AI-powered cloud security tool that scans AWS environments for common misconfigurations and vulnerabilities. It provides actionable insights and even command-level fixes using LLMs to enhance cloud security with minimal setup.

• AI-Powered Security Platform: Built with Go (Gin) and Python (FastAPI) backends, and React.js/Next.js frontend
• AWS Service Scanners: Comprehensive security analysis for IAM, EC2, S3, Lambda, DynamoDB, and ECS
• LLM-Based Remediation: Automated command-line fixes for misconfigurations using DSPy for robust structures on unreliable LLM outputs
• GraphQL API: Real-time security scanning and vulnerability management with PostgreSQL database
• Docker Deployment: Multi-environment support (development/production)
• Extensible Architecture: Supports multiple cloud providers with role-based access control
• SaaS Functionality: Authentication middleware and Stripe payment webhook integration

• Docker 24+
• Docker Compose v2+
• 8GB RAM minimum

1. Clone the repository:

   git clone https://github.com/PhantomInTheWire/CloudCop.git
   cd CloudCop

2. Copy environment file:

   cp .env.example .env
   # Edit .env and add your OPENAI_API_KEY

3. Start all services:

   npm run dev

Services will be available at:

• Frontend: http://localhost:3000 - Next.js Dashboard
• Backend GraphQL: http://localhost:8080/graphql - Go API
• Kestra: http://localhost:8081 - AI Agent Orchestration
• Neo4j Browser: http://localhost:7474 - Security Graph (user: neo4j, password: from .env)
• PostgreSQL: localhost:5432 - Metadata & Results

We provide a comprehensive E2E test suite that runs against LocalStack (simulating AWS) and the AI Service.

1. Prerequisites:

   • Docker & Docker Compose
   • Go 1.21+ (for running tests locally)
   • (Optional) OpenAI API Key for real AI summaries

2. Run Full AI Demo: This single command starts the entire stack, creates 20+ misconfigured AWS resources (S3, EC2, IAM, Lambda, DynamoDB), runs the security scanner, and validates the AI summaries and remediation commands.

   cd backend/api
   export OPENAI_API_KEY=sk-your-key # Optional
   make e2e-ai-demo

   What happens:

   • Starts LocalStack, Postgres, Neo4j, and Python AI Service
   • Simulates a compromised AWS environment with 20+ vulnerabilities
   • Runs the Go Scanner via SecurityService
   • AI Agent analyzes findings and generates specific AWS CLI remediation commands
   • Verifies the GraphQL API response includes these summaries

3. Cleanup:

   make e2e-ai-down

• Start Infrastructure:

  npm run dev

• Scanner Unit Tests:

  cd backend/api
  go test ./internal/scanner/...

• GraphQL Playground: Open http://localhost:8080/graphql after starting infrastructure.

For support, please open an issue in the standard GitHub issue tracker.

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