https://github.com/edolor/cipherwhisperer
Cipher Whisperer is a state-of-the-art tool built with LangGraph that automates the process of detecting and decrypting ciphers embedded in text.
https://github.com/edolor/cipherwhisperer
aiagents cipher-algorithms ciphertext langchain langgraph openai
Last synced: 8 days ago
JSON representation
Cipher Whisperer is a state-of-the-art tool built with LangGraph that automates the process of detecting and decrypting ciphers embedded in text.
- Host: GitHub
- URL: https://github.com/edolor/cipherwhisperer
- Owner: Edolor
- License: mit
- Created: 2025-04-10T18:47:21.000Z (13 days ago)
- Default Branch: master
- Last Pushed: 2025-04-10T19:57:02.000Z (13 days ago)
- Last Synced: 2025-04-15T01:18:07.744Z (8 days ago)
- Topics: aiagents, cipher-algorithms, ciphertext, langchain, langgraph, openai
- Language: Python
- Homepage:
- Size: 38.1 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
Awesome Lists containing this project
README
# Cipher Whisperer
## Overview
Cipher Whisperer is a software project that aims to decrypt and analyze cipher texts using a graph-based approach. The project utilizes various software libraries and tools to process and transform the input text.
Graph Architecture above.
## Software and Libraries Used
* Python 3 as the primary programming language
* `dotenv` for environment variable management
* `langgraph` for graph-based processing and transformation
* `langchain_core` and `langchain_openai` for natural language processing and AI-powered decryption
* `pydantic` for data validation and parsing
## Decryptors
The project features a range of decryptors, including:
* BruteForceDecryptor: a brute-force decryptor that uses a list of English words to decrypt Caesar ciphers
* Other decryptors (to be added in future updates)
## Getting Started
### Prerequisites
* Python 3
* Required libraries: `dotenv`, `langgraph`, `langchain_core`, `langchain_openai`, `pydantic`
### Installation
1. Clone this repository.
2. Create a virtual environment.
3. Install the required libraries: `pip install -r requirements.txt`
4. Create a `.env` file with your environment variables (i.e. API keys) following the `.env.example` file
### Running the Code
1. Run the main script: `python main.py`
2. Follow the prompts to input a cipher text and receive the decrypted output
## Project Structure
* `cipherwhisperer/`: main project directory
+ `main.py`: entry point for the project
+ `graph.py`: graph-based processing and transformation of input text
+ `chains.py`: chain-based processing and transformation of input text
+ `models.py`: data models for the project (e.g. `GraphState`)
+ `decryptors.py`: decryptor implementations (e.g. BruteForceDecryptor)
+ `.gitignore`: ignore file for Git
## Contributing
Contributions are welcome! Please submit a pull request with your changes and a brief description of what you've added or fixed.
## License
This project is licensed under the MIT License. See `LICENSE` for details.
## Reference
1. Yuan, Y., Jiao, W., Wang, W., Huang, J., He, P., Shi, S., & Tu, Z. (2024). GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher. In The Twelfth International Conference on Learning Representations [Link Here](https://openreview.net/forum?id=MbfAK4s61A).