Release v0.0.0

castiel - v0.0.0

castiel is an AI-assisted penetration testing harness. It pairs a human engagement lead with an AI operator that handles the technical workload. Probing targets, reasoning about findings, and keeping a structured record of the entire engagement, while the human keeps full control over scope, phase, and authorization.

This is the first public release of castiel.

• AI operator with a full tool-calling loop: run shell commands, supervise background processes, read/write/edit files, search the web, and search the workspace.
• Currently supports llama.cpp, Ollama and OpenRouter for LLM providers.
• Five-phase engagement model (planning, recon, scanning, exploitation, wrap-up) that stays inside the active phase; the human triggers every phase transition.
• Findings recorded in plain JSON documents with CVSS scoring, evidence, and full provenance, so the engagement builds a clean, reviewable record.
• Extensible through MCP servers, picked up live without a restart, alongside the built-in tools.
• Workstation-style interface: streaming chat with reasoning, tool-call detail, cited sources, code highlighting; a file tree toggling raw files and rendered views; a live background-process panel; and a dedicated view per document. Network topology, web-app surface, and a CVSS gauge with a drillable findings table.