Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
191 detections
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Detects high-frequency S3 object upload activity (PutObject/CompleteMultipartUpload) originating from the Rclone tool, a common indicator of potential data exfiltration to cloud storage.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects high-frequency S3 object upload activity (PutObject/CompleteMultipartUpload) originating from the Rclone tool, a common indicator of potential data exfiltration to cloud storage.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects the publication or upload of RubyGems packages containing embedded Server-Side Template Injection (SSTI) payloads within their author metadata, specifically targeting common testing strings like '<%= 7*7 %>'. This behavior is indicative of supply chain testing or potential exploitation attempts against package registry infrastructure or downstream consumers.
Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects anomalous activity by newly added guest users in Microsoft Teams, specifically identifying when a guest user account is added and subsequently performs multiple file-related operations (upload, download, access) or message-sending activities within a short timeframe. This behavior can be indicative of external threat actors or compromised guest accounts exfiltrating or accessing sensitive information within a Teams workspace.
Detects the creation of a new AWS S3 bucket followed by a large volume of data uploads (more than 200 objects) within a 2-hour window. The detection focuses on activity attributed to a single identity with limited source IP diversity, which is highly indicative of scripted data staging and potential exfiltration preparation by an unauthorized actor.
Detects high-frequency S3 object upload activity (PutObject/CompleteMultipartUpload) originating from the Rclone tool, a common indicator of potential data exfiltration to cloud storage.
Detects GitLab CI/CD pipeline configuration (.gitlab-ci.yml) that sets job artifacts to 'untracked: true' with 'when: always', which publishes every untracked file as a downloadable CI artifact -- the exact misconfiguration that exposed the leaked GitLab token in the GnuTLS incident.
Detects an attempt to exploit CVE-2026-14894 within the Super Forms plugin by sending a crafted HTTP POST request to admin-ajax.php. The attack attempts to upload an obfuscated PHP web shell disguised as a base64-encoded GIF image.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
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