SilentScope 🔍

Advanced System Activity Analytics & Monitoring Framework

SilentScope is a sophisticated, enterprise-grade system activity analytics framework designed for comprehensive system monitoring, data collection, and behavioral analysis. Built with advanced encryption, fault tolerance, and scalable architecture.

🚀 Key Features

• Advanced Activity Analytics

  • Real-time keyboard pattern analysis
  • Intelligent clipboard monitoring
  • Active application tracking
  • Process behavior analysis
  • Network connection monitoring

• Enterprise Security

  • Military-grade Fernet encryption
  • Secure data storage
  • Encrypted MongoDB synchronization
  • Access control management

• Robust Architecture

  • Independent component isolation
  • Fault-tolerant operations
  • Automatic recovery mechanisms
  • Scalable data handling

• Silent Operation

  • Background process management
  • Low resource utilization
  • Stealth mode capabilities
  • Service-based execution

🛠️ Technical Stack

• Core: Python 3.8+
• Database: SQLite (local), MongoDB (sync)
• Security: Fernet encryption, PyWin32
• Monitoring: psutil, pynput
• Service Management: Windows Service Framework

📦 Installation

# Clone repository
git clone https://github.com/kenzycodex/SilentScope.git

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Setup configuration
cp .env.example .env
# Edit .env with your settings

🚦 Quick Start

from silentscope import SilentScope

# Initialize the framework
monitor = SilentScope()

# Start monitoring
monitor.start()

For detailed setup instructions, see SETUP.md

📚 Documentation

• Complete Documentation
• Architecture Overview
• Security Guide
• API Reference
• Deployment Guide

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Setup

# Install development dependencies
pip install -r requirements-dev.txt

# Run tests
pytest

# Check code style
black .

📊 Performance

• Minimal CPU usage (<2% average)
• Low memory footprint (<50MB)
• Efficient data storage
• Optimized MongoDB synchronization

🔒 Security Considerations

See our Security Policy for details on:

• Data encryption
• Storage security
• Network protection
• Access control

📄 License

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

🙏 Acknowledgments

• Core development team
• Open source contributors
• Testing team

📞 Support

• Issue Tracker
• Discussion Forum
• Security Reports

🗺️ Roadmap

See our ROADMAP.md for future development plans.

📈 Project Status

Made with ❤️ by Kenzy Codex 💙