All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Real-time log ingestion API via FastAPI with
/logs/and/predict/endpoints - Isolation Forest unsupervised anomaly detection model (scikit-learn)
- AI model training script
ai-model/train_model.pywith synthetic log data generation - SQLite database with SQLAlchemy ORM for persistent log storage
- Next.js 15 + React 18 interactive security dashboard
- Recharts integration for traffic spike and threat distribution visualizations
- 3D Threat Globe visualization using React Three Fiber and Three.js
- 3D Network Topology Graph with real-time interactive nodes
- TailwindCSS utility-first styling across all frontend components
- Docker &
docker-compose.ymlfor containerized full-stack deployment .dockerignorefor optimized Docker image builds- GitHub Actions CI/CD pipeline with PYTHONPATH fix for backend module imports
- Comprehensive unit tests for
/logs/API endpoints CONTRIBUTING.mdwith contribution guidelinesSECURITY.mdwith security policy and responsible disclosure processSETUP_GUIDE.mdwith step-by-step local setup instructionsgithub_deploy_guide.mdwith deployment instructions- MIT License
- Repository topics: python, docker, machine-learning, nextjs, cybersecurity, anomaly-detection, isolation-forest, threat-detection, security-monitoring, fastapi
- Frontend downgraded from unstable Next.js canary to stable Next.js 15 + React 18 to resolve compatibility issues
- CI pipeline: set
PYTHONPATH=.to resolve backend module import errors in tests .gitignoreupdated to exclude debug, temporary, and compiled files
- Backend: Python 3.10+, FastAPI, scikit-learn, Pandas, NumPy, SQLAlchemy, SQLite
- Frontend: Next.js 15, React 18, TailwindCSS, Recharts, Three.js, React Three Fiber, @react-three/drei, Lucide React
- DevOps: Docker, GitHub Actions CI
- WebSocket integration for live real-time threat alerts
- OAuth2 user authentication and role-based access control
- Cloud deployment to AWS / Render
- PostgreSQL migration support for production-scale databases
- Additional ML models (Autoencoder, ensemble methods) for improved detection accuracy