Efficient LLM-Jailbreaking via Multimodal-LLM Jailbreak

Understand

This paper focuses on jailbreaking attacks against large language models (LLMs), eliciting them to generate objectionable content in response to harmful user queries.

• Unlike previous LLM-jailbreak methods that directly orient to LLMs, our approach begins by constructing a multimodal large language model (MLLM) built upon the target LLM.
• Subsequently, we perform an efficient MLLM jailbreak and obtain a jailbreaking embedding.
• Finally, we convert the embedding into a textual jailbreaking suffix to carry out the jailbreak of target LLM.