This repository is a curated collection of resources focused on Large Language Model (LLM) security, targeting researchers, developers, and security professionals. It aims to consolidate tools, papers, articles, and benchmarks related to LLM vulnerabilities, attacks, and defenses, providing a centralized hub for understanding and mitigating risks in LLM applications.

How It Works

The project functions as an "awesome list," meticulously categorizing and linking to a wide array of academic papers, practical tools, and informative articles. It covers various attack vectors such as white-box, black-box, and backdoor attacks, alongside defense mechanisms, platform security, and benchmarking efforts. The organization into specific categories facilitates efficient navigation and research into LLM security threats and solutions.

Quick Start & Requirements

This is a curated list, not a software package. No installation or execution is required. The primary use is for research and reference.

Highlighted Details

• Extensive categorization of academic papers, including links to papers and associated code repositories where available.
• A comprehensive list of tools for LLM security assessment, including scanners, fuzzers, and prompt injection detectors.
• Coverage of emerging attack types like indirect prompt injection, backdoor attacks, and fingerprinting.
• Inclusion of surveys and articles that provide broader context and practical advice on LLM security.

Maintenance & Community

Contributions are welcomed, with guidelines provided for submission. The project actively links to relevant social media and blogs for ongoing community engagement and updates.

Licensing & Compatibility

The repository itself is likely under a permissive license (e.g., MIT, Apache 2.0) given its nature as a curated list, but individual linked resources may have different licenses. Compatibility for commercial use depends on the licenses of the linked tools and papers.

Limitations & Caveats

As a curated list, the project's content is dependent on external contributions and the availability of linked resources. The rapidly evolving nature of LLM security means the list requires continuous updates to remain comprehensive and current.