Next-Gen AI-Powered Security Operations Center (SOC) Advanced Threat Detection, Vector Analysis, and Automated Incident Response
The VectorVault is a cutting-edge Security Operations Center (SOC) dashboard designed to modernize threat detection and response. It combines Real-time Monitoring, Vector-based Machine Learning, and Automated Mitigation Workflows into a single, cohesive interface.
Unlike traditional SOCs, VectorVault leverages Ephemeral Authentication and AI-Driven Analysis to ensure maximum security and rapid response times.
- "New Session, New Credentials": Security codes are generated on-demand via Python scripts.
- Email Delivery: Credentials are securely emailed to the authorized user.
- Auto-Expiration: Login credentials expire automatically after 2 minutes, enforcing strict access control.
- 3D Vector Analysis: Input complex threat vectors (X, Y, Z coordinates) to classify attacks.
- ML-Powered Classification: Instantly identifies threats like DDoS, SQL Injection, or Malware based on vector signatures.
- Visual Feedback: Interactive visualization of the threat vector space.
- Live Dashboard: Monitor network health, server load, and active threats in real-time.
- "Code Weight" Workflow: seamless transition from monitoring to deep analysis.
- Automated Logging: One-click logging of predicted threats directly to the active incident registry.
- Threat Simulation: Watch real-time simulations of critical threats entering the system.
- Auto-Mitigation: Visual tracking of threats moving from "Critical" to "Resolved" status.
- Two-Zone Layout: Clear separation between Active Threats and Mitigated/Saved incidents.
- Instant Mitigation: Access ready-to-deploy C++ and Assembly code snippets for specific threats.
- Detailed Reporting: Generate comprehensive incident reports via email with a single click.
| Component | Technology | Description |
|---|---|---|
| Frontend | React + Vite | Fast, responsive UI with TailwindCSS & Shadcn/ui |
| Backend | Node.js + Express | Robust API handling and process orchestration |
| Database | SQLite | Lightweight, local database for incidents & predictions |
| AI/ML | Python | Scripts for vector analysis, auth generation, and reporting |
| Vector DB | TiDB (Optional) | Cloud-native vector storage for scalable deployments |
- Node.js (v18+)
- Python (v3.8+)
- npm or yarn
git clone https://github.com/your-org/The-VectorVault.git
cd The-VectorVault
npm installCreate a .env file in the root directory:
# Server Configuration
PORT=3001
NODE_ENV=development
# Database
SQLITE_DB_PATH=/path/to/your/desktop/attack_classifier.db
# Email Configuration (for Auth & Reports)
EMAIL_USER=[email protected]
EMAIL_PASS=your-app-passwordStart both the Backend Server and Frontend Client with a single command:
npm run dev:full- Frontend:
http://localhost:8080 - Backend:
http://localhost:3001
- Go to the Login Page.
- Click "Generate Credentials".
- Check your Email for the username and password.
- Login within 2 minutes before they expire.
- On the Dashboard, click the "Code Weight" button.
- System automatically sends a security code email and redirects you to Vector Search.
- Enter vector coordinates (e.g.,
1, 0, 0for DDoS) and click "Analyze". - Review the prediction and click "Log Incident" to save it.
- Navigate to the Incidents Page.
- Find the new incident and click "Solve".
- Review the C++ / Assembly mitigation code.
- Click "Accept & Resolve" to clear the threat.
The-VectorVault/
├── src/
│ ├── pages/ # React Pages (Dashboard, Incidents, VectorSearch, etc.)
│ ├── components/ # Reusable UI Components
│ ├── hooks/ # Custom React Hooks
│ └── App.tsx # Main Routing Logic
├── server.cjs # Express Backend Server
├── auth_manager.py # Python Script for Credential Generation
├── incident_reporter.py # Python Script for Email Reports
├── threat_solutions.py # Python Database of Threat Solutions
├── package.json # Dependencies & Scripts
└── README.md # You are here!
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request