SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense

Text-to-Video (T2V) generative models are vulnerable to jailbreak attacks in real-world deployment, leading them to produce harmful or inappropriate content. Existing defense approaches mainly rely on input filtering or reconstruction, which not only incur high computational latency but also tend to distort semantics. To address these issues, we experimentally and systematically analyze the differences between clean and jailbreak samples in the cross-attention feature space, revealing for the fi

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ethics.ai (11 August 2026), “SafeCA: Safe Cross-Attention Localization and Regulation for Text-to-Video Jailbreak Defense,” evidence record 18686, https://ethics.ai/record/18686 (originally published by arXiv red teaming query).

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