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CVPR2025Top-tier venue

Mind the Trojan Horse: Image Prompt Adapter Enabling Scalable and Deceptive Jailbreaking

Junxi Chen, Junhao Dong, Xiaohua Xie

2025Year
3Top-tier citations

Abstract

Recently, the Image Prompt Adapter (IP-Adapter) has been increasingly integrated into text-to-image diffusion models (T2I-DMs) to improve controllability. However, in this paper, we reveal that T2I-DMs equipped with the IP-Adapter (T2I-IP-DMs) enable a new jailbreak attack named the hijacking attack. We demonstrate that, by uploading imperceptible image-space adversarial examples (AEs), the adversary can hijack massive benign users to jailbreak an Image Generation Service (IGS) driven by T2I-IP-DMs and mislead the public to discredit the service provider. Worse still, the IP-Adapter's dependency on open-source image encoders reduces the knowledge required to craft AEs. Extensive experiments verify the technical feasibility of the hijacking attack. In light of the revealed threat, we investigate several existing defenses and explore combining the IP-Adapter with adversarially trained models to overcome existing defenses' limitations. Our code is available at https://github.com/fhdnskfbeuv/ attackIPA. CAUTION: Though we have blacked out and blurred inappropriate images according to our values, this paper may still contain offensive or distressing content.

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