Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
40,063 detections
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Detects instances where explorer.exe initiates cmd.exe with suspicious command-line patterns often associated with malicious script execution or evasion. These include caret-based obfuscation, mixed-case PowerShell invocations, or base64-like blobs, alongside indicators of common malicious file paths or execution policy bypass flags.
Detects instances where explorer.exe initiates cmd.exe with suspicious command-line patterns often associated with malicious script execution or evasion. These include caret-based obfuscation, mixed-case PowerShell invocations, or base64-like blobs, alongside indicators of common malicious file paths or execution policy bypass flags.
This rule detects instances where a process associated with a known StealC command-and-control (C2) IP address subsequently spawns a hidden cmd.exe instance. It correlates network connections to known malicious infrastructure with the creation of hidden command shells within the same device session, specifically looking for common parent processes like web browsers or system utilities.
Detects anomalous activity where an AI coding assistant process reads sensitive local credential files (such as .env, .aws/credentials, or SSH keys) followed by an outbound network connection to a destination not associated with known package registries or AI provider APIs. This pattern is indicative of potential prompt-injection attacks targeting autonomous AI coding tools to exfiltrate developer secrets.
Detects the execution of binaries or scripts named with keywords related to AI agent plugins (e.g., 'skill', 'plugin', 'mcp-server') from potentially untrusted locations like Downloads or Temp folders. The rule further correlates this execution with post-exploitation indicators such as persistence establishment (registry keys, scheduled tasks, launch agents) or outbound network activity.
This rule monitors for potential MeshAgent activity associated with the Settra threat actor. It identifies processes that are likely renamed instances of MeshAgent (via metadata inspection), processes attempting to communicate with known C2 IP addresses, and direct network connections to these C2 IP addresses.
Detects a rapid, multi-stage intrusion sequence on a single host involving discovery, lateral movement, and high-volume file modifications. The rule identifies anomalous behavior where diverse reconnaissance and lateral movement commands are executed within a compressed timeframe, characteristic of automated or LLM-driven orchestration of ransomware operations.
Detects the installation of AI agent-related packages (npm, pip, etc.) followed shortly by unauthorized access to sensitive files or credential stores on the same host. This pattern is indicative of a malicious or 'poisoned' AI agent tool performing credential theft or unauthorized exfiltration of sensitive system data.
This rule detects potential unauthorized use of MeshAgent RMM software by correlating process execution events (mvtcs.exe, MeshAgent) with network traffic to specific IP addresses identified as associated with Settra command-and-control infrastructure. It specifically filters for MeshAgent activity and validates the threat by requiring an established network connection to known malicious endpoints.
This rule detects potential unauthorized use of MeshAgent RMM software by correlating process execution events (mvtcs.exe, MeshAgent) with network traffic to specific IP addresses identified as associated with Settra command-and-control infrastructure. It specifically filters for MeshAgent activity and validates the threat by requiring an established network connection to known malicious endpoints.
Detects the obfuscated first-stage JavaScript payload sharedLoad.min.js dropped by the malicious npm indexed-btree package, identified by string-array encoding and self-checksumming array rotation obfuscation patterns
Detects the sharedLoad.min.js obfuscated first-stage loader dropped by the malicious npm indexed-btree package, triggered via BTree.prototype.set to evade static/taint-analysis scanners
Detects the indexed-btree npm malware loader embedded in BTree.prototype.set that spawns a detached hidden Node.js child process and references sharedLoad.min.js
Detects the indexed-btree npm malware loader embedded in BTree.prototype.set that spawns a detached hidden Node.js child process and references sharedLoad.min.js
Detects the execution of npm commands to install specific, potentially malicious or typo-squatted npm packages. The rule filters for common npm install command line arguments and matches against a predefined list of package names that are often associated with supply chain compromise attempts.
This rule detects instances where a Node.js process spawns a child Node.js process from a 'node_modules' directory using configuration flags typically associated with hidden, detached background tasks (e.g., 'detached', 'stdio', 'windowsHide', 'ignore'). It explicitly excludes common Node.js process managers and build tools to reduce false positives associated with legitimate development activities.
Detects outbound network connections from internal devices to a set of known malicious IP addresses (45.151.45.31 and 46.166.79.31) which may indicate command and control communication or other malicious activity.
This rule detects the use of specific tools associated with credential dumping and memory forensics, including Dokan driver installations for file system mounting, the use of DumpIt for creating memory dumps, and the subsequent analysis of these dumps using MemProcFS to access sensitive process memory information such as LSASS minidumps.
Detects potential C2 activity associated with MQTTDoor or MatrixDoor malware by monitoring suspicious network traffic patterns. This includes unauthorized processes connecting to MQTT brokers (hivemq.com), non-chat applications interacting with a Matrix homeserver, and geo-location lookups (ip-api.com) occurring shortly after process execution.
Detects git checkout of a bare 40-hex commit SHA or the literal FETCH_HEAD ref, executed by a recognized AI coding-agent process. Narrowed to the Plugin4Shell exploitation fingerprint (checkout of a pinned-SHA-shaped or FETCH_HEAD ref) rather than ordinary branch/tag checkouts, which these agents perform constantly during normal plugin installs.
Detects the Sauron Loader DLL side-loading chain: rnpkeys.exe (legitimate) side-loading malicious rnp.dll, which loads tdwp.dll to decrypt the loader in memory, all staged from C:\ProgramData\keyroll. Requires BOTH DLLs to be loaded by the same rnpkeys.exe process instance (not either/or) to eliminate single-artifact false positives, and surfaces SHA256 hashes of all three components for direct comparison against known IOCs (legitimate rnpkeys.exe: 194d7e8870ff783ce1e4e4e3015c895cc67ae52fd5e063c89dd1c069400d3991; malicious rnp.dll: 5606afdc5191d42f38d3c4f1692eda0a629c88810e29bfe78528733284ad1bf8; malicious tdwp.dll: 6551293e996d19755ba497f50b30a18c178f0d6e2a73b29ae742b8171e2985b7).
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