Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects attempts to access sensitive .env configuration files in Gemini CLI applications, which may indicate an attempt to exploit CVE-2026-12537. Attackers target these files to retrieve credentials or environment variables that could lead to Remote Code Execution (RCE) within CI/CD pipelines or deployment environments.
Detects indicators of persistence activity associated with the MYRA RAT. This includes unauthorized modifications to shared library preload mechanisms (/etc/ld.so.preload), creation of malicious shared objects in systemd user paths by common interpreter/shell processes, suspicious modification of cron job files by those same processes, and the execution of the 'systemd-userdbd' process from non-standard, unauthorized filesystem locations.
This rule detects file access or modification events targeting '.env' files, which often store environment variables and sensitive configuration data (such as API keys and credentials). The detection specifically focuses on file paths associated with CI/CD build agents, runners, or workspace directories (e.g., github, gitlab, jenkins, build, runner), where such credentials are high-value targets for attackers seeking to escalate access or pivot within an environment.
Detects the execution of Python interpreters with command-line arguments that utilize common obfuscation and decoding techniques. The rule identifies a combination of Base64 decoding, codec decoding, ROT13/ROT47 rotation, and hexadecimal string conversion, which are frequently used to hide malicious scripts or payloads from static analysis.
Detects Python processes that establish network connections to web ports (80 or 443) followed by the execution of deserialization functions (pickle.load or pickle.loads) within the same process context. This pattern is commonly associated with downloading and executing malicious payloads or remote code execution via insecure deserialization.
This rule detects attempts to access sensitive .env configuration files in Gemini CLI applications, which may indicate an attempt to exploit CVE-2026-12537. Attackers target these files to retrieve credentials or environment variables that could lead to Remote Code Execution (RCE) within CI/CD pipelines or deployment environments.
Detects multiple TCP synchronization (SYN) packets targeting the SSH service (port 22) from a single source IP address within a short timeframe. This behavior is indicative of a brute-force or credential-guessing attack against the SSH service.
This rule detects suspicious HTTP request bodies containing the 'LD_PRELOAD' environment variable assignment, targeting common temporary or writable directories. This behavior is indicative of an attempt to perform dynamic linker hijacking on a Linux system to inject malicious shared libraries into target processes.
Identifies Node.js or IDE-related processes initiating connections to the Solana mainnet RPC endpoint. This behavior is associated with GLASSWORM's WASM loader performing dead-drop C2 resolution via blockchain transaction memos.
Detects the use of the 'ditto' command with specific arguments indicating data staging or collection activities, particularly when archiving to a temporary location like '/tmp/osalogging.zip'. This could be indicative of an adversary collecting data from the local system before exfiltration.
Detects the execution of a binary from the Linux shared memory directory /dev/shm.
This directory is a tmpfs mount backed entirely by RAM and is abused by attackers for fileless malware staging because files written there never touch physical disk and may evade disk-based detection.
This directory is a tmpfs mount backed entirely by RAM and is abused by attackers for fileless malware staging because files written there never touch physical disk and may evade disk-based detection.
This rule detects the loading of a machine learning model (e.g., Pickle, PyTorch, or Hugging Face model files) via Python, immediately followed by the creation of a Windows Executable (PE) or Shared Object (.so) file on disk by the same initiating process. This behavior is indicative of an embedded stage-2 loader within a malicious model file, often seen in backdoored Large Language Models (LLMs). The time correlation between the model loading and the file drop is set to 45 seconds to identify immediate post-load execution.
This rule detects potentially malicious activity related to the 'node-gyp' build tool used by npm. It monitors for two patterns: 1) npm spawning node-gyp, which can be an automated trigger for malicious binding.gyp files, and 2) node-gyp spawning node.exe with command-line arguments indicative of obfuscated JavaScript (e.g., base64 encoding, eval, AES-GCM patterns), a technique often seen in malicious Node.js packages.
This rule detects network connections from internal hosts to identified C2 or phishing infrastructure associated with the threat actor group UNC1151 (also known as Ghostwriter). It monitors both host-based network events (via DeviceNetworkEvents) and centralized network security logs (via CommonSecurityLog) for traffic targeting a curated list of known malicious IP addresses.
This rule detects suspicious activity involving Node.js or Bun runtimes, specifically focusing on the access of sensitive configuration files (e.g., .npmrc, .aws/credentials, .ssh, .kube/config) or the execution of commands containing keywords associated with credential harvesting and automated data collection scripts.
Detects rapid access (three or more distinct files within a 60-second window) to sensitive files typically containing credentials or configuration data (e.g., SSH keys, AWS credentials, environment files, container configurations). This pattern is often associated with credential dumping or reconnaissance activity by an adversary attempting to harvest secrets.
Detects anomalous execution patterns involving Node.js and Bun runtimes, specifically identifying suspicious process lineage such as node processes spawned by node.gyp, or Bun execution patterns involving temporary files or specific command-line arguments. Additionally, it alerts on the execution of a specific known malicious file hash.
Detects execution of node-gyp to compile native Node.js addons, which can be leveraged by attackers to execute arbitrary code or build malicious modules during project installation or development. The rule looks for binding.gyp usage and build commands initiated by npm or node processes.
Detects execution patterns associated with the Miasma/Mini Shai-Hulud multi-layer obfuscated npm payload. This includes monitoring for bun runtime spawning from Node/NPM contexts, execution of bun with specific patterns from /tmp, downloading of specific bun versions from GitHub, and execution of suspicious index.js scripts within .claude directories.
Detects persistence mechanisms associated with the MYRA Linux RAT, including LD_PRELOAD hijacking for shared library redirection, malicious cron job creation with specific scheduling (13-minute intervals), and unauthorized modifications to profile.d scripts to execute malicious code.
Detects instances where 'node' or 'bun' runtime processes access multiple sensitive developer configuration or credential files (e.g., .ssh, .aws/credentials, .npmrc, .kube/config). This behavior is indicative of potential credential theft or reconnaissance activities by an adversary attempting to leverage developer environments.
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