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--- |
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language: |
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- en |
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license: apache-2.0 |
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size_categories: |
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- 1K<n<10K |
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task_categories: |
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- question-answering |
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tags: |
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- Reasoning |
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- LLM |
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- Encryption |
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- Decryption |
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configs: |
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- config_name: Rot13 |
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data_files: |
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- split: test |
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path: data/Rot13.jsonl |
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- config_name: Atbash |
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data_files: |
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- split: test |
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path: data/Atbash.jsonl |
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- config_name: Polybius |
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data_files: |
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- split: test |
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path: data/Polybius.jsonl |
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- config_name: Vigenere |
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data_files: |
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- split: test |
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path: data/Vigenere.jsonl |
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- config_name: Reverse |
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data_files: |
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- split: test |
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path: data/Reverse.jsonl |
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- config_name: SwapPairs |
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data_files: |
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- split: test |
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path: data/SwapPairs.jsonl |
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- config_name: ParityShift |
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data_files: |
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- split: test |
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path: data/ParityShift.jsonl |
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- config_name: DualAvgCode |
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data_files: |
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- split: test |
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path: data/DualAvgCode.jsonl |
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- config_name: WordShift |
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data_files: |
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- split: test |
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path: data/WordShift.jsonl |
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--- |
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# CipherBank Benchmark |
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## Benchmark description |
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CipherBank, a comprehensive benchmark designed to evaluate the reasoning capabilities of LLMs in cryptographic decryption tasks. |
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CipherBank comprises 2,358 meticulously crafted problems, covering 262 unique plaintexts across 5 domains and 14 subdomains, with a focus on privacy-sensitive and real-world scenarios that necessitate encryption. From a cryptographic perspective, CipherBank incorporates 3 major categories of encryption methods, spanning 9 distinct algorithms, ranging from classical ciphers to custom cryptographic techniques. |
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## Model Performance |
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We evaluate state-of-the-art LLMs on CipherBank, e.g., GPT-4o, DeepSeek-V3, and cutting-edge reasoning-focused models such as o1 and DeepSeek-R1. Our results reveal significant gaps in reasoning abilities not only between general-purpose chat LLMs and reasoning-focused LLMs but also in the performance of current reasoning-focused models when applied to classical cryptographic decryption tasks, highlighting the challenges these models face in understanding and manipulating encrypted data. |
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| **Model** | **CipherBank Score (%)**| |
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|--------------|----| |
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|Qwen2.5-72B-Instruct |0.55 | |
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|Llama-3.1-70B-Instruct |0.38 | |
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|DeepSeek-V3 | 9.86 | |
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|GPT-4o-mini-2024-07-18 | 1.00 | |
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|GPT-4o-2024-08-06 | 8.82 | |
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|gemini-1.5-pro | 9.54 | |
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|gemini-2.0-flash-exp | 8.65| |
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|**Claude-Sonnet-3.5-1022** | **45.14** | |
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|DeepSeek-R1 | 25.91 | |
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|gemini-2.0-flash-thinking | 13.49 | |
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|o1-mini-2024-09-12 | 20.07 | |
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|**o1-2024-12-17** | **40.59** | |
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## Please see paper & website for more information: |
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- [Paper](https://huggingface.co/papers/2504.19093) |
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- [https://arxiv.org/abs/2504.19093](https://arxiv.org/abs/2504.19093) |
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- [https://cipherbankeva.github.io/](https://cipherbankeva.github.io/) |
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## Citation |
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If you find CipherBank useful for your research and applications, please cite using this BibTeX: |
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```bibtex |
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@misc{li2025cipherbankexploringboundaryllm, |
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title={CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges}, |
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author={Yu Li and Qizhi Pei and Mengyuan Sun and Honglin Lin and Chenlin Ming and Xin Gao and Jiang Wu and Conghui He and Lijun Wu}, |
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year={2025}, |
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eprint={2504.19093}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CR}, |
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url={https://arxiv.org/abs/2504.19093}, |
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} |
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``` |
