Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects anomalous file modifications to web-accessible directories (such as index.html, dist, public, or wwwroot) by common JavaScript execution environments including node.exe, bun.exe, or npm. This activity is consistent with post-compromise tampering of web assets as observed in the Miasma/Hades campaign, likely involving the abuse of stolen repository credentials to deploy malicious content.
This rule monitors for the execution of the 'bun.exe' process specifically when it originates from a Node.js-related context (such as npm, node-gyp, or binding.gyp execution) or exhibits suspicious behaviors like executing payloads from /tmp directories. This pattern is often associated with supply chain attacks or malicious package execution within JavaScript development environments.
Detects outbound network connections to 'stitch-production.org' or connections by node/bun runtime processes to GitHub API or 'stitch-production.org', which may indicate command and control communication or data exfiltration.
Detects malicious behavior attributed to the Miasma/TonRAT malware, specifically targeting node.js or bun.exe runtime environments. The rule identifies suspicious network connections to command and control (C2) domains, access to sensitive developer credential files (e.g., .npmrc, .aws/credentials), execution of identified credential-harvesting functions in process command lines, and the execution of specific suspicious preinstall scripts.
Detects the obfuscated 'setup.cjs' dropper associated with the easy-day-js npm supply chain attack. The rule identifies unique obfuscated variable names, XOR-encoded marker bytes, and specific campaign-related strings, including postinstall commands, package names, second-stage payload filenames, self-deletion patterns, and TLS bypass indicators.
Detects the creation of an Amazon Q Model Context Protocol (MCP) configuration file. This file is used to define tools and resources for Amazon Q, and its creation could indicate a user configuring external tool access for the AI assistant or an adversary attempting to influence its capabilities.
Detects unexpected shell command execution spawned by the Amazon Q Developer VS Code extension processes (e.g., 'amazonq-lsp'). This activity is consistent with patterns related to the exploitation of CVE-2026-12957, involving the potential auto-execution of unauthorized commands via MCP (Model Context Protocol) server configurations or malicious inputs.
Detects anomalous child process execution (e.g., bash, sh, npx, node) spawned directly by AI coding assistants or IDE extensions (Claude Code, Cursor, Amazon Q). This behavior, specifically involving auto-executed configurations like mcp.json, is indicative of exploitation attempts targeting AI coding environments where remote code execution (RCE) can be achieved via untrusted configurations or injected prompts.
Detects the Amazon Q Developer language server or extension host spawning suspicious child processes (bash, sh, zsh, python, node) that execute commands involving AWS STS identity retrieval, external data exfiltration via network tools like curl/wget, or direct references to AWS credential environment variables. This pattern is indicative of potential Remote Code Execution (RCE) via malicious Model Context Protocol (MCP) auto-execution.
Loader used in click-hijacking traffic distribution scheme
Loader used in click-hijacking traffic distribution scheme
Supply chain worm targeting npm packages and GitHub Actions, linked to Shai-Hulud/Hades lineage
Stealthy backdoor MLTBackdoor linked to KongTuke ClickFix and ModeloRAT campaigns
Stealthy backdoor MLTBackdoor linked to KongTuke ClickFix and ModeloRAT campaigns
ClickFix style social engineering cluster delivering Mistic and ModeloRAT
Detects the creation or modification of suspicious LaunchAgent or LaunchDaemon plist files on macOS. Specifically looks for files named 'com.apple.accountsd.plist' or files within a hidden directory '.com.apple.accountsd' in common LaunchAgent/Daemon paths. This pattern is often used by malware for persistence.
Rust-based macOS infostealer implant embedding prompt injection payloads
Rust-based macOS infostealer implant embedding prompt injection payloads
Rust-based macOS infostealer implant embedding prompt injection payloads
Fraud framework powering scam domains for crypto and gambling schemes
Detects unauthorized processes, such as shells, scripting engines, or command-line utilities, that attempt to display or access environment variables containing sensitive cloud credential patterns (e.g., AWS_ACCESS, API_KEY). This behavior often indicates an attempt to steal cloud provider credentials from the host environment.
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