Structured Visual Narratives Undermine Safety Alignment in Multimodal Large Language Models
Multimodal Large Language Models (MLLMs) extend text-only LLMs with visual reasoning, but also introduce new safety failure modes under visually grounded instructions. We study comic-template jailbreaks that embed harmful goals inside simple three-panel visual narratives and prompt the model to role-play and "complete the comic." Building on JailbreakBench and JailbreakV, we introduce ComicJailbreak, a comic-based jailbreak benchmark with 1,167 attack instances spanning 10 harm categories and 5 task setups. Across 15 state-of-the-art MLLMs (six commercial and nine open-source), comic-based attacks achieve success rates comparable to strong rule-based jailbreaks and substantially outperfor...
| Authors | Rui Yang Tan, Yujia Hu, Roy Ka-Wei Lee |
|---|---|
| Primary category | cs.CR |
| Published | 23 March 2026 |
| Last updated at source | 23 April 2026 |
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