🐕 CodeDog

AI-Powered Supply Chain Threat Detection Platform

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🚀 A cutting-edge full-stack application that analyzes GitHub repositories for security threats in real-time using local AI models and advanced threat detection algorithms

✨ Features

🧠 AI-Powered Analysis Local LLM integration with Ollama DeepSeek-R1 model for threat detection Intelligent commit analysis Automated vulnerability assessment	⚡ Real-Time Monitoring Live log streaming via WebSocket Instant threat alerts Progress tracking Dynamic dashboard updates
🛡️ Advanced Security Docker container sandboxing Network isolation Resource limitations Input sanitization	🎨 Modern Interface Beautiful dark mode UI Responsive design Interactive analytics Professional dashboards

🏗️ System Architecture

graph TB
    subgraph "Frontend Layer"
        A[React Dashboard] --> B[Socket.IO Client]
        A --> C[REST API Client]
    end
    
    subgraph "Backend Layer"
        D[Express Server] --> E[Socket.IO Server]
        D --> F[Analysis Engine]
        D --> G[AI Service]
    end
    
    subgraph "AI Layer"
        G --> H[Ollama Server]
        H --> I[DeepSeek-R1 Model]
    end
    
    subgraph "Data Layer"
        F --> J[MongoDB]
        F --> K[Job Queue]
    end
    
    subgraph "Security Layer"
        F --> L[Docker Engine]
        L --> M[Node.js Container]
        L --> N[Python Container]
    end
    
    B -.->|WebSocket| E
    C -.->|HTTP/REST| D
    
    style A fill:#61dafb,stroke:#000,color:#000
    style D fill:#339933,stroke:#000,color:#fff
    style H fill:#ff6b35,stroke:#000,color:#fff
    style J fill:#47a248,stroke:#000,color:#fff
    style L fill:#2496ed,stroke:#000,color:#fff

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🚀 Quick Start

📋 Prerequisites

Node.js 18+

Docker Desktop

Git

Ollama

🛠️ Installation

🔧 Step-by-Step Setup Guide

1️⃣ Clone the Repository

git clone https://github.com/Mihir-Rabari/code-dog.git
cd code-dog

2️⃣ Setup Ollama & AI Model

# Install Ollama (if not already installed)
curl -fsSL https://ollama.ai/install.sh | sh

# Pull the DeepSeek-R1 model
ollama pull deepseek-r1:1.5b

# Verify installation
ollama list

3️⃣ Backend Setup

cd backend
npm install

# Create environment file
cp .env.example .env
# Edit .env with your configurations

4️⃣ Frontend Setup

cd ../frontend
npm install

# Create environment file
cp .env.example .env

5️⃣ Docker Images

cd ../docker
docker build -f Dockerfile.node -t threat-detector:node .
docker build -f Dockerfile.python -t threat-detector:python .

6️⃣ Database Setup

# Start MongoDB (using Docker)
docker run -d -p 27017:27017 --name codedog-mongo mongo:latest

# Or use MongoDB Atlas (cloud)
# Update your .env file with connection string

🏃‍♂️ Running the Application

Backend Server cd backend npm run dev Server runs on http://localhost:5000

Frontend Dashboard cd frontend npm run dev Dashboard runs on http://localhost:3000

🎯 Quick Test

# Health check
curl http://localhost:5000/health

# Open dashboard
open http://localhost:3000

📊 How It Works

sequenceDiagram
    participant U as 👤 User
    participant F as 🖥️ Frontend
    participant B as ⚙️ Backend
    participant A as 🧠 AI Service
    participant D as 🐳 Docker
    participant DB as 🗄️ Database

    U->>F: Enter GitHub URL
    F->>B: POST /api/analyze-repo
    B->>DB: Create job record
    B->>D: Start sandbox container
    D->>D: Clone repository
    D->>D: Analyze dependencies
    D->>A: Send code for AI analysis
    A->>A: Process with DeepSeek-R1
    A->>B: Return threat assessment
    B->>F: WebSocket: Real-time logs
    B->>F: WebSocket: Risk score
    F->>U: Display results

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🎯 Usage Workflow

Step	Action	Description
1️⃣	Input	Enter GitHub repository URL
2️⃣	Configure	Select project type (Node.js/Python)
3️⃣	Analyze	Click "Start Analysis" button
4️⃣	Monitor	Watch real-time logs and progress
5️⃣	Review	Examine risk score and threats
6️⃣	Export	Download detailed security report

🛡️ Security Architecture

🔒 Container Isolation Sandboxed Docker environments No network access during analysis Resource limits (CPU/Memory) Temporary filesystem	🛠️ Input Validation URL format verification Repository accessibility checks Malicious payload detection Rate limiting protection
🔍 Threat Detection Suspicious commit patterns Dependency vulnerabilities Typosquatting detection Runtime behavior analysis	📊 Risk Assessment 0-100 risk scoring system Severity categorization Confidence metrics Actionable recommendations

🧪 Testing & Quality Assurance

🔬 Test Suite Overview

Backend Testing

cd backend
npm test                    # Run all tests
npm run test:unit          # Unit tests only
npm run test:integration   # Integration tests
npm run test:coverage      # Coverage report

Frontend Testing

cd frontend
npm test                   # Jest + React Testing Library
npm run test:e2e          # Cypress end-to-end tests
npm run test:coverage     # Coverage report

Docker Testing

# Test container builds
docker-compose -f docker-compose.test.yml up --build

# Security scan
docker scout cves threat-detector:node

📚 API Documentation

🔗 REST API Endpoints

Method	Endpoint	Description	Parameters
POST	/api/analyze-repo	Start repository analysis	repoUrl, projectType
GET	/api/job/:jobId/status	Get job status	jobId
GET	/api/job/:jobId/details	Get detailed job info	jobId
GET	/api/jobs	List all jobs	limit (optional)
GET	/health	Health check	-

🔌 WebSocket Events

Incoming Events join - Join job room disconnect - Leave room

Outgoing Events log - Real-time analysis logs alert - Security threat alerts progress - Analysis progress done - Final summary

📋 Request/Response Examples

🔍 API Examples

Start Analysis

curl -X POST http://localhost:5000/api/analyze-repo \
  -H "Content-Type: application/json" \
  -d '{
    "repoUrl": "https://github.com/user/repo",
    "projectType": "nodejs"
  }'

Response

{
  "jobId": "job_1234567890_abc123",
  "status": "running",
  "message": "Analysis started successfully"
}

Get Job Status

curl http://localhost:5000/api/job/job_1234567890_abc123/status

WebSocket Connection

const socket = io('http://localhost:5000');
socket.emit('join', 'job_1234567890_abc123');
socket.on('log', (data) => console.log(data));

🎬 Demo & Presentation

🚀 Perfect for Hackathons!

🎯 Demo Script Setup - Show the sleek dashboard Input - Enter a suspicious repo URL Real-time - Watch live log streaming AI Analysis - Highlight AI-powered detection Results - Present risk score & threats Export - Download security report

🏆 Key Selling Points ⚡ Real-time analysis 🧠 Local AI (no API costs) 🛡️ Advanced security 🎨 Beautiful dark UI 📊 Professional reports 🐳 Docker sandboxing

🌟 Showcase

📸 Screenshots

Coming soon - Add your amazing dashboard screenshots here!

🎥 Demo Video

Add a link to your demo video here

🤝 Contributing

We welcome contributions from the community!

🛠️ Development Setup

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

📝 Code Style

• ESLint + Prettier for JavaScript
• Follow existing patterns
• Add JSDoc comments
• Write meaningful commit messages

📄 License

MIT License - see LICENSE file for details

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