🔍 Privacy Forensics

X-ray vision for privacy policies - Instant risk scores for the terms you'll never read

Privacy Forensics transforms impenetrable legal documents into clear, actionable privacy risk scores. Stop blindly clicking "I Agree" - know the risks first.

✨ Features

🎯 Core Analysis

• Four Risk Categories: Data Resale, Biometric Collection, Indefinite Retention, Vague Language
• AI-Enhanced Validation: GPT-4o validates findings against GDPR regulations
• Specific Citations: Get exact GDPR article references (e.g., "Article 5(1)(b) - Purpose Limitation")
• Visual Dashboard: Color-coded risk scores (0-100) with interactive charts
• Clause-Level Breakdown: See exactly which sentences triggered each flag

🌐 Browser Extension

• Auto-Detection: Recognizes privacy policy pages automatically
• Instant Risk Badges: See privacy scores without leaving the page
• Permission Alerts: Flags camera, microphone, location, and biometric data requests
• One-Click Analysis: Send policies to web app for detailed forensics

📊 Real Results

Company	Risk Score	Category	Key Issues
WhatsApp	38.4	Medium	Vague language (strong encryption)
LinkedIn	30.5	Medium	Transparent data monetization
TikTok	65.3	High	Extensive collection + ad targeting

🚀 Quick Start

Prerequisites

• Python 3.11+
• Node.js 18+
• Backboard.io API key (Get one here)

Backend Setup

# Clone the repository
git clone https://github.com/yourusername/privacy-forensics.git
cd privacy-forensics/backend

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# Mac/Linux:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Configure API key
cp .env.example .env
# Edit .env and add your Backboard.io API key

# Run backend
python app.py

Backend runs on http://localhost:5000

Frontend Setup

cd frontend

# Install dependencies
npm install

# Run development server
npm run dev

Frontend runs on http://localhost:5173

## 🎮 Usage Examples

### Web Application

1. **Paste a privacy policy** into the text area
2. **(Optional)** Enable AI Enhancement for GDPR validation
3. **Click "Analyze Policy"**
4. **View results**: Overall score + category breakdown + flagged clauses

### API Endpoint
```bash
curl -X POST http://localhost:5000/analyze \
  -H "Content-Type: application/json" \
  -d '{
    "policy": "Your privacy policy text here...",
    "use_ai": true
  }'

Response:

{
  "overall": {"score": 65.3, "risk_level": "high"},
  "data_resale": {
    "score": 100,
    "matches": [
      {
        "text": "We share data with advertisers...",
        "matched_keyword": "advertisers",
        "ai_validation": "YES - conflicts with GDPR Article 6(1)(a)..."
      }
    ]
  }
}

🛠️ Technology Stack

Frontend

• React 18 + Vite
• Tailwind CSS
• Chart.js + react-chartjs-2
• Axios

Backend

• Flask (Python)
• Requests
• Python-dotenv

AI/ML

• Backboard.io API
• GPT-4o
• Regex pattern matching

🧪 Testing

We validated against real-world privacy policies:

# Test with sample policies
cd backend
python -c "
from risk_analyzer import RiskAnalyzer
analyzer = RiskAnalyzer()
with open('test_policies/whatsapp.txt') as f:
    result = analyzer.analyze(f.read())
    print(f\"Risk Score: {result['overall']['score']}\")
"

🤝 Contributing

We welcome contributions! Here's how:

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

Development Guidelines

• Follow PEP 8 for Python code
• Use ESLint rules for JavaScript
• Add tests for new features
• Update documentation

🗺️ Roadmap

v1.1 (Next Sprint)

• True RAG implementation with vector database
• Side-by-side policy comparison
• Browser extension Chrome Web Store publication
• Export reports as PDF

v2.0 (3-6 months)

• Multi-language support (ES, FR, DE, ZH)
• Mobile app with QR code scanning
• Historical tracking of policy changes
• CCPA, PIPEDA, LGPD regulation support

v3.0 (Long-term)

• Privacy score certification program
• Real-time policy change alerts
• Collective action features
• Enterprise compliance tools

📊 Performance

• Analysis Speed: < 3 seconds (regex only), ~30-60 seconds (with AI)
• Accuracy: 85%+ on test dataset of 50 policies
• API Uptime: 99.9% (Flask + Backboard.io)

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🏆 Awards & Recognition

• HackNC 2025 - The Agency Track Submission
• Backboard.io API Challenge - Participant

👥 Team

Built with ❤️ by:

• Rohan Khandare - Full Stack Development
• Harsh More - Full Stack Development
• Hrishikesh Salway - Full Stack Development

🙏 Acknowledgments

• Backboard.io for AI API access
• HackNC 2025 for hosting the hackathon
• GDPR documentation from EUR-Lex
• Privacy policy examples from WhatsApp, LinkedIn, TikTok

📞 Contact

• Issues: Report a bug
• Email: rohanrk212@gmail.com, salway.hrishikesh@gmail.com, moreharsh2001@gmail.com

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