KeyGuard AI Scan

Overview

KeyGuard AI Scan is a comprehensive, open-source security tool that scans websites for exposed API keys and provides AI-powered recommendations with any OpenAI compatible endpoint, for remediation. Built with modern technologies and designed for both developers and security teams, it helps identify and fix API key exposures that could lead to security breaches.

🚀 Features

🔍 Comprehensive Scanning

Real-time Website Scanning: Progressive scan with live updates
Deep Analysis: Scans HTML, JavaScript, CSS, and network requests
100+ API Key Types: Detects AWS, Google Cloud, GitHub, Stripe, OpenAI, and many more
Advanced Pattern Matching: Regex patterns with entropy analysis
Context-Aware Detection: Distinguishes between real keys and test/dummy values

🤖 AI-Powered Intelligence

Smart Recommendations: NEURA_ROUTER or any OpenAI SDK compatible integration for context-aware suggestions
Severity Classification: Automatic risk assessment (Critical, High, Medium, Low)
Actionable Remediation: Detailed, step-by-step fix instructions
Best Practices: Security guidelines and prevention tips
Custom Solutions: Tailored recommendations based on detected frameworks

📊 Professional Reporting

Interactive Dashboard: Visual reporting with findings breakdown
Export Options: PDF, JSON, CSV report generation
Shareable Results: Secure sharing of scan results
Historical Tracking: User account with scan history
Real-time Progress: Live updates during scanning process

🔐 Enterprise Security

User Authentication: JWT-based secure sessions
Rate Limiting: Protection against abuse
Data Privacy: No permanent storage of sensitive data
HTTPS Encryption: All communications encrypted
Audit Logging: Comprehensive activity tracking

🏗️ Architecture

Frontend Stack

Framework: React 18 with TypeScript
Build Tool: Vite for fast development and builds
Styling: Tailwind CSS + Shadcn/ui components
State Management: TanStack Query for server state
Analytics: Langfuse for user tracking and insights
Icons: Lucide React for consistent iconography

Backend Stack

Language: Rust for performance and safety
Database: LibSQL for lightweight, fast data storage
Web Framework: Axum for async HTTP services
Authentication: JWT with bcrypt password hashing
AI Integration: NEURA_ROUTER (OpenAI SDK compatible)
HTTP Client: Reqwest for web scraping

Infrastructure

Containerization: Docker with multi-stage builds
Orchestration: Docker Compose for local development
Ports: Frontend (11111), Backend (11112)
Database: In-memory LibSQL (production-ready for scaling)

🚀 Quick Start

Prerequisites

Node.js 18+ and npm
Rust 1.75+ (for backend development)
Docker and Docker Compose (recommended)

Using Docker (Recommended)

Clone the repository

git clone <repository-url>
cd keyguard-ai-scan

Set environment variables

cp .env.example .env
# Edit .env with your NEURA_ROUTER_API_KEY

Start the services
```
docker-compose up --build
```
Access the application
- Frontend: http://localhost:11111
- Backend API: http://localhost:11112

Manual Development Setup

Frontend Setup

# Install dependencies
npm install

# Start development server
npm run dev

Backend Setup

# Navigate to server directory
cd server

# Build and run
cargo run

🔧 Configuration

Environment Variables

Frontend (.env)

VITE_API_URL=http://localhost:11112

Backend (server/.env)

JWT_SECRET=your-secure-jwt-secret
NEURA_ROUTER_API_KEY=your-neura-router-api-key
NEURA_ROUTER_API_URL=https://api.neura-router.com/v1
RUST_LOG=info

API Keys Setup

NEURA_ROUTER Integration
- Sign up at NEURA_ROUTER platform
- Generate API key with GPT-4 access
- Add to environment variables
Production Deployment
- Use strong JWT secret (32+ characters)
- Enable HTTPS in production
- Configure proper CORS origins

📖 API Documentation

Core Endpoints

Scanning

POST /api/scan - Start new scan
GET /api/scan/:id - Get scan results
GET /api/scan/:id/progress - Get scan progress

Authentication

POST /api/auth/register - Register new user
POST /api/auth/login - User login
GET /api/user/scans - Get user's scan history

Health

GET /api/health - Service health check

Request/Response Examples

Start Scan

POST /api/scan
{
  "url": "https://example.com",
  "user_id": "optional-user-id"
}

Scan Response

{
  "success": true,
  "data": {
    "id": "scan-uuid",
    "url": "https://example.com",
    "status": "scanning",
    "findings": [],
    "summary": {
      "critical": 0,
      "high": 0,
      "medium": 0,
      "low": 0,
      "total": 0
    }
  }
}

🧪 Testing

Frontend Testing

npm run test
npm run test:coverage

Backend Testing

cd server
cargo test
cargo test --release

Integration Testing

docker-compose -f docker-compose.test.yml up --build

🚀 Deployment

Production Docker Build

# Build production images
docker-compose -f docker-compose.prod.yml build

# Deploy to production
docker-compose -f docker-compose.prod.yml up -d

Manual Production Setup

Build frontend: npm run build
Build backend: cd server && cargo build --release
Configure reverse proxy (nginx/traefik)
Set up SSL certificates
Configure monitoring and logging

🔐 Security Considerations

Data Privacy

No Permanent Storage: Scan results stored temporarily
Encryption: All data transmission via HTTPS
User Control: Clear data retention policies
Anonymization: No PII stored without consent

Scanning Ethics

Rate Limiting: Prevents abuse of target websites
Robots.txt: Respects website scanning preferences
Legal Compliance: GDPR, CCPA compliant
Responsible Disclosure: Security-focused approach

🤝 Contributing

Development Workflow

Fork the repository
Create feature branch: git checkout -b feature/amazing-feature
Commit changes: git commit -m 'Add amazing feature'
Push to branch: git push origin feature/amazing-feature
Open Pull Request

Code Standards

Frontend: ESLint + Prettier configuration
Backend: Rustfmt + Clippy linting
Testing: Minimum 80% code coverage
Documentation: Comprehensive inline docs

📊 Analytics & Monitoring

Built-in Analytics

Scan Metrics: Success rates, duration, findings
User Behavior: Feature usage, engagement patterns
Performance: Response times, error rates
Security: Vulnerability trends, detection accuracy

Monitoring Stack

Logging: Structured logs with tracing
Metrics: Custom metrics for business KPIs
Alerting: Error rate and performance alerts
Health Checks: Automated service monitoring

🆘 Support

Documentation

API Reference: Comprehensive endpoint documentation
Developer Guide: Setup and customization instructions
Security Guide: Best practices and compliance
Troubleshooting: Common issues and solutions

Community

Issues: GitHub Issues for bug reports
Discussions: Feature requests and questions
Discord: Real-time community support
Security: adolfo@meetneura.ai for vulnerabilities

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Shadcn/ui: Beautiful, accessible React components
Langfuse: Analytics and user tracking platform
NEURA_ROUTER: AI-powered recommendation engine
Rust Community: Amazing ecosystem and libraries
Security Researchers: Vulnerability patterns and best practices

KeyGuard AI Scan - Securing the web, one API key at a time. 🔐✨

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
public		public
server		server
src		src
.env.example		.env.example
.gitignore		.gitignore
Dockerfile.backend		Dockerfile.backend
Dockerfile.frontend		Dockerfile.frontend
PRD.md		PRD.md
README.md		README.md
bun.lockb		bun.lockb
components.json		components.json
docker-compose.yml		docker-compose.yml
eslint.config.js		eslint.config.js
index.html		index.html
package-lock.json		package-lock.json
package.json		package.json
postcss.config.js		postcss.config.js
tailwind.config.ts		tailwind.config.ts
tsconfig.app.json		tsconfig.app.json
tsconfig.json		tsconfig.json
tsconfig.node.json		tsconfig.node.json
vite.config.ts		vite.config.ts

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