Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
707 detections
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Detects the use of the default, hardcoded 'sk-1234' secret key for HS256 JWT signing in LiteLLM proxy logs. This configuration is insecure and allows for the forgery of arbitrary user session tokens.
Detects unreviewed commits to .gitlab-ci.yml that alter how the gitlab-triage tool invokes the sensitive API_TOKEN variable, with no associated merge request.
Detects GitLab CI job shell commands that redirect the environment to a .tmp file, a pattern identified in the GnuTLS GitLab token leak.
Detects GitLab CI job shell commands that redirect the environment to a .tmp file, a pattern identified in the GnuTLS GitLab token leak.
Detects processes attempting to access sensitive Linux system files (/etc/passwd or /etc/shadow) that are not typically associated with system administration, security, or identity management tasks. This behavior may indicate an attempt by an unauthorized user or process to gather credentials or system configuration information.
Detects anomalous authentication attempts where a single source IP validates a high volume of distinct Service Principal or App Client IDs within a short timeframe with a high failure rate. This pattern is indicative of attackers performing bulk validation of stolen API keys or OAuth credentials, likely harvested through mobile application decompilation (APK/IPA analysis).
Detects anomalous authentication attempts where a single source IP validates a high volume of distinct Service Principal or App Client IDs within a short timeframe with a high failure rate. This pattern is indicative of attackers performing bulk validation of stolen API keys or OAuth credentials, likely harvested through mobile application decompilation (APK/IPA analysis).
Detects node.js or bun runtime processes accessing known sensitive cloud, CI, and package manager credential files on disk. This behavior is indicative of malicious npm supply chain attacks (e.g., Mini Shai-Hulud) attempting to exfiltrate secrets stored in standard configuration paths.
Detects suspicious execution of system commands (curl, wget, python, bash, etc.) by AI/ML-related server processes like LiteLLM, RAGFlow, or Kestra. The detection looks for command-line arguments that may indicate credential harvesting, such as attempts to access environment variables, sensitive database configuration files, or the use of encoded data/network retrieval tools.
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 unreviewed commits to .gitlab-ci.yml that alter how the gitlab-triage tool invokes the sensitive API_TOKEN variable, with no associated merge request.
Detects package manager processes (npm, pip, python) executing install-related commands followed by the creation or modification of sensitive files (SSH keys, cloud credentials, shell configurations) within a short timeframe. This behavior is indicative of potential supply chain attacks where a malicious package attempts to steal credentials or secrets upon installation.
Detects access to sensitive credential stores (KeePass databases, Firefox logins, SSH keys, VPN configuration files) by suspicious processes, specifically those associated with potential credential harvesting tools or unauthorized update binaries.
Detects access to sensitive credential stores (KeePass databases, Firefox logins, SSH keys, VPN configuration files) by suspicious processes, specifically those associated with potential credential harvesting tools or unauthorized update binaries.
Detects CI/CD job activity referencing shell commands that redirect the entire environment to a file (e.g. 'env > out.tmp'), the exact pattern that caused a GitLab CI job in the openconnect/ocserv project to dump secrets into a public build artifact, leaking a high-privilege personal access token with Owner access to GnuTLS and 55 other critical projects.
Detects processes other than the official Telegram desktop client accessing sensitive local data files ('key_datas', 'settingss', 'usertag') within the Telegram application directory. This activity is often associated with credential theft or session hijacking.
Detects unauthorized processes accessing sensitive web browser files (login data, cookies, local state) from suspicious or non-standard paths. This is a common behavioral pattern for infostealers attempting to exfiltrate user credentials and browser session tokens.
Detects high-volume image pull activity against an Azure Container Registry from a single identity, which may indicate reconnaissance or mass harvesting of container images to extract embedded credentials, secrets, or source code.
Detects high-frequency requests to the RubyGems legacy API key endpoint, which may indicate attempts to harvest or bruteforce developer API keys. The rule specifically monitors for request patterns involving variations like .yaml, .json, or parameter-based variants often observed in scanning activities.
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