Multi-Turn Jailbreaking Attack in Multi-Modal Large Language Models

In recent years, the security vulnerabilities of Multi-modal Large Language Models MLLMs have become a serious concern in the Generative Artificial Intelligence GenAI research. These highly intelligent models, capable of performing multi-modal tasks with high accuracy, are also severely susceptib...

Invisible Injections: Exploiting Vision-Language Models through Steganographic Prompt Embedding

Vision-language models VLMs have revolutionized multimodal AI applications but introduce novel security vulnerabilities that remain largely unexplored. We present the first comprehensive study of steganographic prompt injection attacks against VLMs, where malicious instructions are invisibly...