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Description

Open-source AI reverse-engineering agent using Ghidra and LLMs to reconstruct and validate C/C++ functions from binaries.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

auto-re-agent

[![PyPI](https://img.shields.io/pypi/v/auto-re-agent)](https://pypi.org/project/auto-re-agent/) [![Python](https://img.shields.io/pypi/pyversions/auto-re-agent)](https://pypi.org/project/auto-re-agent/) [![CI](https://github.com/Dryxio/auto-re-agent/actions/workflows/ci.yml/badge.svg)](https://github.com/Dryxio/auto-re-agent/actions/workflows/ci.yml) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)

`auto-re-agent` is an open-source AI reverse-engineering agent that uses Ghidra and LLMs—including Claude, Codex, and OpenAI-compatible models—to reconstruct and validate C/C++ functions from compiled binaries. It combines independent reverser/checker models, agentic evidence gathering, candidate build and test gates, structural verification, and parity analysis in one autonomous workflow.

Original pre-0.2 demo: [YouTube](https://youtu.be/zBQJYMKmwAs?si=emi1kDsJ81-2-tc3)

What it does

re-agent reverse --class CTrain
    │
    ├── Configuration (YAML + supported environment overrides + CLI flags)
    ├── Function selection (dependency-order | easiest-first | high-impact)
    ├── Source and binary context
    │   ├── decompile, xrefs, structs, enums, vtables, globals, and strings
    │   └── normalized high P-code, CFG, assembly, and nearby project source
    ├── Reverser → checker → fix loop (bounded rounds and investigations)
    ├── Conservative structural verifier
    ├── Candidate overlay
    │   └── configured build, test, and runtime gates
    ├── Candidate parity gate (GREEN | YELLOW | RED)
    └── Reports, per-round logs, session history, and knowledge graph

The tool generates candidate C/C++ implementations; it does not patch the original source tree automatically. A successful reversal can require four independent conditions:

  1. the LLM checker returns PASS;
  2. the objective verifier finds no strong structural mismatch;
  3. candidate validation satisfies the configured acceptance policy;
  4. pari