Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects HTTP requests to the Microsoft device login endpoint (/devicelogin) that originate from a non-Microsoft referrer domain. This behavior is highly indicative of Adversary-in-the-Middle (AiTM) phishing attacks targeting OAuth device code flows, where a malicious proxy site redirects users to the legitimate Microsoft login page while attempting to capture session tokens.
Detects anomalous high-volume file access or download activity in Microsoft 365 (SharePoint or OneDrive) by a single user within a 15-minute window, which may indicate bulk data exfiltration.
Detects anomalous high-volume file access or download activity in Microsoft 365 (SharePoint or OneDrive) by a single user within a 15-minute window, which may indicate bulk data exfiltration.
Detects spoofed emails carrying a .patch attachment sent to a GitLab incoming-email merge-request address. Requires Microsoft's composite authentication verdict (CompAuth: fail) -- a lower-noise spoofing signal than raw SPF/DKIM/DMARC -- and excludes sender/recipient pairs already seen corresponding with that token address in the prior 30 days to suppress recurring legitimate contributors.
Detects spoofed emails carrying a .patch attachment sent to a GitLab incoming-email merge-request address. Requires Microsoft's composite authentication verdict (CompAuth: fail) -- a lower-noise spoofing signal than raw SPF/DKIM/DMARC -- and excludes sender/recipient pairs already seen corresponding with that token address in the prior 30 days to suppress recurring legitimate contributors.
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.
This rule identifies successful user sign-ins (ResultType 0) originating from specific Autonomous System Numbers (197540, 216154) where Multi-Factor Authentication (MFA) was not required or not recorded, and where Conditional Access policies either did not apply or succeeded without enforcing MFA.
Detects phishing emails impersonating 'Veltrix Capital' that lure developers into running, debugging, or cloning repositories, often disguised as technical assessment or job-related tasks involving cryptocurrency or blockchain themes.
Detects repeated HTTP POST requests containing 'ScreenConnect' in the URI, originating from external networks. This pattern is indicative of automated scanning activity attempting to exploit potential authentication bypass or session hijacking vulnerabilities (such as CVE-2026-84869) in ConnectWise ScreenConnect instances.
Detects anomalous authentication or API access patterns where a single user account interacts with both Salesforce and ServiceNow environments simultaneously from multiple distinct source IP addresses. This behavior is indicative of credential abuse or account takeovers consistent with multi-platform SaaS targeting.
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-frequency HTTP requests to the Dahua easy4ipcloud.com password recovery endpoint. The rule monitors for abnormal volumes of reset requests from a single IP address, which is indicative of an attacker attempting to use offline-generated recovery codes to bypass authentication on Dahua IoT devices.
This rule detects email or web proxy traffic containing a lure themed around 'Confluence', combined with a redirect or link to Telegram, and specifically containing Cyrillic character sets. This combination is often indicative of targeted phishing campaigns using social engineering lures to redirect users to external messaging platforms for further interaction or credential harvesting.
Detects a suspicious correlation between the registration of new authentication methods or application integrations and the subsequent modification of Conditional Access policies within a 2-hour window. This behavior is indicative of the activation phase of a TrustSink attack, where an adversary sets up a malicious MFA provider and forces its use by expanding Conditional Access policy scope.
Detects a suspicious correlation between the registration of new authentication methods or application integrations and the subsequent modification of Conditional Access policies within a 2-hour window. This behavior is indicative of the activation phase of a TrustSink attack, where an adversary sets up a malicious MFA provider and forces its use by expanding Conditional Access policy scope.
Detects signs of the TrustSink technique where an Entra sign-in process, while at the MFA stage, is intercepted by redirecting the user to a rogue External Authentication Method (EAM) provider. This unauthorized provider typically uses look-alike domains or tunneling services to host phishing pages that harvest plaintext credentials and return forged MFA tokens to Entra.
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