Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the Sckit supply chain implant reading sensitive credential files from a user's home directory. The rule monitors processes spawned by Node.js or Python interpreters (the primary loaders for the Sckit worm) attempting to access high-value files like SSH keys, .npmrc, .pypirc, and various token storage files, indicating potential credential harvesting behavior.
Detects anomalous child process execution (e.g., shells, curl, python) or the creation of web-accessible script files (.jsp, .php, .aspx) originating from common VPN gateway or edge appliance service processes. This behavior is indicative of potential exploitation of a remote-facing appliance or webshell deployment.
Detects a suspicious sequence of events where a known web server process (e.g., IIS, Nginx, Apache) spawns a command shell process, followed shortly by the creation of a file with a web shell-like extension (.aspx, .jsp, .php) in the same environment. This pattern is indicative of an adversary exploiting a public-facing application to upload and potentially access a web shell.
Detects unauthorized attempts to interact with the Docker API to create containers or pull images, specifically looking for patterns associated with the CARBONATO worm which utilizes the /containers/create endpoint with 'net-setup' parameters.
Detects incoming HTTP POST requests to the Docker API endpoint '/containers/create' containing 'Privileged: true' and a bind mount to the host filesystem ('/:/host'). This pattern is indicative of an attempt to deploy a privileged container with host access, which can be leveraged for container breakout or host system compromise.
Detects the presence of the 'SOUL.md' configuration file associated with the Hermes Agent AI framework. This file contains a specific 'GH0ST' persona prompt designed to bypass ethical restrictions (jailbreak) and configure the agent for automated post-exploitation tasks, such as loot collection and Telegram-based command and control.
Detects evidence of persistence mechanisms associated with the CARBONATO botnet on Linux systems. This includes the application of chattr +i to the malicious watchdog binary, the execution of the auto-persist-host.sh script, the enabling of the docker-network-resolver systemd timer, or modifications to crontab for watchdog execution.
Detects instances where the XMRig cryptominer is masquerading as the legitimate systemd-logind process on Linux hosts. The rule triggers on process execution of /usr/sbin/systemd-logind coupled with suspicious outbound network connections to known mining pools or mining-related ports.
Detects the creation of files containing AI provider API keys within the /root/.hermes/loot/ directory, consistent with credential harvesting behavior observed by the CARBONATO GH0ST agent.
Detects anomalous database activity on Magento e-commerce platforms where a SELECT operation against sensitive payment-related tables is followed by a DELETE operation on the same table within the same host context. This sequence is indicative of an attacker exfiltrating credit card data and subsequently attempting to remove forensic evidence of the theft.
Detects a suspected automated exploitation sequence where a web storefront file (e.g., .phtml, .js, .php) is modified to inject malicious script code (skimmer), followed by an unauthorized SQL DELETE operation on sensitive database tables containing payment, customer, or order information, originating from the same host within a 6-hour window.
Detects the deployment of the CARBONATO botnet's Hermes Agent within containerized environments. The rule identifies specific artifacts such as the 'SOUL.md' persona configuration, 'netd-svc' container references, and indicators of AI-focused credential theft (e.g., searching for OpenAI or Anthropic API keys) orchestrated by the GH0ST AI agent.
Detects outbound connections to a known malicious C2 infrastructure associated with the CARBONATO threat actor. The rule identifies both established SSH sessions using the OpenSSH implementation and the initiation of outbound TCP connections on ports dynamically determined by an MD5 hash, which is a known behavior of this actor's C2 communication strategy.
Detects the use of the 'nsenter' utility to target the PID 1 namespace with host-level namespace flags. This technique is used by the CARBONATO botnet to escape from a privileged Docker container and execute commands on the underlying host system, leveraging the host filesystem mount.
Detects unauthorized access to unauthenticated Docker registry API endpoints on port 5000. This rule identifies catalog enumeration and the pulling of malicious container images associated with the CARBONATO botnet, including the retrieval of image manifests and configuration files that expose sensitive environment variables and credentials.
Detects persistence mechanisms used by the CARBONATO botnet on Linux-based Docker hosts. The rule monitors for the application of immutable file attributes using 'chattr +i' on identified watchdog binaries (specifically '.docker-network-monitor'), the creation of malicious cron jobs, the enabling of suspicious systemd timers ('docker-network-resolver'), and the execution of specific persistence-related shell scripts.
Detects the deployment and operational artifacts associated with the Hermes Agent framework using the CARBONATO GH0ST persona on Linux systems. This detection focuses on identifying specific file-system indicators, including persona configuration files (SOUL.md), loot staging directories, and deployment entry scripts (entry.sh or CARBONATO_API_KEY artifacts) that indicate malicious activity and potential AI-driven Telegram command and control (C2) staging.
Detects the use of the 'getevent' utility on Android/Linux systems to monitor and capture raw input events from '/dev/input'. This technique is often used by mobile malware to perform keylogging by intercepting touch or physical keystroke event streams, bypassing standard application-level input handling.
Detects a multi-stage attack chain where an AI-agent's configuration file (e.g., mcp.json) is modified, followed immediately by the execution of a tool process (node/python) spawned by the agent, the subsequent spawning of a shell process, and finally an outbound network connection to a rare, non-standard domain. This sequence is indicative of AI agent tool poisoning, where malicious tool definitions are introduced to execute arbitrary commands and exfiltrate data. Coverts T1195.002, T1565.001, T1059
Detects a multi-stage, automated attack chain performed by AI-based development agents (e.g., Claude, Copilot, Cursor). The rule correlates process discovery, credential access, file collection (staging), and exfiltration over web services within a tight 15-minute window, identifying potential autonomous exploitation and data exfiltration. Covered T1046, T1552.001, T1078, T1005, T1567
Detects extension code implementing Caesar-shift-over-base64 decoding of a remote proxy server list fetched from dead-drop hosts, feeding a PAC-based proxy configuration
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