#vulnerability-research2 articles

2 articles

AIBearisharXiv – CS AI · 17h ago7/10

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Depth Charge: Jailbreak Large Language Models from Deep Safety Attention Heads

Researchers have developed SAHA (Safety Attention Head Attack), a new jailbreak framework that exploits vulnerabilities in deeper attention layers of open-source large language models. The method improves attack success rates by 14% over existing techniques by targeting insufficiently aligned attention heads rather than surface-level prompts.

AIBearisharXiv – CS AI · Feb 276/107

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Analysis of LLMs Against Prompt Injection and Jailbreak Attacks

Researchers evaluated prompt injection and jailbreak vulnerabilities across multiple open-source LLMs including Phi, Mistral, DeepSeek-R1, Llama 3.2, Qwen, and Gemma. The study found significant behavioral variations across models and that lightweight defense mechanisms can be consistently bypassed by long, reasoning-heavy prompts.