Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Device code authentication flow completed, followed by subsequent session activity from a different IP/user-agent, indicating token replay to an attacker-controlled client that bypasses MFA
Detects anomalous authentication behavior where a single session identifier is used to access three or more distinct SaaS applications within a one-hour window. This behavior often indicates the unauthorized use of a stolen session cookie or OAuth token (Pass-the-Cookie) across multiple SSO-integrated platforms.
This rule detects the reuse of the same user's refresh token from two different countries within a 15-minute window. This behavior is a strong indicator of token theft or session hijacking, commonly associated with AiTM phishing, infostealer malware, or session cookie extraction, where an adversary uses stolen credentials from a remote location.
Detects anomalous use of an AI agent session or OAuth token from multiple distinct IP addresses, hostnames, or user-agents within a short 10-minute window. This behavior is highly indicative of token theft and replay, where an adversary attempts to use a compromised session token from a different location or environment.
Detects user authentication events where the MFA redirect URL points to an unrecognized or potentially malicious domain. This behavior is indicative of an Adversary-in-the-Middle (AiTM) attack, such as the TrustSink credential capture technique, where the user is diverted from the legitimate identity provider to an attacker-controlled OIDC endpoint to capture credentials or session tokens.
This rule detects the reuse of the same user's refresh token from two different countries within a 15-minute window. This behavior is a strong indicator of token theft or session hijacking, commonly associated with AiTM phishing, infostealer malware, or session cookie extraction, where an adversary uses stolen credentials from a remote location.
Detects anomalous authentication behavior where a single session identifier is used to access three or more distinct SaaS applications within a one-hour window. This behavior often indicates the unauthorized use of a stolen session cookie or OAuth token (Pass-the-Cookie) across multiple SSO-integrated platforms.
Detects OAuth application consent grant events where an application name matches common 'Data Loader' naming conventions and requests high-privilege scopes (read/write/full/api). This pattern is consistent with consent phishing campaigns used by threat actors to gain persistent access to SaaS environments like M365 or Salesforce.
Detects unauthorized access to CRM platforms (Salesforce) using Salesloft or Drift OAuth tokens, where the source IP address does not match the known legitimate service provider IP ranges. This behavior is indicative of potential token theft or misuse, particularly relevant to supply-chain campaign activities.
Detects a pattern associated with ShinyHunters/UNC6040, where a user authorizes a new or rarely-used OAuth connected application shortly after performing a help-desk initiated password reset or MFA re-enrollment, originating from a different geographic location.
Detects OAuth application consent requests that combine broad API access scopes with persistence-enabling scopes (e.g., offline_access or refresh_token). This pattern is consistent with OAuth consent phishing attacks, where adversaries attempt to gain non-interactive, long-term access to an organization's cloud environment via malicious connected applications.
Detects the granting of highly privileged OAuth or API scopes to AI-related applications (such as Copilot plugins, browser-automation agents, or AI connectors) immediately followed by high-volume data access activities (file reads or email transfers) performed by the same user account. This behavior is indicative of an attacker weaponizing a compromised identity to grant an external AI agent broad access to sensitive data for exfiltration or automated reconnaissance.
Detects the granting of highly privileged OAuth or API scopes to AI-related applications (such as Copilot plugins, browser-automation agents, or AI connectors) immediately followed by high-volume data access activities (file reads or email transfers) performed by the same user account. This behavior is indicative of an attacker weaponizing a compromised identity to grant an external AI agent broad access to sensitive data for exfiltration or automated reconnaissance.
Detects the granting of highly privileged OAuth or API scopes to AI-related applications (such as Copilot plugins, browser-automation agents, or AI connectors) immediately followed by high-volume data access activities (file reads or email transfers) performed by the same user account. This behavior is indicative of an attacker weaponizing a compromised identity to grant an external AI agent broad access to sensitive data for exfiltration or automated reconnaissance.
This rule detects potential identity compromise via abuse of the OAuth device-code grant flow. It monitors for successful user logins leveraging the device code flow, which is a common indicator of AiTM (Adversary-in-the-Middle) phishing campaigns that lure users into authorizing malicious applications under pretexts like security updates or SSO re-authentication.
This rule detects potential identity compromise via abuse of the OAuth device-code grant flow. It monitors for successful user logins leveraging the device code flow, which is a common indicator of AiTM (Adversary-in-the-Middle) phishing campaigns that lure users into authorizing malicious applications under pretexts like security updates or SSO re-authentication.
This rule detects potential identity compromise via abuse of the OAuth device-code grant flow. It monitors for successful user logins leveraging the device code flow, which is a common indicator of AiTM (Adversary-in-the-Middle) phishing campaigns that lure users into authorizing malicious applications under pretexts like security updates or SSO re-authentication.
Detects high-frequency Resource Owner Password Credentials (ROPC) authentication requests targeting the OAuth token endpoint. Attackers use ROPC for brute-forcing, credential stuffing, or bypassing security controls by directly passing user credentials to the OAuth flow.
Detects an account granting offline access, mail, files, directory, or user impersonation permissions shortly after anomalous authentication. This rule is designed to identify potential persistence mechanisms established by adversaries leveraging OAuth applications, as seen in campaigns like Tycoon 2FA AITM.
Detects stolen session token reuse to bypass MFA by correlating a successful SSO/VPN login from one IP with a subsequent successful login from a different IP using the same user agent context, or a user-agent change between sessions for the same user within a short window. Targets access broker technique where infostealer-harvested session cookies are replayed from different source IPs.
Detects stolen session token reuse to bypass MFA by correlating a successful SSO/VPN login from one IP with a subsequent successful login from a different IP using the same user agent context, or a user-agent change between sessions for the same user within a short window. Targets access broker technique where infostealer-harvested session cookies are replayed from different source IPs.
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