Phishing Detection Framework

Overview

The Phishing Detection Framework provides an easy-to-use Python library for detecting phishing attempts in URLs and email messages. It leverages state-of-the-art machine learning models from Hugging Face to ensure high accuracy and reliability.

Key Features

• Dual Detection Modes: Supports both URL and email phishing detection.
• Pre-trained Models: Uses advanced models for performance:
  • bert-finetuned-phishing
  • phishing-email-detection-distilbert_v2.4.1
• Batch Processing: Handle multiple inputs efficiently.
• Developer Friendly: Flexible API for seamless integration and customization.
• Open-Source: Built for developers by developers.

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🚀 Get Started

Installation

Install the library using pip:

pip install phishing-detection-py

For detailed installation steps and dependency management, visit the Installation Guide.

Quick Start Example

from phishing_detection_py import PhishingDetector

detector = PhishingDetector(model_type="url")
result = detector.predict("http://example-phishing-site.com")
print(result)
# Output: [{'input': 'http://example-phishing-site.com', 'label': 'phishing', 'confidence': 0.98}]

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📖 Documentation

Comprehensive documentation for setup, API usage, and customization is available:

👉 Phishing Detection Framework Documentation

Highlights include:

• API Reference
• Installation Guide
• Usage Examples

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🤝 Contributing

We welcome contributions to improve the Phishing Detection Framework! Get started by reviewing our Contributing Guide.

How to Contribute

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -m "Add new feature").
4. Push to the branch (git push origin feature-name).
5. Open a Pull Request.

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🛡️ License

This project is licensed under the Apache License 2.0. See the LICENSE file for more details.

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🙏 Acknowledgments

• Hugging Face for providing pre-trained models and tools.
• Inspiration from the cybersectony and ealvaradob models.

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Let's build a safer internet together! 🌐✨