Arnold Chan
@slazTrusted contributorCompletionist
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7,555 detections
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Detects the execution of known malicious files associated with the BlueDelta threat group, specifically the HOOKEDGE and HEADLACE malware families, using a curated list of SHA-256 file hashes. Additionally, the rule monitors for the execution of scripts with GUID-based filenames, a common tactic for temporal or staged file deployment.
Detects execution or file presence associated with HOOKEDGE/HEADLACE malware. This rule uses a dual-approach: matching known malicious file hashes (SHA256) and monitoring for specific script files (bat, vbs, cmd) following a GUID-formatted naming convention typically used by the HOOKEDGE installer chain.
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 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 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.
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.
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