Production-Ready AI-Powered Network Defense, Monitoring, and Threat Intelligence System
- Local AI Processing: Privacy-first anomaly detection with no external dependencies
- Cloud AI Integration: Optional OpenAI GPT-powered analysis for advanced insights
- Pattern Learning: Adaptive baseline learning that improves over time
- False Positive Reduction: User feedback integration to reduce false alarms
- Fail2ban Integration: Automatic IP blocking for brute force protection
- UFW Firewall: Pre-configured security rules
- Session Management: Secure web sessions with timeout
- Input Validation: Comprehensive sanitization and validation
- Health Monitoring: Comprehensive system health checks
- Log Rotation: Automated log management with size limits
- Performance Optimization: Resource limits and monitoring
- Backup Strategy: Automated configuration backups
S h a y d Z Super Monitor is a production-ready, AI-enhanced network defense and threat intelligence system designed for both home labs and enterprise environments. Built for Raspberry Pi but compatible with any Linux system.
- Dual AI Modes: Choose between local (private) or cloud-based AI processing
- Smart Anomaly Detection: AI learns normal patterns and detects deviations
- Predictive Analysis: Forecasts potential issues before they occur
- Intelligent Recommendations: AI-powered system optimization suggestions
- Real-time Threat Intelligence: CISA, CVE, Reddit, BleepingComputer, OTX feeds
- Automated IP Blocking: Instant response to detected threats
- Failed Login Monitoring: Tracks and alerts on authentication failures
- Multi-device Health: Monitors network-connected devices
- AI Dashboard: Real-time AI status and insights
- Security Controls: Threat management and response
- Performance Metrics: System health and optimization
- Mobile-Friendly: Responsive design for all devices
- E-paper Output: Status on Waveshare 2.13" V3 display
- Critical Alerts: Immediate visual feedback
- System Status: Live metrics and health indicators
- Systemd Service: Automatic startup and management
- Log Rotation: Automated maintenance
- Health Checks: Continuous monitoring
- Backup Integration: Configuration preservation
git clone https://github.com/shaydz93/shaydz-super-monitor.git
cd shaydz-super-monitor
chmod +x install.sh
./install.sh- Open http://YOUR-PI-IP:5001
- Create your admin account
- Configure AI settings (Local or Cloud)
- ✅ Maximum Privacy: All processing happens locally
- ✅ No API Key Required: Works without external services
- ✅ Good Performance: Effective anomaly detection
- ✅ Air-gap Compatible: Perfect for isolated networks
- 🌟 Advanced Analysis: OpenAI GPT-powered insights
- 🌟 Enhanced Detection: Sophisticated pattern recognition
- 🌟 Intelligent Recommendations: AI-powered optimization
- 🌟 Predictive Analysis: Future trend identification
To enable Cloud AI: Add your OpenAI API key in Settings → AI Configuration
- Raspberry Pi 3B+ (or any Linux system)
- 512MB RAM, 2GB storage
- Network connection
- Raspberry Pi 4B (2GB+ RAM)
- 1GB RAM, 8GB storage
- Waveshare 2.13" V3 e-Paper HAT
- Raspberry Pi (3B+, 4B, Zero 2W)
- Ubuntu 20.04+, Debian 11+
- Any modern Linux distribution
# Check status
sudo systemctl status shaydz
# View logs
sudo journalctl -u shaydz -f
# Restart service
sudo systemctl restart shaydz
# Run health check
./health_check.sh# Local Mode (Privacy-first)
# - No API key required
# - All processing happens locally
# - Good anomaly detection
# Cloud Mode (Advanced)
# - Requires OpenAI API key
# - Enhanced AI analysis
# - Intelligent recommendations- UFW Firewall: Pre-configured rules
- Fail2ban: Brute force protection
- IP Blocking: Automatic threat response
- Session Security: Secure web access
- Input Validation: Comprehensive sanitization
- Secure Storage: Encrypted configuration
- Log Management: Secure audit trails
- Resource Limits: DOS protection
- CPU, RAM, disk usage
- Temperature monitoring
- Network connectivity
- Process monitoring
- Failed login attempts
- Threat IP detection
- Anomaly identification
- Security event tracking
- Pattern recognition
- Baseline learning
- Predictive analysis
- Performance optimization
See PRODUCTION_GUIDE.md for complete deployment instructions including:
- Security hardening
- Performance optimization
- Backup strategies
- Monitoring setup
- SSL/TLS configuration
- AI_FEATURES.md: Complete AI capabilities guide
- PRODUCTION_GUIDE.md: Production deployment guide
- DEBUG_REPORT.md: Troubleshooting and fixes
- RELEASE_NOTES.md: Version history and features
- GitHub Issues: Report bugs and request features
- Discussions: Share experiences and get help
- Pull Requests: Code contributions welcome
- Documentation: Help improve guides
- Enterprise deployment assistance
- Custom feature development
- Security consulting
- Performance optimization
Add screenshots of your enhanced dashboard, AI insights, and e-paper display here for maximum impact!
- Local AI processing by default
- No data sharing unless you choose cloud mode
- Complete control over your data
- Production-ready security features
- Automated threat response
- Comprehensive monitoring
- Advanced anomaly detection
- Predictive analysis
- Intelligent recommendations
- One-command installation
- Automatic service management
- Comprehensive documentation
MIT License — see LICENSE for details.
- Inspired by open-source blue-team and threat intelligence tools
- E-paper Python libraries © Waveshare
- AI capabilities powered by OpenAI (optional)
- Built with love for the cybersecurity community
- Installation Guide: Get started in minutes
- Production Guide: Deploy in production
- Release Notes: Version 1.0 features
- Health Check: Monitor system health
To clean up development files before committing:
./cleanup.shThis removes:
- Python cache files (
__pycache__/,*.pyc) - Generated configs (
ai_config.json,baseline.json, etc.) - Log files (
*.log) - Temporary files (
*.tmp,*~) - IDE files (
.vscode/,.idea/)
Monitor smarter. Secure better. Deploy with confidence.
S h a y d Z Super Monitor - Where AI meets network security.