🛡️ Autonomous Security Graph Dashboard

An enterprise-grade, high-performance security graph visualization and investigation dashboard powered by FastAPI, Kùzu Graph Database, Cytoscape.js, and an embedded Model Context Protocol (MCP) Server.

🌟 Key Features

• Live Cloud Asset Discovery: Seamless integration with Azure Resource Graph (ARG) for instant discovery of Virtual Machines, Subnets, VNets, Storage Accounts, and Network Interfaces.

• Entra ID Identity Ingestion: High-priority extraction and paging of Entra ID user accounts (Global Admins, CISOs, SOC Analysts, Managers, active VM sessions) mapped to endpoint workloads.

• Single-Threaded Kùzu Graph Engine: Dedicated Python worker-thread queue architecture ensuring zero C++ lock contention or multithreading deadlocks.

• Model Context Protocol (MCP) Server: Native FastMCP integration (src/backend/mcp_server.py) enabling AI agents (e.g., Claude, Antigravity) to query blast radiuses and inspect graph schemas via Cypher.

• Interactive Cytoscape.js GUI: Dynamic canvas featuring Obsidian Dark aesthetic (#111111 canvas, #e93d82 highlights), zoom controls, node search, layout transitions, and detailed inspector drawers.

• Security Incident Correlation: Automatic mapping of live Defender Alerts & Sentinel Security Incidents to compromised cloud infrastructure.

Related MCP server: Graphiti MCP Server

🏗️ Architecture Overview

graph TD
    A[Azure Tenant / ARG API] -->|Metadata Query| B[Scanner Engine src/backend/scanner.py]
    C[Entra ID / Intune] -->|az ad user list| B
    B -->|Ingest Nodes & Edges| D[Kùzu DB Queue Worker src/backend/db.py]
    D -->|Cypher Queries| E[(Kùzu Embedded Graph DB)]
    F[FastAPI Server src/backend/app.py] -->|GET /api/graph| D
    F -->|POST /api/scan| B
    G[React + Cytoscape UI src/frontend] <-->|SSE Logs / REST| F
    H[AI Agents / MCP Clients] <-->|FastMCP src/backend/mcp_server.py| D

🚀 Quick Start Guide

Prerequisites

• Python 3.11+

• Node.js 18+ & npm

• Azure CLI (az) (Optional for live tenant discovery)

1. Local Development Setup

Backend Setup

# Clone repository
git clone https://github.com/IamVigneshk/graph-security-dashboard.git
cd graph-security-dashboard

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Start FastAPI backend server (Runs on http://localhost:8000)
PYTHONPATH=. python src/backend/app.py

Frontend Setup

# Open a new terminal and navigate to frontend directory
cd src/frontend

# Install dependencies
npm install

# Start Vite development server (Runs on http://localhost:5173)
npm run dev

2. Running with Docker Compose

To launch both the backend API server and frontend build in isolated containers:

docker-compose up --build

Access the application at http://localhost:8000.

🔌 Model Context Protocol (MCP) Server Integration

The backend includes a standalone FastMCP server allowing LLMs and AI agents to query the security graph safely:

Running the MCP Server

PYTHONPATH=. python src/backend/mcp_server.py

Exposed MCP Tools

1. get_graph_schema(): Returns graph node types (Machine, CloudResource, Incident, Alert, User) and relationship schemas (:AFFECTS, :HOSTED_IN, :LOGGED_IN_TO, :INCLUDES).

2. read_cypher_query(query): Executes read-only Cypher queries against the embedded Kùzu database. Write operations (CREATE, DELETE, SET) are strictly blocked.

Example MCP Cypher Query

MATCH (i:Incident)-[:AFFECTS]->(m:Machine)-[:HOSTED_IN]->(r:CloudResource)
RETURN i.title, m.name, r.type

📡 API Endpoints Reference

🎨 UI Aesthetic & Design System

• Background: #111111 (Obsidian Dark)

• Cards & Drawers: #191919 / #1a1a1a with glassmorphic borders

• Primary Accent: #e93d82 (Magenta Glow)

• Severity Colors: Critical (#ff3366), High (#ff6600), Medium (#ffcc00), Low (#00ccff)

📄 License

MIT License. Developed by Vignesh K.