Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects host reconnaissance and enumeration commands, such as systeminfo, ipconfig, and wmic, when spawned from the 'openclaw' or 'letssendit' process tree. This behavior is indicative of post-installation reconnaissance activity associated with the OpenClaw malicious skill package.
Detects non-browser applications (Python, PowerShell, cURL, wget, node) communicating directly with OpenAI or ChatGPT API endpoints, indicative of automated AI tradecraft by threat actors. This rule specifically looks for network connections to api.openai.com initiated by these common scripting or command-line tools.
Detects anomalous network traffic patterns communicating with the Telegram Bot API (api.telegram.org) from non-official Telegram processes. The rule identifies potential command and control (C2) activity by analyzing request frequency, specific API method usage (e.g., getUpdates, sendMessage), and beaconing-like behavior.
Detects activity associated with a specific phishing campaign distributing 'Distribution Settlement Agreement' PDF lures. The rule monitors for file creation or execution of files matching this naming pattern, as well as network connection attempts to domains identified as related to the threat actors: 'gasparinutrition.com' and 'gappssmtp.com'.
Detects network requests to Google image search containing an 'imgurl' parameter, which can be used by an attacker to exfiltrate data by forcing an external service to crawl a controlled URL containing sensitive information.
This rule detects potential command and control (C2) activity by identifying specific DNS queries to known malicious domains or suspicious network-related processes executing on an endpoint. It flags DNS requests for 'birdeemusic.com' and network connections initiated by processes with names indicative of custom or potentially malicious payloads like '_socket.pyd' or 'Traiolx Custom Utils'.
Detects Node.js processes initiating network connections to remote destination port 2222. This specific port and behavior pattern are known to be used by the Miasma botnet as a fallback C2 channel or for SSH-based remote access when standard communication ports are blocked or monitored.
Detects the execution of sensitive command-line tools or environment variables (e.g., AWS CLI, MCP tools, environment secrets) triggered by AI-based development assistants such as Claude, Cursor, or Windsurf. This behavior may indicate an attacker abusing the permissions or capabilities of an AI coding assistant to perform unauthorized cloud discovery or credential access.
Detects bash processes executing commands that combine AWS identity verification with outbound exfiltration using curl. The pattern specifically monitors for the use of 'aws sts get-caller-identity' followed by an immediate HTTP POST transmission of data (indicated by '-d @-'), which is characteristic of attackers exfiltrating captured cloud environment metadata or temporary credentials.
This rule detects potentially malicious child processes spawned by Amazon Q or AWS Language Server components (e.g., amazon-q, aws-lsp-server). The rule specifically flags behavior associated with the loading of MCP server configurations, potential unauthorized access to AWS credentials, or network data exfiltration attempts through commonly abused binaries like shell interpreters, python, or curl/wget when these are not signed by Amazon.
Detects instances where common development runtime processes (e.g., node, python, shells) spawn child processes whose command lines contain references to sensitive credential environment variables such as AWS access keys, GitHub tokens, or SSH authentication sockets. This behavior often indicates that a developer or an automated tool is insecurely passing credentials via command-line arguments to subprocesses.
Detects the execution of AWS CLI commands by common scripting interpreters (Node.js or Python). This behavior is often indicative of automated cloud environment reconnaissance or credential testing using compromised access keys or instances.
Detects instances where the SimpleHelp RMM agent process initiates a command interpreter or scripting process. This behavior is often indicative of post-exploitation activity, specifically unauthorized script or command execution delivered via a remote support session.
Detects the creation of a 'linux-process-env.json' artifact by a Node.js process. This file is typically generated by the Djinn Stealer malware as part of its 'collectLinuxProcessEnv' function, which enumerates system process command lines and environment variables from the /proc directory after initial compromise.
This rule detects network connections to Discord's API webhooks endpoint, specifically looking for POST requests. This activity can indicate data exfiltration, command and control communications, or other malicious use of Discord webhooks by adversaries.
Detects anomalous child process creation from PHP-FPM or PHP web worker processes. This is indicative of exploitation activity, specifically targeting vulnerabilities in PHP environments where deserialization or memory access (e.g., ASLR bypass via /proc/self/maps) leads to unauthorized code execution and subsequent command-line tool usage.
Detects Node.js processes executing with suspicious command-line arguments that include specific file extensions (.woff, .woff2, .svg, .jpeg, .png, .dict) or known suspicious file names associated with potential malicious activity or obfuscation.
Detects Node.js executing the malicious setup.cjs script with the --no-warnings flag. This execution sequence is associated with the easy-day-js typosquat postinstall hook used in the Mastra npm supply chain compromise.
Detects processes attempting to read or open sensitive SSH files (keys and configuration) that are not recognized as legitimate SSH-related utilities (e.g., ssh, sshd, rsync, git). This behavior is often indicative of credential harvesting or unauthorized reconnaissance of authentication artifacts.
Detects Python or Node.js processes reading sensitive SSH private key files (id_rsa, id_ed25519) followed by an outbound network connection within a one-minute window. This behavior is indicative of credential theft and exfiltration, such as that observed in the InvisibleFerret campaign.
Detects instances where development IDEs (VS Code or Cursor) spawn suspicious child processes such as command shells (cmd, powershell, bash) or network utilities (curl, wget). The detection logic focuses on common command line patterns associated with IDE tasks or potential malicious activity.
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