RecodeAI

Recode AI: Turning Complexity Into ClarityWhat if understanding binary files was as easy as reading a book? Welcome to Recode AI—the future of reverse engineering.

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Inspiration

The journey to Recode AI began with a clear realization: decompiling and analyzing binary files is an immensely challenging task. Tools like Ghidra are powerful but still produce cryptic outputs that require expert-level knowledge to interpret. This creates barriers not only for beginners but also slows down seasoned experts. We wanted to build something that could bridge this gap, making reverse engineering accessible, efficient, and scalable—an AI-driven platform that transforms complexity into clarity. Our inspiration comes from empowering both professionals and enthusiasts to decode binaries with ease and confidence.

What it does

Recode AI is a revolutionary decompilation and analysis tool designed to:

  • Seamlessly decompile binary files into human-readable source code.
  • Augment decompiled code with AI-generated insights, such as variable names, comments, and logical explanations.
  • Provide a multi-language translation feature to convert decompiled code into your preferred programming language.
  • Serve both experts and beginners, enhancing workflows for professionals and making reverse engineering approachable for newcomers.
  • Leverage Azure’s scalable cloud services for efficient processing, ensuring a seamless user experience.

How we built it

Recode AI is powered by an innovative tech stack and a carefully architected workflow:

  • Frontend: Built with React and Vite, delivering an intuitive and responsive user interface.
  • Backend: A Go-based lightweight server containerized with Docker.
  • Decompilation Core: Ghidra is containerized and orchestrated through Azure Container Instances (ACI) to handle decompilation tasks.
  • AI Insights: We utilized AI models to enhance the decompiled output by renaming variables, simplifying logic, and generating comments.
  • Cloud Infrastructure:
    • Azure Blob Storage: For secure and scalable file storage.
    • Azure Functions: Serverless triggers manage the flow of data between services.
    • Azure Container Instances (ACI): Dynamically scales to run Ghidra and AI workloads efficiently.

Challenges we ran into

Building Recode AI presented several challenges:

  1. Containerizing Ghidra: Running Ghidra within a container while ensuring stable performance required careful configuration and optimization.
  2. Scalability: Orchestrating Azure services like Blob Storage, Functions, and ACI to work together seamlessly and scale dynamically.
  3. AI Integration: Mapping decompiled outputs to meaningful AI-enhanced insights.
  4. User Experience: Balancing the complexity of the backend with a frontend that remains simple and intuitive for diverse users.
  5. Performance Optimization: Minimizing processing delays to ensure the system remains responsive under load.

Accomplishments that we're proud of

  • Successfully containerized and orchestrated Ghidra with Azure services, creating a scalable, cost-effective, and serverless architecture.
  • Seamlessly integrated AI-generated insights to enhance the readability and usability of decompiled outputs.
  • Built a robust workflow that automates file handling, processing, and result delivery through Azure Functions and Blob Storage.
  • Developed an intuitive UI that caters to both experienced developers and beginners.
  • Demonstrated the potential to make reverse engineering faster, more accessible, and impactful across industries.

What we learned

  • Cloud Scalability: Leveraging Azure’s serverless architecture taught us the power of dynamic scaling and cost-efficient resource allocation.
  • Reverse Engineering Insights: Gaining a deeper understanding of the challenges faced in decompilation and how AI can simplify them.
  • Cross-Functional Integration: Successfully marrying traditional tools like Ghidra with modern AI models to create a cohesive platform.
  • User-Centric Design: Ensuring the tool remains intuitive and accessible while addressing complex problems.

What's next for Recode AI

  • Enhanced AI Models: Integrating more advanced AI models to improve insights and generate more accurate, meaningful code structures.
  • Expanded File Support: Supporting more file types beyond binaries, like firmware and obfuscated scripts.
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