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Prompt-Hacking-Resources

A curated list of resources for AI Red Teaming, Jailbreaking, and Prompt Injection.

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Introduction

Introduction to Prompt-Hacking-Resources

Prompt-Hacking-Resources is a comprehensive repository that offers a curated collection of resources aimed at individuals interested in the fields of AI Red Teaming, Jailbreaking, and Prompt Injection. It serves as a vital resource for anyone looking to explore and understand the vulnerabilities of Large Language Models (LLMs) and the techniques used in prompt hacking.

Key Features:
  • Curated Resource List: The repository provides a well-organized collection of blogs, communities, courses, events, and YouTube channels dedicated to prompt hacking and AI safety.
  • Diverse Categories: Resources are categorized into various sections such as Blogs, Communities, Courses, and Jailbreaks, making it easy to navigate and find relevant information.
  • Community Contribution: Contributions are encouraged from users, allowing the community to grow and share knowledge.
  • Focus on AI Security: The repository emphasizes understanding model limitations, promoting the safe exploration of prompt hacking methodologies, and documenting offensive research.
Benefits:
  • Stay Informed: Users can access expert analyses, tutorials, and research articles to stay updated with the latest in AI security.
  • Engage with Experts: The repository includes links to Discord communities and Reddit threads where users can engage in discussions and share insights.
  • Educational Opportunities: A variety of courses, ranging from beginner to advanced levels, are available for users to enhance their knowledge and skills in prompt engineering and AI safety.

By aggregating these vital resources, Prompt-Hacking-Resources aims to empower users in the emerging field of AI cybersecurity.

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Information

  • Publisher
    AISecKit
  • Websitegithub.com
  • Published date2025/04/27

Categories

  • Security Research

Tags

  • Prompt Injection
  • Model Robustness
  • Safety Alignments
  • Adversarial Examples

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