Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
461 detections
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Detects potential cross-application SSO session or token reuse by identifying users transitioning from a low-trust application (forum) to a high-trust application (ChatGPT/Codex) within a short window (15 minutes), especially when the sign-in is non-interactive (lacking MFA) or occurs from a different IP address or user agent, suggesting a possible token replay attack.
Detects potential cross-application SSO session or token reuse by identifying users transitioning from a low-trust application (forum) to a high-trust application (ChatGPT/Codex) within a short window (15 minutes), especially when the sign-in is non-interactive (lacking MFA) or occurs from a different IP address or user agent, suggesting a possible token replay attack.
Detects GitHub OAuth authorization, repository cloning, or ZIP downloads from source IP addresses that have not been observed for the specific actor within the past 30 days. This rule helps identify potential account compromise or token theft where an attacker attempts to access repository data from a new location, while specifically excluding bot/service accounts known for rotating CI infrastructure IPs.
Detects GitHub OAuth authorization, repository cloning, or ZIP downloads from source IP addresses that have not been observed for the specific actor within the past 30 days. This rule helps identify potential account compromise or token theft where an attacker attempts to access repository data from a new location, while specifically excluding bot/service accounts known for rotating CI infrastructure IPs.
This rule detects unauthorized GitHub repository access or OAuth activity performed by a user account identified as terminated in the organization's HR system. It uses a watchlist to cross-reference GitHub audit logs against terminated employee records, applying a 2-hour grace period to account for potential log synchronization delays or final offboarding tasks.
This rule detects unauthorized GitHub repository access or OAuth activity performed by a user account identified as terminated in the organization's HR system. It uses a watchlist to cross-reference GitHub audit logs against terminated employee records, applying a 2-hour grace period to account for potential log synchronization delays or final offboarding tasks.
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 potential N0va-style phishing or token-exchange abuse where a user completes a device-code authentication flow, followed immediately by an access token usage from a different IP address or device. This sequence indicates an adversary has captured the resulting token/session and is attempting to bypass multi-factor authentication (MFA) to gain unauthorized access to cloud resources.
Detects potential N0va-style phishing or token-exchange abuse where a user completes a device-code authentication flow, followed immediately by an access token usage from a different IP address or device. This sequence indicates an adversary has captured the resulting token/session and is attempting to bypass multi-factor authentication (MFA) to gain unauthorized access to cloud resources.
Detects anomalous access to WSO2 API Manager Store and Publisher endpoints involving the retrieval of sensitive information like consumer keys and secrets. The rule specifically targets requests authenticated with JWTs that exhibit headers indicative of 'alg=none' or other unsupported/forged algorithm patterns, often associated with CVE-2026-5430 exploitation attempts. The rule uses statistical baseline monitoring to identify volume spikes in requests to these sensitive paths.
Detects evidence of an Adversary-in-the-Middle (AiTM) phishing attack where a user sign-in results in specific error codes (50074: MFA required; 50140: Keep-me-signed-in interrupted), followed by rapid enumeration of key M365 applications (OfficeHome, My Apps, My SignIns) using the same session/user-agent, signifying post-authentication reconnaissance via stolen tokens.
This rule monitors Azure AD Sign-in logs to identify 'impossible travel' scenarios, where a user authenticates successfully from two geographically distant locations within a time window (1 hour) that would require travel speeds exceeding a plausible threshold. This behavior is a common indicator of credential compromise or session token replay attacks.
Detects OAuth2 JWT bearer-grant token requests to Google's OAuth endpoint using the attacker-controlled service-account identity and Sheets API scope observed in the fake GlobalProtect campaign
Detects anomalous sign-in behavior where a device code authentication flow is initiated from one location, but the resulting session is replayed from a different IP address in a different country within a one-hour window. This behavior is indicative of an adversary capturing an authentication token via a device code phishing or relay attack and attempting to use it from their own infrastructure to bypass conditional access policies and MFA.
Detects a suspicious sequence of events within JFrog Artifactory where an account accesses sensitive code-signing material (rubygems/gemspec/signing keys) and subsequently performs administrative actions (user addition/role assignment/privilege escalation) within a one-hour window, indicating potential account takeover or exploitation.
Detects a suspicious sequence of events within JFrog Artifactory where an account accesses sensitive code-signing material (rubygems/gemspec/signing keys) and subsequently performs administrative actions (user addition/role assignment/privilege escalation) within a one-hour window, indicating potential account takeover or exploitation.
Detects login events to the 'My Sign-Ins' portal (mysignins.microsoft.com) by users. This portal is a high-value target for adversaries who have gained access to a session via token theft or session hijacking, as it allows them to modify or add authentication methods (such as MFA devices) to establish long-term persistence in the victim's account.
Detects the use of the OAuth device code authentication flow in Azure AD/Entra ID sign-in events. This flow is frequently abused by attackers who use vishing or SMS phishing pretexts to trick users into authorizing a device login, enabling the attacker to obtain a valid session token without direct credential harvesting or cookie theft.
Detects anomalous authentication behavior where a user successfully completes an OAuth device-code grant, followed by a subsequent login event using the same user context but originating from a different source IP address. This pattern is indicative of device-code phishing, where an adversary tricks a user into authorizing a device, then uses the resulting session or token from their own infrastructure.
Detects anomalous authentication behavior where a user successfully completes an OAuth device-code grant, followed by a subsequent login event using the same user context but originating from a different source IP address. This pattern is indicative of device-code phishing, where an adversary tricks a user into authorizing a device, then uses the resulting session or token from their own infrastructure.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
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