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awesome-red-teaming-llms

Repository accompanying a paper on Red-Teaming for Large Language Models (LLMs).

Introduction

Awesome Red-Teaming LLMs

The Awesome Red-Teaming LLMs repository provides a comprehensive guide on attacks, defenses, and red-teaming strategies for Large Language Models (LLMs).

Key Features:
  • Red-Teaming Attack Taxonomy: Detailed classification of various attack types against LLMs.
  • Surveys and Resources: Curated lists and references to additional surveys on red-teaming.
  • Contribution Welcome: Open to contributions from the community to expand the taxonomy.
Benefits:
  • Enhances understanding of threat modeling and operationalizing security frameworks for LLMs.
  • Provides researchers and practitioners with necessary tools and knowledge to effectively red-team AI systems.
Highlights:
  • Based on the paper "Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)" published on arXiv.
  • Actively maintained repository with a growing number of resources to assist in LLM security assessments.

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