Awesome-LM-SSP and LLM-security-and-privacy
About Awesome-LM-SSP
CryptoAILab/Awesome-LM-SSP
A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).
This resource helps researchers and practitioners in the field of large models understand and mitigate risks related to safety, security, and privacy. It provides a curated reading list and database of research papers, books, competitions, and toolkits on topics like jailbreaking, adversarial attacks, and data privacy. Anyone working on or deploying large language, vision-language, or diffusion models would find this valuable.
About LLM-security-and-privacy
briland/LLM-security-and-privacy
LLM security and privacy
This resource provides a curated collection of research papers and tools focused on the security and privacy risks associated with Large Language Models (LLMs). It helps AI security researchers, cybersecurity professionals, and AI system developers understand potential threats and vulnerabilities in LLMs. The input is a collection of papers and tools, and the output is a categorized list with summaries and citations to inform research and mitigation strategies.
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