collaborators

7 papers

cs.CR2026

SkillSentry: Adaptive Honey Worlds for Dynamic Safety Testing of Agent Skills

Nizhang Li, Zonghao Ying, Xiangfan Wu +7

External skills extend the capabilities of large language model agents, but also introduce an execution-time attack surface: a skill that appears benign under inspection may reveal…

cs.CR2026

SafeHarbor: Defining Precise Decision Boundaries via Hierarchical Memory-Augmented Guardrail for LLM Agent Safety

Zhe Liu, Zonghao Ying, Wenxin Zhang +5

Recent advances in foundation models have transformed LLMs from passive conversational systems into autonomous agents capable of reasoning and tool execution. While these capabilit…

cs.CV2026

TrajShield: Trajectory-Level Safety Mediation for Defending Text-to-Video Models Against Jailbreak Attacks

Quanchen Zou, Nizhang Li, Wenxin Zhang +4

Text-to-Video (T2V) models have demonstrated remarkable capability in generating temporally coherent videos from natural language prompts, yet they also risk producing unsafe conte…

cs.CR2026

SecureWebArena: A Holistic Security Evaluation Benchmark for LVLM-based Web Agents

Zonghao Ying, Yangguang Shao, Jianle Gan +8

Large vision-language model (LVLM)-based web agents are emerging as powerful tools for automating complex online tasks. However, when deployed in real-world environments, they face…

cs.CV2026

SPARK: Jailbreaking T2V Models by Synergistically Prompting Auditory and Recontextualized Knowledge

Zonghao Ying, Moyang Chen, Nizhang Li +6

Jailbreak attacks can circumvent model safety guardrails and reveal critical blind spots. Prior attacks on text-to-video (T2V) models typically add adversarial perturbations to obv…

cs.CL2026

Mask-GCG: Are All Tokens in Adversarial Suffixes Necessary for Jailbreak Attacks?

Junjie Mu, Zonghao Ying, Zhekui Fan +6

Jailbreak attacks on Large Language Models (LLMs) have demonstrated various successful methods whereby attackers manipulate models into generating harmful responses that they are d…