Papers with multimodal jailbreak attacks

2 papers
FC-Attack: Jailbreaking Multimodal Large Language Models via Auto-Generated Flowcharts (2025.findings-emnlp)

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Challenge: Recent research shows that multimodal large language models are vulnerable to jailbreak attacks .
Approach: They propose a jailbreak attack method based on auto-generated flowcharts . the flowchartings are then combined with a benign textual prompt to execute the attack .
Outcome: The proposed method achieves an attack success rate of up to 96% via images and 78% via videos across multiple MLLMs.
ReCon: Active Defense against Large Vision-Language Model Jailbreaks via Reverse Safety Concept Injection (2026.findings-acl)

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Challenge: Existing defense strategies neglect visual threats and lack of fine-grained specificity regarding specific attack semantics.
Approach: They propose a black-box defense framework that maps unsafe concepts to fine-grained, constructive Safe Concepts.
Outcome: a new black-box defense framework enhances robustness against jailbreak attacks . it maps detected unsafe concepts to fine-grained, constructive Safe Concepts . the proposed framework is available for free at http://www.epa.org/recon/ .

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