metadata

license: apache-2.0
title: EmailGuard2
sdk: gradio
emoji: 🌍
colorFrom: blue
colorTo: pink
short_description: The only secure and rational email phishing detector

EmailGuard2 : Advanced Phishing Detection System

A multi-model ensemble system for detecting phishing attempts in emails, URLs, and text messages using AI and feature engineering.

Features

Multi-model ensemble prediction
Advanced feature extraction and analysis
Real-time phishing detection
Web-based user interface
Risk scoring and confidence reporting
URL and email content analysis

Installation

Clone the repository:

git clone <repository-url>
cd emailguard-phishing-detection

Install dependencies:

pip install -r requirements.txt

Run the application:

python app.py

Open your browser and go to http://localhost:7860

Usage

Enter email content, URL, or suspicious text in the input field
Click "Advanced Analysis" to process the input
Review the results including risk level and confidence scores

Models Used

Primary: cybersectony/phishing-email-detection-distilbert_v2.4.1
URL Specialist: Custom URL analysis model
Feature Engine: Hand-crafted pattern detection rules

Detection Features

URL Analysis

Suspicious domain detection
Shortened URL identification
Malicious link patterns

Content Analysis

Urgency keyword detection
Money-related terms
Personal information requests
Spelling error patterns
Excessive capitalization

Risk Assessment

HIGH RISK: Strong phishing indicators (>60% confidence)
MEDIUM RISK: Suspicious patterns (30-60% confidence)
LOW RISK: Appears legitimate (<30% confidence)

System Requirements

Python 3.8+
4GB+ RAM
Internet connection (for initial model download)

Technical Details

The system uses:

PyTorch for deep learning models
Transformers for NLP processing
Gradio for web interface
Custom ensemble voting mechanism
Feature-based risk adjustment

Example Inputs

Phishing Example:

URGENT: Your PayPal account has been limited! Verify immediately at http://paypal-security-check.suspicious.com/verify

Legitimate Example:

Hi Sarah, Thanks for the quarterly report. Let's discuss in tomorrow's meeting. Best, Mike

Configuration

Model configuration in app.py:

MODELS = {
    "primary": "cybersectony/phishing-email-detection-distilbert_v2.4.1",
    "url_specialist": "cybersectony/phishing-email-detection-distilbert_v2.4.1"
}

Limitations

This is an educational/research tool
Always verify suspicious content through official channels
May produce false positives/negatives
Requires manual verification for critical decisions

License

Apache2.0 License

Contributing

Fork the repository
Create a feature branch
Make your changes
Submit a pull request

Support

For issues and questions, please use the GitHub issue tracker.