Papers with jailbreak attack algorithms

2 papers
LLMs Caught in the Crossfire: Malware Requests and Jailbreak Challenges (2025.acl-long)

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Challenge: Large Language Models (LLMs) have a high vulnerability to jailbreak attacks that leverage crafted prompts to generate malicious outputs.
Approach: They propose to use large language models to test their security against jailbreak attacks that leverage crafted prompts to generate malicious outputs.
Outcome: The proposed model is based on 320 manually crafted malicious code generation requirements, covering 11 jailbreak methods and 29 code functionality categories.
Jailbreak Distillation: Renewable Safety Benchmarking (2025.findings-emnlp)

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Challenge: a new framework for safety benchmarking is being developed for large language models . the framework "distills" jailbreak attacks into high-quality and easily-updatable safety benchmarks .
Approach: They propose a framework that "distills" jailbreak attacks into high-quality safety benchmarks.
Outcome: The proposed framework "distills" jailbreak attacks into high-quality safety benchmarks . it requires minimal human effort to rerun the pipeline and produce updated benchmarks.

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