Cover Image

White-box Multimodal Jailbreaks Against Large Vision-Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Ruofan, Ma, Xingjun, Zhou, Hanxu, Ji, Chuanjun, Ye, Guangnan, Jiang, Yu-Gang
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

IDEATOR: Jailbreaking and Benchmarking Large Vision-Language Models Using Themselves
by: Wang, Ruofan, et al.
Published: (2024)

BlueSuffix: Reinforced Blue Teaming for Vision-Language Models Against Jailbreak Attacks
by: Zhao, Yunhan, et al.
Published: (2024)

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion
by: Wang, Ruofan, et al.
Published: (2025)

Defense-to-Attack: Bypassing Weak Defenses Enables Stronger Jailbreaks in Vision-Language Models
by: Zhao, Yunhan, et al.
Published: (2025)

Simulated Ensemble Attack: Transferring Jailbreaks Across Fine-tuned Vision-Language Models
by: Wang, Ruofan, et al.
Published: (2025)

Adversarial Prompt Distillation for Vision-Language Models
by: Luo, Lin, et al.
Published: (2024)

Steering Away from Harm: An Adaptive Approach to Defending Vision Language Model Against Jailbreaks
by: Wang, Han, et al.
Published: (2024)

Adversarial Prompt Tuning for Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2023)

Toward Universal and Transferable Jailbreak Attacks on Vision-Language Models
by: Cui, Kaiyuan, et al.
Published: (2026)

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models
by: Zhang, Jiaming, et al.
Published: (2025)

Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers
by: Zheng, Weijie, et al.
Published: (2024)

Jailbreaks on Vision Language Model via Multimodal Reasoning
by: Noheria, Aarush, et al.
Published: (2026)

FedAPT: Federated Adversarial Prompt Tuning for Vision-Language Models
by: Zhai, Kun, et al.
Published: (2025)

SafeVid: Toward Safety Aligned Video Large Multimodal Models
by: Wang, Yixu, et al.
Published: (2025)

Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks
by: Xie, Yong, et al.
Published: (2024)

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models
by: Wang, Xin, et al.
Published: (2026)

JailBound: Jailbreaking Internal Safety Boundaries of Vision-Language Models
by: Song, Jiaxin, et al.
Published: (2025)

AttackVLA: Benchmarking Adversarial and Backdoor Attacks on Vision-Language-Action Models
by: Li, Jiayu, et al.
Published: (2025)

Securing Vision-Language Models with a Robust Encoder Against Jailbreak and Adversarial Attacks
by: Hossain, Md Zarif, et al.
Published: (2024)

Activation Steering Meets Preference Optimization: Defense Against Jailbreaks in Vision Language Models
by: Wu, Sihao, et al.
Published: (2025)

SAMA: Towards Multi-Turn Referential Grounded Video Chat with Large Language Models
by: Sun, Ye, et al.
Published: (2025)

Learning to Detect Unknown Jailbreak Attacks in Large Vision-Language Models
by: Liang, Shuang, et al.
Published: (2025)

B-AVIBench: Towards Evaluating the Robustness of Large Vision-Language Model on Black-box Adversarial Visual-Instructions
by: Zhang, Hao, et al.
Published: (2024)

Steering the Verifiability of Multimodal AI Hallucinations
by: Pang, Jianhong, et al.
Published: (2026)

DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models
by: Sun, Ye, et al.
Published: (2026)

Robust Multimodal Large Language Models Against Modality Conflict
by: Zhang, Zongmeng, et al.
Published: (2025)

E$^2$AT: Multimodal Jailbreak Defense via Dynamic Joint Optimization for Multimodal Large Language Models
by: Lu, Liming, et al.
Published: (2025)

SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models
by: Dong, Xiangyu, et al.
Published: (2025)

Beyond Visual Safety: Jailbreaking Multimodal Large Language Models for Harmful Image Generation via Semantic-Agnostic Inputs
by: Yu, Mingyu, et al.
Published: (2026)

Jailbreaking Multimodal Large Language Models using Multi-Clip Video
by: Kang, Choongwon, et al.
Published: (2026)

INF-LLaVA: Dual-perspective Perception for High-Resolution Multimodal Large Language Model
by: Ma, Yiwei, et al.
Published: (2024)

Learning to Detect Unseen Jailbreak Attacks in Large Vision-Language Models
by: Liang, Shuang, et al.
Published: (2025)

PixelSmile: Toward Fine-Grained Facial Expression Editing
by: Hua, Jiabin, et al.
Published: (2026)

Text is All You Need for Vision-Language Model Jailbreaking
by: Chen, Yihang, et al.
Published: (2026)

Jailbreak Large Vision-Language Models Through Multi-Modal Linkage
by: Wang, Yu, et al.
Published: (2024)

ImgTrojan: Jailbreaking Vision-Language Models with ONE Image
by: Tao, Xijia, et al.
Published: (2024)

Divide-and-Conquer Inference for Large-Scale Visual Recognition with Multimodal Large Language Models
by: Ye, Zhipeng, et al.
Published: (2026)

T2UE: Generating Unlearnable Examples from Text Descriptions
by: Ma, Xingjun, et al.
Published: (2025)

Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
by: Yin, Jianghao, et al.
Published: (2026)

TAIJI: Textual Anchoring for Immunizing Jailbreak Images in Vision Language Models
by: Yin, Xiangyu, et al.
Published: (2025)