Red Cell Pen test AI agent

Red Cell is an AI-powered autonomous penetration testing agent built on the Temporal workflow engine. It orchestrates end-to-end security assessments by combining real offensive security tools — Nmap, Nuclei, Subfinder, Httpx — with LLM-driven reasoning to discover, analyze, and verify vulnerabilities across target infrastructure. The agent progresses through a 14-state workflow: accepting natural language target definitions, enumerating subdomains and assets, mapping the attack surface with port scanning and API discovery (OpenAPI, GraphQL, REST), gathering real-time threat intelligence, and performing AI-driven vulnerability analysis. At its core, an agentic loop lets the LLM observe responses, reason about what to test next, and execute security checks autonomously — enabling discovery of business logic flaws, attack chains, and novel vulnerability patterns beyond what template-based scanners catch. Human approval gates ensure high-impact exploits require explicit authorization before execution. A built-in memory and learning system stores successful techniques and payloads, improving effectiveness across engagements. Comprehensive reporting delivers executive summaries, technical findings with reproduction steps, and remediation guidance