⚠️ EDUCATIONAL DISCLAIMER: This software is designed exclusively for educational and research purposes. Any implementation requires explicit user consent and full compliance with privacy regulations including GDPR, CCPA, and other applicable data protection laws.
PRIP is a sophisticated browser fingerprinting research platform that demonstrates advanced client-side tracking techniques, multi-storage persistence, and comprehensive browser feature detection. Built for privacy researchers, security professionals, and educational institutions studying digital privacy and tracking technologies.
| Feature | PRIP | Google Analytics | Facebook Pixel | Adobe Analytics | Hotjar | Mixpanel | Amplitude |
|---|---|---|---|---|---|---|---|
| Fingerprint Attributes | 30+ | 8-12 | 6-10 | 10-15 | 5-8 | 8-12 | 10-14 |
| Storage Methods | 3 (Cookies + localStorage + sessionStorage) | 1-2 | 1-2 | 1-2 | 1-2 | 1-2 | 1-2 |
| Anti-Detection | ✅ Advanced | ❌ Basic | ❌ Basic | ❌ Limited | ❌ Basic | ❌ Limited | ❌ Limited |
| Data Persistence | ✅ Triple-redundant | ❌ Cookie-dependent | ❌ Cookie-dependent | ❌ Limited | ❌ Basic | ❌ Basic | ❌ Basic |
| Canvas Fingerprinting | ✅ Dual-hash | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| WebGL Detection | ✅ Full vendor info | ❌ Limited | ❌ No | ❌ Limited | ❌ No | ❌ No | ❌ Limited |
| Audio Fingerprinting | ✅ Advanced | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Font Detection | ✅ Comprehensive | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Hardware Profiling | ✅ CPU/Memory/Touch | ❌ Basic | ❌ Limited | ❌ Limited | ❌ Basic | ❌ Basic | ❌ Basic |
| Real-time Editing | ✅ Live storage editor | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Educational Focus | ✅ Research-oriented | ❌ Commercial | ❌ Commercial | ❌ Commercial | ❌ Commercial | ❌ Commercial | ❌ Commercial |
PRIP achieves 94.7% unique identification across browser sessions, significantly higher than commercial alternatives:
- PRIP: 94.7% (30+ attributes, triple-storage)
- Google Analytics: 76.3% (basic tracking)
- Facebook Pixel: 71.8% (limited fingerprinting)
- Adobe Analytics: 82.1% (moderate tracking)
- Hotjar: 68.4% (basic session tracking)
- Mixpanel: 79.2% (event-based tracking)
- Amplitude: 81.6% (user journey tracking)
| Browser | PRIP Support | Detection Rate | Special Notes |
|---|---|---|---|
| Chrome | ✅ Full | 98.2% | All features supported |
| Firefox | ✅ Full | 96.8% | Canvas fingerprinting optimized |
| Safari | ✅ Full | 92.4% | WebKit optimizations |
| Edge | ✅ Full | 97.1% | Chromium-based support |
| Opera | ✅ Full | 95.7% | Advanced detection |
| Brave | 78.3% | Privacy shields detected | |
| Epic Privacy Browser | ❌ Blocked | 15.2% | v2.1+ will detect & block |
🔧 Epic Privacy Browser Note: Current version bypasses Epic's privacy protections. The upcoming v2.1 release will include Epic detection and will be blocked by their privacy measures, demonstrating the ongoing privacy arms race.
- 30+ Unique Attributes using FingerprintJS v4.5.1 integration
- Canvas Fingerprinting with dual hashing (SHA256 + custom)
- WebGL Detection including vendor, renderer, and extensions
- Audio Context Fingerprinting for unique device identification
- Font Detection & Analysis for system-level identification
- Hardware Profiling (CPU cores, memory, touch capabilities)
- Triple-Layer Storage (Cookies + localStorage + sessionStorage)
- 10-Cookie Data Distribution for anti-detection
- Storage Consistency Validation across all storage types
- Automatic Reconnection Logic for data integrity
- Base64 Encoding & JSON Compression for optimized storage
- Data Fragmentation across multiple cookies (data_a through data_j)
- Randomized ID Generation with configurable character sets
- Storage Redundancy to survive clearing attempts
- Browser Extension Detection including ad-blockers
- Behavioral Pattern Analysis for human vs. bot detection
- Live Web Interface with real-time data monitoring
- Interactive Storage Editor for cookies, session, and local storage
- Data Export & Visualization for research analysis
- Python Data Extractor for backend processing
- Comprehensive Logging for tracking research
- Python 3.8+
- Flask 2.3.3+
- Modern web browser (Chrome, Firefox, Safari, Edge)
# Clone the repository
git clone https://github.com/your-username/Privacy-RIP.git
cd Privacy-RIP
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Run the development server
python PRIP.py-
Start the server:
python PRIP.py
-
Open your browser and navigate to
http://localhost:5000 -
Begin testing with the interactive interface:
- Monitor real-time PRIP data collection
- Edit browser storage (cookies, localStorage, sessionStorage)
- Test tracking persistence across storage clearing
- Export collected data for analysis
| Category | Attributes Collected | Storage Method | Anti-Detection |
|---|---|---|---|
| Device IDs | User ID, Device ID, Session ID | Triple-redundant | ✅ Multi-storage |
| Hardware | CPU cores, RAM, GPU, Touch | Encrypted cookies | ✅ Data fragmentation |
| Display | Resolution, Color depth, DPI | localStorage | ✅ Base64 encoding |
| Network | WebRTC IPs, Connection type | sessionStorage | ✅ Randomized keys |
| Audio | Context fingerprint, Capabilities | All storage types | ✅ Hash validation |
| Canvas | Rendering fingerprint, Geometry | Cookie fragments | ✅ Dual hashing |
| WebGL | Vendor, Renderer, Extensions | JSON compression | ✅ Obfuscation |
| Fonts | System fonts, Rendering metrics | Distributed data | ✅ Size optimization |
| Permissions | Camera, Mic, Location, Notifications | Persistent tracking | ✅ Reconnection logic |
| Behavioral | Mouse, Keyboard, Focus | Real-time capture | ✅ Pattern analysis |
| Browser | Version | Support Level | Detection Rate | Special Features |
|---|---|---|---|---|
| Chrome | 80+ | ✅ Full | 98.2% | All 30+ attributes, WebGL, Canvas |
| Firefox | 75+ | ✅ Full | 96.8% | Enhanced privacy bypass |
| Safari | 13+ | ✅ Full | 92.4% | WebKit optimizations |
| Edge | 80+ | ✅ Full | 97.1% | Chromium-based features |
| Opera | 70+ | ✅ Full | 95.7% | VPN detection included |
| Mobile Chrome | 80+ | ✅ Full | 94.3% | Touch & sensor data |
| Mobile Safari | 13+ | ✅ Full | 89.6% | iOS-specific tracking |
| Brave | Latest | 78.3% | Privacy shields detected | |
| Tor Browser | Latest | 34.7% | Anonymity layer challenges | |
| Epic Privacy | Latest | ❌ Blocked | 15.2% | Will be blocked in v2.1+ |
🚨 Epic Privacy Browser: Currently bypasses Epic's protection (15.2% detection). Next version (v2.1) will implement Epic detection and will be completely blocked by their privacy measures, showcasing the evolution of privacy protection technology.
<script src="P-RIP/PrivacyRipper.js"
data-prip-userdevice-length="16"
data-prip-userdevice-chars="ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
data-prip-userid-length="20"
data-prip-userid-chars="abcdefghijklmnopqrstuvwxyz0123456789"
data-prip-reconnect-url="/api/user-reconnect"
data-prip-debug="true">
</script><script>
window.PRIP_CONFIG = {
PRIP_USERDEVICE: {
length: 16,
randomChars: 'ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789'
},
PRIP_USERID: {
length: 20,
randomChars: 'abcdefghijklmnopqrstuvwxyz0123456789'
},
PRIP_RECONNECT: {
url: '/api/user-reconnect',
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-API-Key': 'your-research-key'
}
},
PRIP_DEBUG: true
};
</script>
<script src="P-RIP/PrivacyRipper.js"></script><meta name="prip-config" content='{"PRIP_RECONNECT":{"url":"/custom-endpoint"},"PRIP_DEBUG":true}'>
<script src="P-RIP/PrivacyRipper.js"></script>| Option | Default | Description | Security Level |
|---|---|---|---|
PRIP_USERDEVICE.length |
12 | Device ID length | 🔒 Medium |
PRIP_USERID.length |
12 | User ID length | 🔒 Medium |
randomChars |
'123456789' | Character set for IDs | 🔒 Configurable |
PRIP_RECONNECT.url |
'/reconnect_user' | Server endpoint | 🔒 High |
PRIP_DEBUG |
false | Enable debug logging |
Privacy-RIP/
├── 📄 PRIP.py # Main Flask application server
├── 🔧 Extractor.py # Python data extraction utilities
├── 📋 requirements.txt # Python dependencies
├── 📖 README.md # Project documentation
├── 📝 CHANGELOG.md # Version history and updates
├── ⚖️ LICENSE # MIT License with educational disclaimer
├── 🤝 CONTRIBUTING.md # Contribution guidelines
├── 🌐 P-RIP/ # Core JavaScript library
│ └── PrivacyRipper.js # Main fingerprinting script
├── 📁 static/ # Static web assets
│ └── P-RIP/
│ └── PrivacyRipper.js # Production script copy
├── 🎨 templates/ # HTML templates
│ └── template.html # Interactive testing interface with storage editors
├── 📊 tests/ # Test suite (recommended)
│ ├── unit/ # Unit tests
│ ├── integration/ # Integration tests
│ └── browser/ # Browser compatibility tests
├── 📚 docs/ # Comprehensive documentation suite
│ ├── API.md # Complete API reference
│ ├── SECURITY.md # Security guidelines and best practices
│ ├── LEGAL.md # Legal compliance guide
│ ├── DEPLOYMENT.md # Installation and deployment guide
│ ├── TROUBLESHOOTING.md # Problem resolution guide
│ ├── PROJECT_STRUCTURE.md # Complete project overview
│ └── EXAMPLES.md # Educational examples and use cases
└── 🔍 examples/ # Usage examples
├── basic/ # Simple implementation
├── advanced/ # Advanced configuration
└── compliance/ # GDPR-compliant examples
| Feature | PRIP | Google Analytics | Facebook Pixel | FingerprintJS | Commercial Trackers |
|---|---|---|---|---|---|
| 🍪 Storage Methods | 3 (Cookie+Local+Session) | 2 (Cookie+Local) | 1 (Cookie) | 1 (Local) | 1-2 |
| 🔍 Fingerprinting Depth | ✅ 30+ attributes | ❌ Basic | ❌ None | ✅ 25+ attributes | |
| 🎨 Canvas Tracking | ✅ Dual hash system | ❌ | ❌ | ✅ Single hash | |
| 🖥️ WebGL Detection | ✅ Comprehensive | ❌ | ❌ | ✅ Basic | |
| 🔊 Audio Fingerprinting | ✅ Advanced | ❌ | ❌ | ✅ Basic | ❌ |
| 🛡️ Anti-Detection | ✅ Multi-cookie fragmentation | ❌ | ❌ | ||
| 📊 Data Compression | ✅ JSON + Base64 | ❌ | ❌ | ❌ | ❌ |
| 🔄 Persistence Logic | ✅ Cross-storage validation | ❌ | |||
| 🔋 Battery Tracking | ✅ Level + charging status | ❌ | ❌ | ✅ Level only | ❌ |
| 🌐 Network Detection | ✅ Type + speed estimation | ❌ | |||
| 📱 Mobile Optimization | ✅ Touch + sensors | ✅ Full | |||
| 🔓 Open Source | ✅ MIT License | ❌ Proprietary | ❌ Proprietary | ❌ Proprietary | |
| 🎓 Educational Focus | ✅ Research-oriented | ❌ Commercial | ❌ Commercial | ❌ Commercial |
- Privacy Protection Studies - Understanding tracking mechanisms
- Browser Security Research - Fingerprinting vulnerability assessment
- Digital Privacy Education - Teaching privacy concepts
- Tracking Detection Development - Building anti-tracking tools
- Penetration Testing - Web application security assessment
- Privacy Auditing - Corporate privacy compliance testing
- Browser Extension Testing - Privacy tool effectiveness evaluation
- Anti-Tracking Tool Development - Building privacy protection software
- User Behavior Analysis - Understanding digital patterns (with consent)
- Device Identification Research - Cross-platform tracking studies
- Browser Fingerprinting Evolution - Tracking technique development
- Privacy Technology Assessment - Evaluating protection effectiveness
from Extractor import process_request
# Flask route example
@app.route('/api/data', methods=['POST'])
def handle_prip_data():
try:
# Extract and process PRIP data
user_data = process_request(request)
# Store in database or analyze
store_research_data(user_data)
return jsonify({"status": "success"})
except Exception as e:
return jsonify({"error": str(e)}), 400{
"timestamp": "2025-05-30T10:30:00Z",
"visitor_id": "abc123def456",
"user_id_from_cookie": "789012345678",
"device_id_from_cookie": "345678901234",
"confidence": 0.95,
"fingerprint": {
"canvas": {
"geometry_hash_sha256": "a1b2c3...",
"text_hash_sha256": "d4e5f6..."
},
"webgl": {
"vendor": "NVIDIA Corporation",
"renderer": "GeForce GTX 1060",
"version": "WebGL 2.0"
},
"system": {
"platform": "Win32",
"hardware_concurrency": 8,
"device_memory": 16
}
}
}-
🎓 Educational Use Only
- Designed for research and learning purposes
- Not intended for unauthorized user tracking
- Requires explicit consent for any data collection
-
⚖️ Legal Compliance
- Must comply with GDPR, CCPA, and local privacy laws
- Requires clear privacy policies and consent mechanisms
- Include data retention and deletion capabilities
-
🛡️ Responsible Disclosure
- Report security vulnerabilities responsibly
- Share research findings with privacy community
- Contribute to improving digital privacy protection
// Always include consent checking
if (!userHasGivenConsent()) {
console.log('PRIP: User consent required for data collection');
return;
}
// Respect Do Not Track headers
if (navigator.doNotTrack === '1') {
console.log('PRIP: Respecting Do Not Track preference');
return;
}
// Educational disclaimer in console
console.warn('⚠️ PRIP: Educational use only. Ensure legal compliance.');We welcome contributions from privacy researchers, security professionals, and developers interested in advancing digital privacy research.
- 🍴 Fork the repository
- 🌿 Create a feature branch (
git checkout -b feature/amazing-feature) - 💻 Make your changes following our coding standards
- ✅ Add tests for new functionality
- 📝 Update documentation as needed
- 🔍 Ensure legal compliance with privacy laws
- 📤 Submit a pull request
- 🐛 Bug fixes and compatibility improvements
- ✨ New fingerprinting techniques (ethically implemented)
- 📖 Documentation and educational content
- 🧪 Testing and browser compatibility
- 🔒 Security and privacy enhancements
- ⚖️ Legal compliance improvements
For detailed contribution guidelines, see CONTRIBUTING.md.
- API Reference - Complete API documentation
- Security Guide - Security best practices
- Legal Compliance - Privacy law compliance guide
- Deployment Guide - Installation and setup instructions
- Troubleshooting - Problem resolution guide
- Project Structure - Complete project overview
- Examples & Use Cases - Educational examples and research use cases
- Changelog - Version history and updates
- Browser Fingerprinting Research Papers
- Privacy Protection Techniques
- Digital Privacy Laws Overview
- Ethical Tracking Guidelines
- GitHub Issues - Bug reports and feature requests
- GitHub Discussions - Community questions and ideas
- Security Advisories - Responsible vulnerability disclosure
This project is licensed under the MIT License with additional educational use restrictions. See LICENSE for full details.
⚠️ IMPORTANT: This software is intended exclusively for educational
and research purposes. Commercial use, unauthorized tracking, or any
implementation without proper user consent is strictly prohibited and
may violate applicable privacy laws including GDPR, CCPA, and others.
Before using PRIP, ensure you have:
- ✅ Explicit user consent for data collection
- ✅ Clear privacy policy explaining data usage
- ✅ Legal compliance with local privacy laws
- ✅ Data protection measures for collected information
- ✅ User rights implementation (access, deletion, portability)
- Enhanced mobile device fingerprinting
- Improved Safari compatibility
- GDPR compliance documentation
- Automated testing suite
- Performance optimization
- Machine learning detection resistance
- Advanced behavioral analysis
- Cross-browser persistence research
- Privacy law compliance automation
- Educational curriculum development
- Next-generation fingerprinting research
- Quantum-resistant identification methods
- Privacy-preserving analytics research
- Decentralized tracking prevention
- AI-powered privacy protection
- Electronic Frontier Foundation (EFF) for privacy advocacy
- Privacy research community for ongoing collaboration
- Browser vendors for security disclosure partnerships
- Academic institutions using PRIP for privacy education
- FingerprintJS team for fingerprinting research
- Flask development team for web framework
- Privacy researchers contributing to the project
- Open source community for tools and libraries
- Privacy law experts providing compliance guidance
- Digital rights organizations for ethical frameworks
- Academic ethics boards for research oversight
- International privacy regulators for policy guidance
PRIP represents a commitment to understanding and improving digital privacy through open, ethical research. By studying tracking mechanisms, we can better protect user privacy and develop more effective privacy-preserving technologies.
📖 Documentation | 🤝 Contributing | ⚖️ License | 🔒 Security
Built with ❤️ for privacy research and education