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Audio Based Jailbreak Attacks on LLMs
Large language models (LLMs) are increasingly integrating various data types, such as text, images, and audio, into a single framework, model or system known as multi-modal LLMs. These are capable of understanding and generating human-like responses, making them invaluable in numerous applications ranging from customer service to content creation. Despite their advanced capabilities, these LLMs are also susceptible to the same jailbreaks and adversarial attacks as traditional LLMs. In fact, their multi-modality increases the vectors through which they can be attacked. For example, jailbreaks—techniques used to bypass the models' intended constraints and safety measures—can be delivered within hidden payloads that exploit the model's ability to process not just text, but also audio and images. In this blog, we will explore a sophisticated form of jailbreak attack: embedding secret audio messages within audio inputs that are undetectable by human listeners but recognized and executed by LLMs. https://mindgard.ai/blog/audio-based-jailbreak-attacks-on-multi-modal-llms