Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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IOC hunt across DNS, network, and file-hash telemetry for the Ledger Google Ads phishing campaign. Vercel redirect domains are matched by exact hostname (DNS query name / parsed URL host) rather than substring, eliminating false positives from unrelated strings that merely contain a look-alike domain fragment. GCS bucket and Google Sites path IOCs remain substring-matched since the bucket IDs and page slugs are already highly specific.
Detects network navigation to Google Sites pages that match patterns associated with known Ledger-impersonating phishing campaigns. These sites are often reached through redirect chains involving Google Ads, cloud storage, and rotating domains.
Detects network navigation to Google Sites pages that match patterns associated with known Ledger-impersonating phishing campaigns. These sites are often reached through redirect chains involving Google Ads, cloud storage, and rotating domains.
Detects network navigation to Google Sites pages that match patterns associated with known Ledger-impersonating phishing campaigns. These sites are often reached through redirect chains involving Google Ads, cloud storage, and rotating domains.
Detects HTTP POST requests directed at Grav CMS endpoints where the __unique_form_id__ parameter contains directory traversal sequences (e.g., ../). This behavior is indicative of attempted exploitation of CVE-2026-42608, aimed at bypassing file system restrictions to write files to unauthorized locations outside the application's expected form data directory.
Detects instances where a Claude process accesses a 'SKILL.md' file, followed closely by a suspicious command execution on the same device. The rule specifically targets command-line activity that involves encoding, download-and-execute patterns, staging in sensitive directories, or communication with suspicious domains/IPs, which is indicative of a supply-chain or poisoned agent-skill file attack.
Detects the GitHub Actions runner executing the Bun runtime to run a hidden index.js payload, specifically associated with the compromised 'actions-cool/issues-helper' or 'actions-cool/maintain-one-comment' actions. The rule filters for process execution context tied to GitHub runner internals and validates that the Bun execution follows the pattern observed in these supply chain attacks.
Detects UNC6240 PSEMHUB.war web shell/tunnel/trojanized installer artifacts by distinctive content markers (x.jsp, u.jsp, tunnel.jsp/jspx, Ple64.exe)
Detects Neo-reGeorg tunnel.jsp/tunnel.jspx servlets used by UNC6240 to establish SOCKS5-over-HTTP(S) tunneling from compromised PeopleSoft PSEMHUB.war hosts
Detects instances where the Claude Desktop application spawns a terminal or shell process that immediately executes commands associated with downloading remote payloads or accessing sensitive cryptocurrency wallet artifacts. This behavior is indicative of potential AI prompt injection where an AI assistant is coerced into executing malicious commands without user authorization.
This rule detects potential backdoor deployment or persistence mechanisms in AI coding assistants like Claude Code and Cursor. It identifies when specific configuration or hook files (e.g., settings.json, hooks.js) are modified, followed within a two-hour window by the execution of suspicious child processes (e.g., powershell.exe, curl.exe, python) initiated by the coding assistant's CLI tool.
Detects the creation of potential hook or startup scripts within hidden AI coding assistant directories (.claude, .vscode, .cursor) followed by the execution of a process from those same directories. This pattern is consistent with supply chain compromises where trojanized extensions or MCP servers are leveraged for code execution.
Detects incoming web requests containing a 'pagename' parameter with URL-encoded path traversal sequences, which could allow unauthorized file access or directory traversal attacks against WordPress page-template resolution as described in CVE-2026-87902.
Detects the execution of processes named 'nohup' with arguments suggesting renderer masquerading ('--type=renderer') containing suspicious terms like 'SystemUpdate' or 'iSync', originating from Cursor IDE helper processes or the terminal shell. This behavior is indicative of a backdoor or malicious process attempting to hide in plain sight by masquerading as legitimate IDE rendering components.
Experimental behavioral hunt for a root-owned shell or interpreter started by a non-root initiating account on explicitly inventoried ISE devices. This identifies an account-context transition in process telemetry; it does not establish preceding exploitation, setuid abuse, or a specific Cisco CVE. Requires verified appliance process telemetry.
Detects the registration or installation of an MCP (Model Context Protocol) server or agent tool containing suspicious prompt-injection strings (e.g., instructions to ignore safety guardrails or role overrides), immediately followed by the execution of shell commands or unauthorized network connections originating from that tool.
Detects unauthorized modifications to AI agent configuration files, including system prompts, tool allow-lists, and MCP server registration files. Such changes are often performed by processes outside of approved configuration management or infrastructure-as-code pipelines, potentially allowing for persistent manipulation of AI model behavior and capabilities.
Detects outbound HTTPS connections to major generative AI inference endpoints originating from non-browser, non-development tool processes at regular intervals. This activity is indicative of beaconing behavior, where malware (specifically families like LAMEHUG) leverages LLM APIs for dynamic command generation, payload obfuscation, or C2 instruction retrieval, bypassing traditional security controls.
Detects network connections from server or workload identities (excluding SYSTEM) to known public Generative-AI inference API domains. This may indicate the use of AI services for data exfiltration, automated content generation, or C2 communication via legitimate web services.
Detects a two-stage activity: first, the potential unauthorized reading or access of LLM provider API keys from files, environment variables, or command-line arguments; and second, the subsequent use of those same credentials to authenticate to LLM provider APIs (OpenAI, Anthropic, Azure, Bedrock) from a different, unrecognized source IP address, indicating potential credential theft and session hijacking.
Detects exploitation attempts by the CARBONATO botnet targeting exposed Docker daemons. The rule monitors for container escape techniques using 'nsenter' to access host namespaces, the execution of specific malicious entrypoint scripts, the use of known malicious container image references, and the creation of privileged containers with host bind mounts, which are indicative of host filesystem and network compromise.
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