AI Security Code Examples

This repository contains practical code examples for implementing AI security measures against prompt injection attacks and other LLM vulnerabilities.

Repository Structure

ai-security-code-examples/
├── traditional-security/          # Traditional security approaches
├── ai-aware-security/             # AI-specific security implementations
├── promptfoo-configs/             # Promptfoo configuration examples
├── defensive-prompts/             # Defensive prompt architectures
├── monitoring-systems/            # Real-time monitoring implementations
├── incident-response/             # Automated incident response
├── metrics-frameworks/            # Security metrics and ROI calculations
└── deployment-scripts/            # Quick deployment automation

Quick Start

1. Install Dependencies

   npm install -g promptfoo
   pip install -r requirements.txt

2. Run Security Assessment

   cd promptfoo-configs
   promptfoo redteam run --config comprehensive-security.yaml

3. Deploy Basic Security

   cd deployment-scripts
   ./emergency-deployment.sh

Key Features

• ✅ Complete OWASP LLM Top 10 coverage
• ✅ Traditional vs AI-aware security comparisons
• ✅ Production-ready Promptfoo configurations
• ✅ Defensive prompt architectures
• ✅ Real-time monitoring systems
• ✅ Automated incident response
• ✅ ROI and metrics frameworks

Documentation

Each directory contains detailed README files with:

• Implementation guides
• Code explanations
• Usage examples
• Best practices

License

MIT License - See LICENSE file for details

Contributing

Pull requests welcome! Please read CONTRIBUTING.md for guidelines.