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Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

This paper focuses on jailbreaking attacks against multi-modal large language models (MLLMs), seeking to elicit MLLMs to generate objectionable responses to harmful user queries. A maximum likelihood-based algorithm is proposed to find an…

Machine Learning · Computer Science 2024-02-07 Zhenxing Niu , Haodong Ren , Xinbo Gao , Gang Hua , Rong Jin

Despite their superb capabilities, Vision-Language Models (VLMs) have been shown to be vulnerable to jailbreak attacks. While recent jailbreaks have achieved notable progress, their effectiveness and efficiency can still be improved. In…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Yunhan Zhao , Xiang Zheng , Xingjun Ma

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…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Junxi Chen , Junhao Dong , Xiaohua Xie

Recent AI systems have shown extremely powerful performance, even surpassing human performance, on various tasks such as information retrieval, language generation, and image generation based on large language models (LLMs). At the same…

Artificial Intelligence · Computer Science 2024-05-29 Minseon Kim , Hyomin Lee , Boqing Gong , Huishuai Zhang , Sung Ju Hwang

Recent advancements in Text-to-Image (T2I) models have raised significant safety concerns about their potential misuse for generating inappropriate or Not-Safe-For-Work (NSFW) contents, despite existing countermeasures such as NSFW…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Yijun Yang , Ruiyuan Gao , Xiao Yang , Jianyuan Zhong , Qiang Xu

As Large Language Models (LLMs) are increasingly being deployed in safety-critical applications, their vulnerability to potential jailbreaks -- malicious prompts that can disable the safety mechanism of LLMs -- has attracted growing…

Cryptography and Security · Computer Science 2024-08-08 Jiahao Zhang , Zilong Wang , Ruofan Wang , Xingjun Ma , Yu-Gang Jiang

Text-to-image (T2I) models have significantly advanced in producing high-quality images. However, such models have the ability to generate images containing not-safe-for-work (NSFW) content, such as pornography, violence, political content,…

Cryptography and Security · Computer Science 2025-05-15 Longtian Wang , Xiaofei Xie , Tianlin Li , Yuhan Zhi , Chao Shen

Text-to-Image models may generate harmful content, such as pornographic images, particularly when unsafe prompts are submitted. To address this issue, safety filters are often added on top of text-to-image models, or the models themselves…

Cryptography and Security · Computer Science 2026-01-09 Zhengyuan Jiang , Yuepeng Hu , Yuchen Yang , Yinzhi Cao , Neil Zhenqiang Gong

Jailbreaking large language models (LLMs) has emerged as a pressing concern with the increasing prevalence and accessibility of conversational LLMs. Adversarial users often exploit these models through carefully engineered prompts to elicit…

Computation and Language · Computer Science 2025-10-13 Sri Durga Sai Sowmya Kadali , Evangelos E. Papalexakis

Although safely enhanced Large Language Models (LLMs) have achieved remarkable success in tackling various complex tasks in a zero-shot manner, they remain susceptible to jailbreak attacks, particularly the unknown jailbreak attack. To…

Computation and Language · Computer Science 2024-06-12 Fan Liu , Zhao Xu , Hao Liu

Text-to-Image(T2I) models have achieved remarkable success in image generation and editing, yet these models still have many potential issues, particularly in generating inappropriate or Not-Safe-For-Work(NSFW) content. Strengthening…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Sensen Gao , Xiaojun Jia , Yihao Huang , Ranjie Duan , Jindong Gu , Yang Bai , Yang Liu , Qing Guo

Metaphor serves as an implicit approach to convey information, while enabling the generalized comprehension of complex subjects. However, metaphor can potentially be exploited to bypass the safety alignment mechanisms of Large Language…

Computation and Language · Computer Science 2025-02-25 Yu Yan , Sheng Sun , Junqi Tong , Min Liu , Qi Li

Text-to-image (T2I) generative models have revolutionized content creation by transforming textual descriptions into high-quality images. However, these models are vulnerable to jailbreaking attacks, where carefully crafted prompts bypass…

Cryptography and Security · Computer Science 2025-06-26 Yingkai Dong , Xiangtao Meng , Ning Yu , Zheng Li , Shanqing Guo

In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption. However, this progress has inadvertently opened avenues for potential misuse, particularly in generating inappropriate or…

Cryptography and Security · Computer Science 2024-04-02 Yijun Yang , Ruiyuan Gao , Xiaosen Wang , Tsung-Yi Ho , Nan Xu , Qiang Xu

We introduce new jailbreak attacks on vision language models (VLMs), which use aligned LLMs and are resilient to text-only jailbreak attacks. Specifically, we develop cross-modality attacks on alignment where we pair adversarial images…

Cryptography and Security · Computer Science 2023-10-12 Erfan Shayegani , Yue Dong , Nael Abu-Ghazaleh

In the realm of large vision language models (LVLMs), jailbreak attacks serve as a red-teaming approach to bypass guardrails and uncover safety implications. Existing jailbreaks predominantly focus on the visual modality, perturbing solely…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Zonghao Ying , Aishan Liu , Tianyuan Zhang , Zhengmin Yu , Siyuan Liang , Xianglong Liu , Dacheng Tao

Large Language Models (LLMs) have evolved into Multimodal Large Language Models (MLLMs), significantly enhancing their capabilities by integrating visual information and other types, thus aligning more closely with the nature of human…

Cryptography and Security · Computer Science 2025-06-03 Youze Wang , Wenbo Hu , Yinpeng Dong , Jing Liu , Hanwang Zhang , Richang Hong

Recently, Multimodal Large Language Models (MLLMs) have demonstrated their superior ability in understanding multimodal content. However, they remain vulnerable to jailbreak attacks, which exploit weaknesses in their safety alignment to…

Cryptography and Security · Computer Science 2025-08-29 Wenzhuo Xu , Zhipeng Wei , Xiongtao Sun , Zonghao Ying , Deyue Zhang , Dongdong Yang , Xiangzheng Zhang , Quanchen Zou

Multimodal Large Language Models (MLLMs) have showcased impressive performance in a variety of multimodal tasks. On the other hand, the integration of additional image modality may allow the malicious users to inject harmful content inside…

Cryptography and Security · Computer Science 2025-04-23 Yulin Chen , Haoran Li , Yirui Zhang , Zihao Zheng , Yangqiu Song , Bryan Hooi