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A procedurally generated dataset of cryptographic CTF challenges for training and evaluating LLM agents with Reinforcement Learning.

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Random-Crypto

License: MIT arXiv:2506.02048

The Random-Crypto Benchmark is a procedurally generated dataset of cryptographic CTF challenges. The benchmark was designed for reinforcement learning of LLM based agents.

The benchmark's website can be visited here.

  • ✅ 50 Human-verified challenges for evaluation (link)
  • ⚙️ 5000 Non-Verified Challenges for training (link)

⚙️ Generating New Challenges

Set up the environment:

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate 

# Install dependencies
pip install -r requirements.txt

Make sure to set your OpenAI API key in a .env file at the root of this folder:

OPENAI_API_KEY=your-key-here

Example Usage

This code generates 50 challenges, one from each type.

python main.py --variants 1 --output_folder my_generated_challenges

This code generates 5000 challenges, one hundred from each type.

python main.py --variants 100 --output_folder my_generated_challenges

Contributors

How To Cite

@article{muzsai2025improving,
  title={Improving LLM Agents with Reinforcement Learning on Cryptographic CTF Challenges},
  author={Muzsai, Lajos and Imolai, David and Luk{\'a}cs, Andr{\'a}s},
  journal={arXiv preprint arXiv:2506.02048},
  year={2025}
}

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A procedurally generated dataset of cryptographic CTF challenges for training and evaluating LLM agents with Reinforcement Learning.

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