awesome-ai-security

🥈Silver

A curated collection of AI security resources for operations teams. Helps identify vulnerabilities, implement best practices, and stay updated on AI security trends. Integrates with Claude to provide actionable insights and recommendations.

5141130Updated 1mo ago

Intermediate30min to implementautomation

Saves ~10 min per use

Quick InstallView Source

git clone https://github.com/ottosulin/awesome-ai-security.git

Works with:

Claude

Overview

About This Skill

https://github.com/ottosulin/awesome-ai-security

Use Cases

Automate the assessment of AI security frameworks and standards for compliance.

Integrate learning resources into training programs for AI security best practices.

Utilize offensive tools to simulate vulnerabilities in AI systems for testing.

Access curated podcasts and articles to stay informed about the latest trends in AI security.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/ottosulin/awesome-ai-security

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I'm looking for a comprehensive list of AI security resources for my [COMPANY] in the [INDUSTRY] sector. Can you provide me with the latest best practices, tools, and frameworks related to AI security? Please include [DATA] that is relevant to my needs.

Example Output

## AI Security Resources for TechCorp in the Financial Industry

1. **Best Practices**:
   - Implement regular security audits to assess vulnerabilities in AI models.
   - Use adversarial training techniques to improve model robustness.

2. **Tools**:
   - **AI-Sec**: A tool for monitoring AI systems in real-time for anomalies.
   - **SecureML**: Framework for secure machine learning deployment.

3. **Frameworks**:
   - **TensorFlow Privacy**: A library for adding differential privacy to TensorFlow models.
   - **OpenAI Security Toolkit**: A set of guidelines and tools for securing AI applications.

4. **Case Studies**:
   - TechCorp successfully reduced fraud detection errors by 30% using adversarial training methods.
   - A recent collaboration with SecureML led to a 50% improvement in model security metrics.