Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects instances where AI coding assistants (e.g., Cursor, Claude, Copilot) are observed interacting with specific configuration or sensitive files and subsequently initiating suspicious shell commands. The rule correlates file read activity (containing keywords like 'skill', 'preflight', '.ssh', or '.aws') followed closely by execution of potentially malicious commands like 'whoami /priv', credential decoding, or registry exploration, indicating potential abuse of the assistant's context.
This rule detects the execution of scripts or processes containing command-line arguments indicative of a cryptocurrency wallet drainer (e.g., 'DRAIN', 'DRAIN_PCT') targeting specific cryptocurrencies (bitcoin, ethereum, etc.). These scripts are commonly used by threat actors to exfiltrate funds from victim crypto wallets.
This rule detects suspicious process execution chains where common web application servers (gunicorn, uwsgi, celery) spawn command-line utilities (bash, sh, curl, wget, python3) containing strings indicative of Python object inspection or class pollution. This pattern is commonly associated with attempts to exploit server-side vulnerabilities for remote code execution or post-exploitation activities.
This rule extracts and audits inventory information from local agents, including vendor, device name, account context, and associated process information. It is designed to provide visibility into the state and configuration of installed local agents within the environment.
This rule detects potentially malicious activity associated with known supply chain compromise indicators in npm packages (such as Keyv and associated malicious scripts). It flags the execution of specific suspicious files (e.g., 'setup.mjs', 'Math_Symbol.js') or the use of specific versions of common packages known to be associated with recent supply chain attacks, when executed via npm or node.js runtime.
Detects the creation of executable script files (PHP, ASP, ASPX, JSP) by web server worker processes (e.g., httpd, nginx, w3wp.exe, php-fpm). This behavior is strongly indicative of the final stage of a web exploitation workflow where an attacker writes a web shell to the server to establish persistence or remote command execution capabilities.
Detects network connections to the localhost IP 127.0.0.1 on TCP port 23075 initiated by non-browser and non-VPN processes, excluding standard system binaries and protected paths. This pattern is commonly associated with SOCKS proxies, tunnelers, or malicious local communication channels used for C2 redirection.
This rule detects the execution or presence of known malicious JavaScript loader files identified as part of a banking-lure phishing campaign by matching their SHA256 file hashes.
Detects malicious heartbeat check-ins to a C2 server endpoint '/api/bot/heartbeat' by monitoring for unauthorized exfiltration of hardware identifiers (Host/Device/HW ID) or potential remote task execution via Base64-encoded instructions in the response body, characteristic of ClickFix-related infostealer campaigns targeting macOS users.
Detects a shell/interpreter process spawned by a VS Code / VS Code-Insiders editor process that references CI marker environment variable names (GITHUB_, GITHUB_REPOSITORY, GITLAB_CI_, CI_PROJECT_PATH), matching how malicious Open VSX 'evil twin' extensions harvested CI/CD environment variables from GitHub, GitLab, and Azure DevOps runners.
Detects instances where a Java process (typically a web application server like Tomcat) initiates suspicious command-line tools such as cmd.exe, powershell.exe, or various Linux shell binaries, using command-line arguments indicative of a reverse shell or code execution (e.g., -e /bin/sh, -i, /dev/tcp, IEX, DownloadString). This pattern is commonly associated with exploit attempts targeting vulnerabilities like Java deserialization.
Detects ClientKing's technique of loading Linux kernel modules directly from memory (via memfd/init_module) without a corresponding on-disk .ko file, used to deploy rootkit functionality.
Detects a Node or Bun process reaching the cloud instance metadata service. The keyv/cacheable
stage-2 collector targets EC2 IMDS and ECS task metadata as the entry point to a broader sweep
covering AWS credential chains and Secrets Manager across all regions, GCP service account
keys, Azure client secrets, HashiCorp Vault tokens, Kubernetes service account tokens, GitHub
Actions OIDC request tokens and npm tokens. On a build agent this pattern is the clearest
signal that credential theft is in progress.
stage-2 collector targets EC2 IMDS and ECS task metadata as the entry point to a broader sweep
covering AWS credential chains and Secrets Manager across all regions, GCP service account
keys, Azure client secrets, HashiCorp Vault tokens, Kubernetes service account tokens, GitHub
Actions OIDC request tokens and npm tokens. On a build agent this pattern is the clearest
signal that credential theft is in progress.
This rule analyzes recent agent telemetry to identify and summarize the distribution of local agent vendors present in the environment over a 30-day lookback period. It extracts vendor information from agent metadata and provides a frequency count to assist in auditing deployed infrastructure agents.
Detects outbound network connections and DNS queries to a maintained list of known UNC6671 extortion-related domain names. The rule utilizes a temporal 'recency' window (aged IOCs) to filter out stale indicators, mitigating false positives caused by sinkholed or reassigned infrastructure.
Detects execution of potentially malicious JavaScript files (e.g., setup.mjs, math_init.js) via Node.js or Bun command-line tools. This often indicates the execution of obfuscated or unauthorized scripts during software installation or supply chain compromise attempts.
Detects process activity referencing GitHub Actions, GitLab CI, or Azure DevOps pipeline environment variable names (GITHUB_*, CI_*, GITHUB_ACTIONS, GITLAB_CI, Azure DevOps pipeline variables) consistent with a malicious extension harvesting CI/CD runner environment variables.
Detects a Node or Bun process reading Kubernetes service account tokens or HashiCorp Vault
token files. The keyv/cacheable collector reads these paths directly as part of its credential
sweep. Companion rule to the IMDS detection (d02b7df0-60e3-4ec9-a077-339507299e11).
token files. The keyv/cacheable collector reads these paths directly as part of its credential
sweep. Companion rule to the IMDS detection (d02b7df0-60e3-4ec9-a077-339507299e11).
Detects creation of the stage-2 payload files distributed with the compromised keyv and
cacheable packages. Math_Symbol.js is a ~728 KB Bun bundle shipped in the tarball and written
to disk as math_init.js by the loader; bun-dl-* directories are used to stage the downloaded
Bun runtime. These filenames are specific to the campaign and should be treated as high
fidelity indicators.
cacheable packages. Math_Symbol.js is a ~728 KB Bun bundle shipped in the tarball and written
to disk as math_init.js by the loader; bun-dl-* directories are used to stage the downloaded
Bun runtime. These filenames are specific to the campaign and should be treated as high
fidelity indicators.
This rule detects the use of the Frida dynamic instrumentation toolkit and the objection framework, specifically searching for command-line arguments and process names associated with their installation or use, as well as network activity on the default Frida server port (27042). It monitors for activities like SSL pinning bypass, mobile application patching, and remote agent deployment.
Detects malicious persistence hooks in IDE configuration files (.claude/settings.json, .vscode/tasks.json) used by the ChainDrop or Mini Shai-Hulud npm worm to execute unauthorized JavaScript payloads upon opening a repository.
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