Built entirely in Jaclang from Day 1.

CyberCortex is a next-generation autonomous cybersecurity platform powered by Jaclang and Data Spatial Programming. Instead of traditional linear scripts or standard object-oriented patterns, CyberCortex models your network architecture, active threats, and security states as an interconnected graph of nodes. Autonomous walkers traverse this graph to perform real-time security validation, threat analysis, and vulnerability assessment.

• Nodes & Edges: Networks and threats are natively modeled as SecurityTarget and ThreatIntel nodes connected by spatial edges.
• Autonomous Walkers: ScannerWalker autonomously traverses the graph to discover vulnerabilities and assess node status.
• Inherent State Management: State is maintained naturally within the graph structure, allowing highly decoupled and resilient security operations.

• Unified Logic: Both backend API routing and multi-agent coordination are written seamlessly in .jac files.
• Jaclang API Integration: Uses Jaclang's built-in Python interoperability to serve a high-performance web dashboard via FastAPI.
• Zero-Friction Orchestration: Agents are not external microservices; they are native walkers spawned directly on the graph.

                           [ AppServer (main.jac) ]
                                      |
                      Serves UI and Triggers Walkers
                                      |
                              v-------+-------v
                              |               |
                       [ScannerWalker]  [CoordinatorWalker]
                              |               |
                              v               v
    +-------------------------------------------------------------+
    |                    CyberGraph Data Spatial                  |
    |                                                             |
    |   (Node: SecurityTarget) ++[Analyzes]++> (Node: ThreatIntel)|
    |   - ip_address                                              |
    |   - status                                                  |
    |   - vulnerabilities                                         |
    +-------------------------------------------------------------+

• graph.jac: Defines the Data Spatial structure (Nodes: SecurityTarget, ThreatIntel and Edges).
• agents.jac: Defines the autonomous Walkers (ScannerWalker, CoordinatorWalker) that traverse the graph to find vulnerabilities.
• main.jac: The main entry point that boots the Data Spatial graph and exposes the execution environment via a Jaclang HTTP server.
• index.html: A sleek, pure HTML/CSS/JS dashboard served natively by the Jaclang backend to provide a visual command center.

• Python 3.10+
• jaclang installed (pip install jaclang)
• fastapi and uvicorn installed (pip install fastapi uvicorn)

1. Clone the repository and ensure your environment has Jaclang set up.
2. Run the main server using the Jac compiler:

   jac run main.jac

3. Open your browser and navigate to:

   http://localhost:8000
   

4. Click "Spawn ScannerWalker" in the dashboard to watch the Jaclang walker autonomously traverse the data spatial graph and report vulnerabilities in real-time.

This project demonstrates the power of Data Spatial Programming for cybersecurity. By modeling infrastructure as a graph and agents as walkers, we eliminate the complex boilerplate of traditional microservices, resulting in a cleaner, more intuitive, and highly scalable security orchestration platform built entirely in Jaclang.