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---
license: apache-2.0
task_categories:
- question-answering
language:
- en
tags:
- Reasoning
- LLM
- Encryption
- Decryption
size_categories:
- 1K<n<10K
configs:
- config_name: Rot13
data_files:
- split: test
path: data/Rot13.jsonl
- config_name: Atbash
data_files:
- split: test
path: data/Atbash.jsonl
- config_name: Polybius
data_files:
- split: test
path: data/Polybius.jsonl
- config_name: Vigenere
data_files:
- split: test
path: data/Vigenere.jsonl
- config_name: Reverse
data_files:
- split: test
path: data/Reverse.jsonl
- config_name: SwapPairs
data_files:
- split: test
path: data/SwapPairs.jsonl
- config_name: ParityShift
data_files:
- split: test
path: data/ParityShift.jsonl
- config_name: DualAvgCode
data_files:
- split: test
path: data/DualAvgCode.jsonl
- config_name: WordShift
data_files:
- split: test
path: data/WordShift.jsonl
---
# CipherBank Benchmark
## Benchmark description
CipherBank, a comprehensive benchmark designed to evaluate the reasoning capabilities of LLMs in cryptographic decryption tasks.
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.
## Model Performance
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.
| **Model** | **CipherBank Score (%)**|
|--------------|----|
|Qwen2.5-72B-Instruct |0.55 |
|Llama-3.1-70B-Instruct |0.38 |
|DeepSeek-V3 | 9.86 |
|GPT-4o-mini-2024-07-18 | 1.00 |
|GPT-4o-2024-08-06 | 8.82 |
|gemini-1.5-pro | 9.54 |
|gemini-2.0-flash-exp | 8.65|
|**Claude-Sonnet-3.5-1022** | **45.14** |
|DeepSeek-R1 | 25.91 |
|gemini-2.0-flash-thinking | 13.49 |
|o1-mini-2024-09-12 | 20.07 |
|**o1-2024-12-17** | **40.59** |
## Please see paper & website for more information:
- [https://arxiv.org/abs/2504.19093](https://arxiv.org/abs/2504.19093)
- [https://cipherbankeva.github.io/](https://cipherbankeva.github.io/)
## Citation
If you find CipherBank useful for your research and applications, please cite using this BibTeX:
```bibtex
@misc{li2025cipherbankexploringboundaryllm,
title={CipherBank: Exploring the Boundary of LLM Reasoning Capabilities through Cryptography Challenges},
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},
year={2025},
eprint={2504.19093},
archivePrefix={arXiv},
primaryClass={cs.CR},
url={https://arxiv.org/abs/2504.19093},
}
```
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