https://github.com/offrange/passstrengthai
Open-source project that utilizes machine learning techniques to estimate the strength of passwords.
https://github.com/offrange/passstrengthai
ai machine-learning password-security password-strength
Last synced: 6 months ago
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Open-source project that utilizes machine learning techniques to estimate the strength of passwords.
- Host: GitHub
- URL: https://github.com/offrange/passstrengthai
- Owner: OffRange
- License: mit
- Created: 2023-06-02T14:34:00.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-03T13:59:14.000Z (over 2 years ago)
- Last Synced: 2024-12-28T03:42:14.730Z (about 1 year ago)
- Topics: ai, machine-learning, password-security, password-strength
- Language: Python
- Homepage: https://offrange.github.io/projects/password-strength-ai
- Size: 13.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Code of conduct: CODE_OF_CONDUCT.md
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README
# Password Strength Estimation AI
Password Strength Estimation AI is an open-source project that utilizes machine learning techniques to estimate the strength of passwords. The AI model is trained on a large dataset of randomly generated passwords, labeled using the zxcvbn password estimation library. This project is implemented using TensorFlow.
## Disclaimer
**The AI model is currently in beta state and may produce inaccurate predictions of password strength. Use the results with caution and always consider additional security measures.**
## Features
- Estimates the strength of passwords using machine learning.
- Trained on a diverse dataset of randomly generated passwords.
- Includes cracked passwords from SecLists to enhance the training dataset.
- Created with TensorFlow for robust and efficient computation.
## Usage
To train the AI model or load a pre-trained model, follow the instructions below:
### Prerequisites
- Python 3.x
- TensorFlow library
- Other required Python packages (`pip install -r requirements.txt`)
### Training
1. Provide a `config.json` file in the root directory of the project. Alternatively, use the `--config ` parameter to specify the configuration file's path.
2. In the `config.json` file, specify the following keys:
- `cracked_passwords_url`: URL to an online `.txt` file containing cracked passwords.
- `csv_password_dataset`: Path to a local `.csv` file containing passwords and their strength score from 0 to 4.
3. Execute the training process using the following command: `python pass_strength_ai.py --train `
### Use a pre-trained model
To estimate passwords using a trained model, follow these steps:
1. Download a pretrained model [here](https://github.com/OffRange/PassStrengthAI/releases)
2. Execute the loading process using the following command: `python pass_strength_ai.py --execute `
## Contributing
Contributions to this project are highly appreciated. You can contribute in the following ways:
- Report issues or suggestions for improvement.
- Submit pull requests to enhance the functionality or codebase.
- Share additional password datasets for further training and evaluation.
Please review the [CONTRIBUTING.md](CONTRIBUTING.md) file for more information on how to contribute to this project.
## License
This project is licensed under the [MIT License](LICENSE.md).