yueliu1999/Awesome-Jailbreak-on-LLMs

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, exciting jailbreak methods on LLMs. It contains papers, codes, datasets, evaluations, and analyses.

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This resource provides a curated collection of techniques for evaluating and improving the safety of Large Language Models (LLMs). It includes research papers, code, and datasets related to both 'jailbreak' attacks (attempts to bypass safety mechanisms) and defenses against them. AI safety researchers and practitioners who are building or deploying LLMs would use this to understand vulnerabilities and develop more robust, responsible AI systems.

1,245 stars. Actively maintained with 14 commits in the last 30 days.

Use this if you are a researcher or engineer focused on understanding, testing, and hardening the safety mechanisms of Large Language Models against adversarial exploits.

Not ideal if you are looking for a plug-and-play tool for general LLM development or for simple prompt engineering.

AI-safety LLM-security AI-ethics adversarial-AI responsible-AI
No Package No Dependents
Maintenance 17 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

1,245

Forks

101

Language

License

MIT

Last pushed

Mar 07, 2026

Commits (30d)

14

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