Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects the execution of the 'sckit' Go-based implant when spawned by Node.js or Python processes using the command-line arguments 'stage0 --config64'. This pattern is associated with malicious npm and PyPI supply chain packages (memtensor) designed to harvest credentials and establish persistence.
Detects malicious BASH_ENV injection within GitHub Actions CI pipelines originating from the compromised sckit_poetry_build.py build backend. The injection, which targets GITHUB_ENV to introduce a malicious _pypi_bridge.sh script, is used to intercept PyPI publishing tokens during build processes, characteristic of the MemTensor/sckit supply chain attack.
Detects the creation of a malicious GitHub Actions workflow file named 'runtime-update.yml', a known tactic used by the Sckit supply-chain worm. The worm injects this workflow to automate persistence and further propagation of the Go-based implant within CI/CD pipelines.
Detects the creation of a 'ca-roots.pem' file within a hidden '.sckit' directory on Linux systems. This behavior is associated with the 'sckit' supply-chain malware (e.g., delivered via malicious npm packages like @memtensor/memos-cloud-openclaw-plugin), which uses this bundled certificate to enable HTTPS Command and Control (C2) communication in environments where standard system CA stores are unavailable.
Detects the installation of known malicious npm or PyPI packages followed within 30 minutes by the execution of a package manager (node or python) performing network activity. This pattern matches the behavior of downloader stages in the 'Graphalgo' campaign, which uses coding-task lures to trick users into installing malicious packages.
Detects potential exfiltration of sensitive DevOps credentials or configuration files (such as AWS credentials, SSH keys, Kubernetes configs, or cryptocurrency wallets) by monitoring for file access events followed by outbound network connections to known exfiltration channels like Slack or specific C2 infrastructure within a 30-minute window.
The following analytic identifies instances where CrushFTP has blocked access due to exceeding the maximum number of simultaneous connections from a single IP address. This activity may indicate brute force attempts, credential stuffing, or automated attacks against the CrushFTP server. This detection is particularly relevant following the discovery of CVE-2025-31161, an authentication bypass vulnerability in CrushFTP versions 10.0.0 through 10.8.3 and 11.0.0 through 11.3.0.
Detects instances where a non-browser process initiates connections to commercial LLM provider APIs (DeepSeek, OpenRouter, Mistral) followed by a connection to Discord CDN/Webhook endpoints within a 15-minute window. This behavior is indicative of a process acting as an autonomous C2 agent that exfiltrates data after receiving instructions or processing information via an LLM.
Detects the execution of the 'sckit' Go implant, a malicious binary associated with trojanized '@memtensor/memos-cloud-openclaw-plugin' or 'MemoryOS' packages. The rule identifies instances where this binary is spawned as a child process of a language runtime (Node.js or Python) when the execution originates from specific directory paths associated with these packages, or when the parent process command line indicates these packages are being initialized.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects malicious activities associated with the SCKit worm, specifically targeting package publishing via npm/twine, GitHub Actions workflow injection (runtime-update.yml), and the dropping of postinstall propagation stubs (bootstrap.cjs) when initiated by SCKit processes.
Detects the Sckit Go implant accessing sensitive local configuration and credential files, including SSH keys, cloud CLI tokens, and package manager credentials. The rule monitors for file read events initiated by processes identified as 'sckit' or processes with specific command line arguments.
Detects execution of PowerShell or Python scripts characterized by common patterns found in AI-generated code, including specific obfuscation techniques (base64, string manipulation), boilerplate error handling structures, verbose comments, and generic variable naming conventions. High scores indicate a higher probability of automated or obfuscated script execution.
Detects the installation of AI-related packages (e.g., mcp, tiktoken_mcp) via common package managers (pip, npm, docker) followed by an outbound network connection from the same host within 10 minutes. This behavior is consistent with supply chain attacks where trojanized AI/MCP components are used to initiate command-and-control communication shortly after deployment.
This rule detects potentially malicious network activity by monitoring for specific query parameters ('bmodule', 'smodule', 'lmodule', 'task', 'upload.php') in web requests or communication with a specific known-malicious IP address ('62.60.226.50'). This pattern is characteristic of C2 (Command and Control) traffic or unauthorized file staging/upload operations.
Detects anomalous Telnet (TCP port 23) traffic associated with Mirai-variant botnet propagation, such as scanning for new targets or inbound compromise attempts, often following cPanel/WHM vulnerabilities.
This rule detects specific JavaScript helper functions and state machine constants commonly used in 'ClickFix' phishing campaigns (e.g., Exvicy and ErrTraffic). These scripts typically prompt users to copy and paste malicious code snippets, often disguised as error fixes or CAPTCHA resolution, to facilitate initial access.
Matches archived SHA-256 hashes of known malicious CRX builds from the 'VPN for X' proxy farm extension family
Detects anomalous DNS query patterns originating from AI agent hosts that are characteristic of DNS tunneling, such as the use of TXT or NULL records and excessively long subdomain labels. These techniques are often used by attackers to establish covert Command and Control (C2) channels and exfiltrate data by bypassing traditional HTTP/HTTPS egress filtering.
Detects periodic, repetitive outbound HTTPS network connections from AI agent-runtime environments to domains that are not in the predefined allow-list. This behavior is consistent with C2 beaconing disguised as application API traffic, potentially indicating an AI agent has been compromised or misused for unauthorized external command communication.
Detects the presence of a specific, hardcoded Ed25519 public key associated with malicious cross-platform payloads (npm, Go modules, Terraform providers) that use Slack for C2 communication.
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