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.
1,882 stars. Actively maintained with 12 commits in the last 30 days.
Use this if you need to quickly find academic papers, benchmarks, or toolkits related to ensuring the trustworthiness of large AI models.
Not ideal if you are looking for an executable software library or an in-depth tutorial on how to implement specific safety features.
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1,882
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Apache-2.0
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Last pushed
Mar 04, 2026
Commits (30d)
12
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