 60 seconds by a non-interactive Primary Refresh Token (PRT) sign-in event from the same user. This sequence is characteristic of adversary-in-the-middle (AiTM) phishing attacks where a user is tricked into authorizing a device code, and the adversary immediately leverages the resulting session/token to obtain a PRT for persistent access.
This rule detects non-interactive Azure AD sign-in attempts that utilize the device code authentication flow, specifically targeting a Microsoft authentication broker App ID while originating from a Python-requests user agent. This combination is often indicative of automated scripts or malicious tools attempting to bypass standard authentication workflows to gain access to cloud resources.
Detects anomalous device registration behavior where a user account registers multiple unique devices within a very short timeframe (less than 90 seconds). This behavior is characteristic of device code phishing attacks, where an adversary uses automated scripts to rapidly register devices after obtaining authorization codes from victims.
Detects successful device code authentication flows involving applications that are not part of a known list of standard Microsoft and Azure client applications. Device code flows are frequently abused in phishing attacks to bypass traditional credential-based authentication.
Detects successful device code authentication flows involving applications that are not part of a known list of standard Microsoft and Azure client applications. Device code flows are frequently abused in phishing attacks to bypass traditional credential-based authentication.
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 anomalous non-interactive sign-ins that bypass multi-factor authentication (MFA) requirements from a geographical location not previously seen in the user's historical sign-in baseline. This pattern is indicative of attackers using stolen OAuth access or refresh tokens to maintain persistence and bypass standard authentication controls.
Detects anomalous activity associated with OAuth 2.0 device code phishing campaigns. The rule identifies accounts showing frequent device code authentication attempts, including successful logins from potentially unmanaged or unrecognized devices, which is consistent with the behavior of phishing kits targeting OAuth device grant flows.
Detects high-volume, systematic API requests to AI inference endpoints from a single user ID, which may indicate automated model extraction or scraping attacks against AI services.
Detects a pattern where a single source IP address performs multiple successful authentications across different cloud account identifiers within a short timeframe. This behavior is indicative of automated credential spraying, multi-agent automated access, or potential account takeover activity targeting multiple accounts within a cloud environment.
Detects instances where a user account experiences multiple failed sign-in attempts followed by a successful sign-in from a different, geographically distant location within a short timeframe, indicating impossible travel and potential credential compromise.
Detects activity associated with the 'BlueKit' session relay tool, which uses the rrweb library to capture and replay user session interactions. This rule identifies web browser network events involving rrweb-related scripts occurring within 10 minutes of a successful user sign-in, indicating a potential Adversary-in-the-Middle (AiTM) phishing attack where credentials and session cookies are being captured.
Detects activity associated with the 'BlueKit' session relay tool, which uses the rrweb library to capture and replay user session interactions. This rule identifies web browser network events involving rrweb-related scripts occurring within 10 minutes of a successful user sign-in, indicating a potential Adversary-in-the-Middle (AiTM) phishing attack where credentials and session cookies are being captured.
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