Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects OAuth 2.0 device authorization grant requests utilizing the Microsoft Authentication Broker application ID (29d9ed98-a469-4536-ade2-f981bc1d605e) with sensitive scopes like 'https://graph.microsoft.com/.default'. This specific application ID is frequently impersonated by phishing kits (e.g., GhostCode) to facilitate token theft via device code flow abuse, where adversaries trick users into authenticating to a legitimate-looking but attacker-controlled flow.
Detects login attempts to source code repositories and developer tooling (GitHub, GitLab, Bitbucket, Azure DevOps, Slack, Visual Studio Code) originating from unmanaged or non-compliant devices, excluding traffic originating from known corporate network ranges.
Detects pull requests created in GitHub repositories by entities labeled as 'Bot', 'App', or 'integration', or containing the term 'codex', specifically targeting repositories where such entities have not performed these actions in the previous 30 days. This baseline approach identifies potentially hijacked or unauthorized automation accounts performing activities outside of their standard repository scope.
Detects pull requests created in GitHub repositories by entities labeled as 'Bot', 'App', or 'integration', or containing the term 'codex', specifically targeting repositories where such entities have not performed these actions in the previous 30 days. This baseline approach identifies potentially hijacked or unauthorized automation accounts performing activities outside of their standard repository scope.
Detects instances where a user grants OAuth application permissions to GitHub or Slack shortly (within 30 minutes) after signing into a low-trust application (Discourse or OpenAI Community), suggesting a potential session hijacking or trusted-relationship abuse scenario where an attacker leverages an existing SSO session to authorize malicious applications.
This rule detects a user account performing its first-ever GitHub OAuth or repository access within a short timeframe (30 minutes) after authenticating to a designated low-trust OpenAI community forum. This pattern is designed to identify potential adversary activity where a compromised or newly created account is used to pivot from a low-trust environment to corporate repository access.
This rule detects a user account performing its first-ever GitHub OAuth or repository access within a short timeframe (30 minutes) after authenticating to a designated low-trust OpenAI community forum. This pattern is designed to identify potential adversary activity where a compromised or newly created account is used to pivot from a low-trust environment to corporate repository access.
This rule detects potential reconnaissance activity against Microsoft Graph API endpoints, indicative of an adversary enumerating tenant resources such as users, groups, applications, and directory roles. It monitors for high volumes of diverse Graph API queries originating from a single user or application identity within a short time window, which is a common behavior pattern for automated discovery tools.
This rule monitors cloud and identity logs to detect a single user identity exhibiting multiple stages of suspicious activity (authentication, reconnaissance, and exfiltration) within a 24-hour period while utilizing distinct, non-overlapping source IP addresses for each stage. This behavior is indicative of an account compromise where different stages of the attack chain originate from different infrastructure.
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.
Detects GitHub repository actions (git.clone, oauth_authorization.create, repo.download_zip) from actor IPs not seen for that user in the prior 30 days, requiring either 3+ actions or activity across 2+ distinct repositories from the new IP within the same day. Aggregating to burst/multi-repo behavior (rather than alerting on a single new-IP event) filters out one-off false positives from travel, VPNs, or dynamic IP reassignment while still surfacing sustained anomalous access patterns consistent with account compromise or bulk exfiltration.
Detects anomalous, high-volume mailbox access across multiple distinct Exchange Online mailboxes within a short timeframe (1 hour) initiated by a single user account. This behavior is indicative of automated email reconnaissance, content scraping, or bulk exfiltration, often associated with post-credential compromise activity where an attacker iterates through mailboxes to identify sensitive information such as financial or administrative data.
Detects high-volume, automated Pix transfer transactions within a short timeframe from a single source or session, which may indicate unauthorized use of a 'Pix' panel or automated financial fraud.
Detects the creation and immediate deletion of a GitHub OAuth token that is used to clone or fetch a large volume of private repositories within a short lifespan. This behavior is indicative of an adversary using a temporary, ephemeral token to perform rapid data exfiltration or mass reconnaissance on source code repositories.
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.
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 a burst of new user account creation activity on a self-hosted git repository instance. This pattern is indicative of unauthorized mass account creation, potentially following an initial compromise or exploitation, which is often a precursor to further malicious activities like persistent access or unauthorized code access.
Detects a burst of new user account creation activity on a self-hosted git repository instance. This pattern is indicative of unauthorized mass account creation, potentially following an initial compromise or exploitation, which is often a precursor to further malicious activities like persistent access or unauthorized code access.
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