DeepZero is an automated vulnerability research pipeline engine, primarily targeting Windows kernel driver (BYOVD) analysis. It provides a highly concurrent, resumable orchestration framework where pipelines are defined declaratively in YAML. The engine supports stages: ingest, map (parallel analysis), reduce (aggregation), and bulk_map, with built-in fault tolerance, atomic state persistence, and live progress dashboards. It integrates external tools like Ghidra (headless decompilation), Semgrep (static analysis), LIEF (PE parsing), and LLM backends (LiteLLM, Claude Code) for exploitability assessment. The repository includes a full reference pipeline (loldrivers) and multiple language documentation sites. While primarily an application framework, it has strong data research characteristics due to its focus on binary corpus analysis and heuristic/AI assessment.
This repository is an educational tutorial for learning LangChain, LangGraph, and Deep Agents frameworks. It contains two tracks: 101 (fundamentals) and 201 (production patterns) with Jupyter notebooks and standalone agents runnable via `langgraph dev`. The code demonstrates multi-agent supervision, human-in-the-loop interrupts, middleware hooks, MCP tool integration, and a deep research agent with skills and memory. All agents use mock or simulated data (Chinook SQLite, Tavily search) and are designed for learning rather than production. The architecture centers on a centralized model configuration (`utils/models.py`) that supports multiple LLM providers, and reusable patterns like subgraph composition, dynamic prompts, and composite backends. While the code is educational and lacks production hardening (error handling, testing, security), it provides clear, well-commented examples of advanced agent patterns.