This repository provides an all-in-one CLI/TUI application for launching and managing security testing tools. It features a curated catalog of 215+ tools across 21 categories, defined declaratively in YAML files and loaded into Python tool classes. The interactive REPL supports commands like /run, /search, /tags, /ai, /goal, and /find, with a rich console interface using prompt_toolkit and Rich. A headless engagement mode runs YAML-defined pipelines (e.g., subfinder → httpx → nuclei) and generates structured findings and Markdown reports. AI features are opt-in and use OpenAI-compatible endpoints or local Ollama, with built-in safety guardrails (charter injection, sanitization, anti-fabrication checks) and graceful degradation to offline behavior. The architecture is monolithic but modular, with clear separation between the tool catalog, execution engine, AI integration, and discovery module. The codebase demonstrates strong engineering practices: safe subprocess execution (list-form, cwd, skip if present), declarative YAML overlays, a fixed tag taxonomy enforced by tests, and extensive test coverage including monkeypatching of subprocess and AI transport. While the catalog inherently drifts as upstream tools become archived, the project includes audit scripts to manage this. Overall, it is a well-crafted, production-quality application for authorized security testing.
This repository is a comprehensive, curated collection of cybersecurity references, scripts, tools, code, labs, and training resources, primarily authored by Omar Santos. It serves as supplemental material for his books, video courses, and live training, covering a vast range of domains including offensive security, defensive security, application security, cloud/container security, hardware/embedded security, AI/ML security, and certification preparation (Cisco, CompTIA, ISC2, etc.). The repo is hybrid in nature: while it contains hundreds of runnable scripts and tools (e.g., network scanners, exploit examples, API security testers, AI-powered log analyzers), its dominant character is that of an educational knowledge base and reference library rather than a deployable application. The content is organized into clear domain directories, with extensive READMEs acting as curated indexes of tools, papers, talks, and labs. The AI security section is particularly well-developed, including course materials on agentic AI, prompt engineering, and the Foundry Security Spec. The repository is actively maintained, with recent commits and automated CI workflows, though the breadth of content introduces risks of link rot and technology churn in fast-moving areas like AI frameworks and certification blueprints.