Jailbreaking Vision-Language Models with Typographic Images
Published on:
9 November 2023
Primary Category:
Cryptography and Security
Paper Authors:
Yichen Gong,
Delong Ran,
Jinyuan Liu,
Conglei Wang,
Tianshuo Cong,
Anyu Wang,
Sisi Duan,
Xiaoyun Wang
Bullets
Key Details
FigStep embeds harmful text as images to bypass text-only safety alignment of models
It combines these image prompts with benign text prompts in a 'continuation task'
FigStep achieved 95% attack success on average across 5 open source vision-language models
It also succeeded in jailbreaking the robust GPT-4V model via additional processing
The method highlights gaps in safety alignment across textual and visual modalities
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AI generated summary
Jailbreaking Vision-Language Models with Typographic Images
This paper proposes a method called FigStep to jailbreak vision-language models by embedding harmful text instructions into images paired with benign text prompts. The method is highly effective at inducing models to generate prohibited content.
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