With the successful launch of the Phishing Detection Framework, we’re excited to share our roadmap for future development:

1. Multilingual Support: Expanding detection capabilities for non-English inputs.
2. Customizable Models: Allow users to fine-tune the models for specific needs.
3. Real-Time Detection: Integrating with APIs for real-time phishing analysis.

We’d love to hear your ideas! Contribute or share feedback on GitHub Discussions.

Let’s continue improving and making the internet safer together!

The Phishing Detection Framework is powered by state-of-the-art machine learning models hosted on Hugging Face:

• URL Detection: bert-finetuned-phishing
• Email Detection: phishing-email-detection-distilbert_v2.4.1

These models are fine-tuned for phishing detection, offering high accuracy and reliability. They analyze:

1. URLs: Scanning for known phishing patterns.
2. Email content: Identifying deceptive language or malicious intent.

Learn more in the API Reference

We're thrilled to announce the release of the Phishing Detection Framework! 🚀

This open-source Python library leverages cutting-edge machine learning models to detect phishing attempts in URLs and emails. Key features include:

• Pre-trained models for high accuracy.
• Batch processing for analyzing multiple inputs.
• Flexible API for integration into your workflows.

Explore the documentation to get started, or check out the GitHub repository to contribute.

Let’s build a safer internet together!