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LLM-augmented reverse engineering extension for Ghidra

Published at
3 days ago

GhidrAssist

Author: Jason Tang

A plugin that provides LLM helpers to explain code and assist in RE.

Support Continued Improvements

Description:

This is a LLM plugin aimed at enabling the use of local LLM's (ollama, text-generation-webui, lm-studio, etc) for assisting with binary exploration and reverse engineering. It supports any OpenAI v1-compatible API. Recommended models are LLaMA-based models such as llama3.1:8b, but others such as DeepSeek and ChatGPT work as well.

Current features include:

  • Explain the current function - Works for disassembly and pseudo-C.
  • Explain the current instruction - Works for disassembly and pseudo-C.
  • General query - Query the LLM directly from the UI.
  • Propose actions - Provide a list of proposed actions to apply.
  • Function calling - Allow agent to call functions to navigate the binary, rename functions and variables.
  • RAG augmentation - Supports adding contextual documents to refine query effectiveness.
  • RLHF dataset generation - To enable model fine tuning.
  • Settings to modify API host, key, model name and max tokens.

Future Roadmap:

  • Agentic assistant - Use Autogen or similar framework for self-guided binary RE.
  • Model fine tuning - Leverage the RLHF dataset to fine tune the model.

Screenshot

Screenshot Screenshots

Quickstart

  • If necessary, copy the binary release ZIP archive to the Ghidra_Install/Extensions/Ghidra directory.
  • Launch Ghidra -> File -> Install Extension -> Enable GhidrAssist.
  • Load a binary and launch the CodeBrowser.
  • CodeBrowser -> File -> Configure -> Miscellaneous -> Enable GhidrAssist.
  • CodeBrowser -> Tools -> GhidraAssist Settings.
  • Ensure the RLHF and RAG database paths are appropriate for your environment.
  • Point the API host to your preferred API provider and set the API key.
  • Open GhidrAssist with the GhidrAssist option in the Windows menu and start exploring.

LLMs

General LLM setup is a bit outside the scope of this project since there's so many different options and there are plenty of sources that cover the topic much better than I could. It assumes one already has access to an OpenAI-compatible API provider. Here's a few resources that might get you started:

For local LLM's, I've found that the Llama3.3:70b, Llama3.1:8b and DeepSeek-r1 produce good results. From OpenAI, the gpt-4o-mini produces good results. I've not yet tested Claude, but I expect it would work fine as well.

Homepage

https://github.com/jtang613/GhidrAssist

Minimum Version

This plugin requires the following minimum version of Ghidra:

  • 11.0

License

This plugin is released under a MIT license.

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