#Prompt Injection

The resource provides an extensive overview of security and privacy challenges in large language models (LLMs), focusing on vulnerabilities like prompt injection, remote code execution, and adversarial attacks. It explores various attack taxonomies, benchmarks, and the susceptibility of applications to these threats. Regular updates on GitHub and Notion make it an essential reference for researchers and developers aiming to protect LLM applications, outlining key risks and potential mitigation strategies.

Rebuff provides robust protection for AI applications by detecting prompt injection attacks using a multi-layered system including heuristics, LLM-based detection, VectorDB, and canary tokens. This prototype aims to filter malicious inputs, analyze prompts, and prevent future attacks by utilizing past data. It currently offers a JavaScript/TypeScript SDK with plans for a Python SDK and user-defined strategies. The platform supports self-hosting by integrating with providers such as Pinecone and Supabase for database management.

Explore a curated collection of tools, papers, and resources focused on improving Large Language Model (LLM) security. This repository addresses various attack strategies, including white-box, black-box, and backdoor methods, along with defensive measures and platform evaluations. Delve into recent advancements and research on adversarial attacks and prompt injection. Learn about security tools such as Plexiglass and PurpleLlama aimed at testing and protecting LLMs. Access essential information for researchers, developers, and security professionals in the field of LLM security.

Discover cutting-edge developments in GPT prompting, emphasizing jailbreak strategies, prompt leakage, and security measures. The project provides resources from ChatGPT jailbreaks to prompt injections and AI prompt engineering, including adversarial machine learning. It includes comprehensive repositories and communities focused on system prompt leaks and mastery of prompt engineering. Ideal for those aiming to mitigate vulnerabilities or boost prompt efficiency, this collection delivers essential tools, techniques, and practices.