Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
707 detections
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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 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 commandline keywords indicative of potential usge of the tool WinPwn. A tool for Windows and Active Directory reconnaissance and exploitation.
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.
This rule detects file access, creation, modification, or renaming operations involving sensitive files associated with cryptocurrency wallets (Bitcoin, Electrum, ElectrumSV), game account configurations (Battle.net, Steam, Minecraft), and browser-based cookies (Roblox). The rule filters out legitimate process interactions, identifying suspicious activity from unknown or unauthorized applications potentially attempting to exfiltrate credentials or session tokens.
This rule detects file access, creation, modification, or renaming operations involving sensitive files associated with cryptocurrency wallets (Bitcoin, Electrum, ElectrumSV), game account configurations (Battle.net, Steam, Minecraft), and browser-based cookies (Roblox). The rule filters out legitimate process interactions, identifying suspicious activity from unknown or unauthorized applications potentially attempting to exfiltrate credentials or session tokens.
Detects the sensitive project-wide CI/CD variable API_TOKEN being exposed to job scopes other than the gitlab-triage automation job that is its only intended consumer, expanding the blast radius of the credential.
Detects the sensitive project-wide CI/CD variable API_TOKEN being exposed to job scopes other than the gitlab-triage automation job that is its only intended consumer, expanding the blast radius of the credential.
Detects the sensitive project-wide CI/CD variable API_TOKEN being exposed to job scopes other than the gitlab-triage automation job that is its only intended consumer, expanding the blast radius of the credential.
Detects GitLab CI job shell commands that redirect the environment to a .tmp file, a pattern identified in the GnuTLS GitLab token leak.
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 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.
This rule detects file access, creation, modification, or renaming operations involving sensitive files associated with cryptocurrency wallets (Bitcoin, Electrum, ElectrumSV), game account configurations (Battle.net, Steam, Minecraft), and browser-based cookies (Roblox). The rule filters out legitimate process interactions, identifying suspicious activity from unknown or unauthorized applications potentially attempting to exfiltrate credentials or session tokens.
This rule detects unauthorized or suspicious access to sensitive configuration and credential files (e.g., .aws, .azure, .ssh) by specific DLP (Data Loss Prevention) or automation scripts, and identifies subsequent attempts to expose environment variables or sensitive tokens within process command lines.
This rule detects unauthorized or suspicious access to sensitive configuration and credential files (e.g., .aws, .azure, .ssh) by specific DLP (Data Loss Prevention) or automation scripts, and identifies subsequent attempts to expose environment variables or sensitive tokens within process command lines.
Detects the use of the 'netsh wlan show profile' command with the 'key=clear' argument, which is used to display the plaintext passwords of stored WiFi profiles on a Windows system.
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 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 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 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 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.
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