1 citations · 1 across the 6 of their papers we have counts for
6 papers
When the Manual Lies: A Realistic Benchmark to Evaluate MCP Poisoning Attacks for LLM Agents
Shi Liu, Xuehai Tang, Xikang Yang +4
The rise of tool-using Large Language Model (LLM) agents, standardized by protocols like the Model Context Protocol (MCP), has unlocked unprecedented autonomous execution capabilit…
Hidden in the Noise: Unveiling Backdoors in Audio LLMs Alignment through Latent Acoustic Pattern Triggers
Liang Lin, Miao Yu, Kaiwen Luo +9
As Audio Large Language Models (ALLMs) emerge as powerful tools for speech processing, their safety implications demand urgent attention. While considerable research has explored t…
Exploiting Synergistic Cognitive Biases to Bypass Safety in LLMs
Xikang Yang, Biyu Zhou, Xuehai Tang +2
Large Language Models (LLMs) demonstrate impressive capabilities across a wide range of tasks, yet their safety mechanisms remain susceptible to adversarial attacks that exploit co…
The Dark Side of Trust: Authority Citation-Driven Jailbreak Attacks on Large Language Models
Xikang Yang, Xuehai Tang, Jizhong Han +1
The widespread deployment of large language models (LLMs) across various domains has showcased their immense potential while exposing significant safety vulnerabilities. A major co…
Enhancing Cross-Prompt Transferability in Vision-Language Models through Contextual Injection of Target Tokens
Xikang Yang, Xuehai Tang, Fuqing Zhu +2
Vision-language models (VLMs) seamlessly integrate visual and textual data to perform tasks such as image classification, caption generation, and visual question answering. However…
Chain of Attack: a Semantic-Driven Contextual Multi-Turn attacker for LLM
Xikang Yang, Xuehai Tang, Songlin Hu +1
Large language models (LLMs) have achieved remarkable performance in various natural language processing tasks, especially in dialogue systems. However, LLM may also pose security…