Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This KQL inventories activity associated with a specified root domain and its subdomains across DeviceNetworkEvents, EmailUrlInfo, CloudAppEvents.
This rule detects administrative changes to domain federation settings or domain authentication configurations within an Azure Active Directory (Microsoft Entra ID) environment. These modifications can be used to establish persistence or facilitate identity-based attacks, such as domain-wide impersonation, by altering how identities are authenticated.
No description available.
This rule monitors for successful sign-ins to sensitive cloud resources (such as Microsoft Authentication Broker, Office 365 Exchange Online, or Graph API) that originate from IP addresses not observed in the user's recent history (14-day baseline) or from known datacenter/hosting network ranges. The rule also filters for common scripted User-Agent strings (e.g., Python requests, curl) or empty User-Agent strings to increase the likelihood of detecting programmatic or malicious automated access rather than standard browser-based user activity.
Detects anomalous, non-interactive sign-in activity in Microsoft 365 that suggests session cookie replay (Pass-the-Cookie). The rule correlates successful, MFA-validated interactive sign-ins against subsequent, non-interactive sign-ins that lack MFA, occur from a different device and IP address within a short time window, and bypass standard interactive re-authentication.
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 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.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
Detects a suspicious sequence of events where a user's password is changed or reset by an administrator (or help-desk role) followed within a short time window by that same user registering a new MFA device, potentially indicating a vishing-based account takeover attack (e.g., PREY-0058/UNC6671).
This rule detects rapid enumeration of Azure AD identity and configuration components by identifying a burst of specific, high-level administrative API calls (Get user flows, Get API connectors, Get identity providers, Get user attributes) within a short window. This pattern is indicative of reconnaissance activities aimed at mapping out the identity provider configuration.
This rule detects user authentication events that deviate significantly from a 14-day historical baseline of known devices, operating systems, browsers, and network locations (ASN). It flags logins where at least two out of four key metadata signals (DeviceId, OS, Browser, ASN) have changed compared to the user's historical pattern, specifically targeting successful authentications that did not trigger a fresh multi-factor authentication (MFA) challenge, potentially indicating token theft or unauthorized session reuse.
Detects anomalous, non-interactive sign-in activity in Microsoft 365 that suggests session cookie replay (Pass-the-Cookie). The rule correlates successful, MFA-validated interactive sign-ins against subsequent, non-interactive sign-ins that lack MFA, occur from a different device and IP address within a short time window, and bypass standard interactive re-authentication.
Detects high-frequency, automated requests to product and catalog pages within a short time window, characteristic of web scraping or catalog harvesting often used to feed fake-shop networks or build clone sites.
This rule detects potential Server-Side Request Forgery (SSRF) activity where web application or runtime processes attempt to access the Cloud Instance Metadata Service (IMDS) or container task metadata endpoints. By monitoring network connections and application logs, the rule filters out known legitimate metadata clients and identifies suspicious processes frequently associated with web-based vulnerabilities that are repeatedly querying sensitive metadata paths.
Detects high-volume image pull activity against an Azure Container Registry from a single identity, which may indicate reconnaissance or mass harvesting of container images to extract embedded credentials, secrets, or source code.
Detects anomalous certificate-based authentication attempts to Jasmine network services characterized by rapid, impossible-travel scenarios or geo-inconsistent session patterns. This behavior is indicative of a stolen certificate being reused from a different geographic location or network, bypassing standard authentication patterns.
Detects anomalous certificate-based authentication attempts to Jasmine network services characterized by rapid, impossible-travel scenarios or geo-inconsistent session patterns. This behavior is indicative of a stolen certificate being reused from a different geographic location or network, bypassing standard authentication patterns.
Detects anomalous certificate-based authentication attempts to Jasmine network services characterized by rapid, impossible-travel scenarios or geo-inconsistent session patterns. This behavior is indicative of a stolen certificate being reused from a different geographic location or network, bypassing standard authentication patterns.
This rule detects potential exploitation attempts (CVE-2026-59822) against LiteLLM MCP tool endpoints. It identifies HTTP requests where the authorization bearer token is unusually short (<= 12 chars), lacks the 'sk-' prefix, and does not appear to be a valid JWT, yet successfully results in a 200 OK status, indicating a potential bypass of authentication logic.
This rule detects attempts to exploit the LiteLLM proxy pass-through endpoint to interact with the cloud Instance Metadata Service (IMDS). Specifically, it identifies configuration attempts to route traffic to the IMDS IP (169.254.169.254) and subsequent requests to retrieve IAM security credentials, which is indicative of a Server-Side Request Forgery (SSRF) attack to steal cloud identity tokens.
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