5 papers · 1 filter
CyberPersistBench: Evaluating LLM-Based Cyber Attackers on Installation and Persistence
Sujin Chen, Lijun Li, Xuhong Wang +1
While LLM-based attackers exhibit growing proficiency in vulnerability exploitation, most existing cybersecurity benchmarks suffer from single-stage truncation, prematurely termina…
Defense-as-Skill: Evolving Runtime Guard Skill for Skill-Augmented Agents
Xiaofang Yang, Ziqi Miao, Chen Qian +3
Skill-augmented agents load reusable skills as persistent runtime context, improving task performance but also giving malicious skills a durable channel for steering future actions…
MobileWorldSafety: Benchmarking GUI Agent Safety Against Environmental Injection Attacks in Android Apps
Sujin Chen, Lijun Li, Tianyi Du +1
LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment. However, because these agents routin…
Collaborative Shadows: Distributed Backdoor Attacks in LLM-Based Multi-Agent Systems
Pengyu Zhu, Lijun Li, Yaxing Lyu +3
LLM-based multi-agent systems (MAS) demonstrate increasing integration into next-generation applications, but their safety in backdoor attacks remains largely underexplored. Howeve…
HarmRLVR: Weaponizing Verifiable Rewards for Harmful LLM Alignment
Yuexiao Liu, Lijun Li, Xingjun Wang +1
Recent advancements in Reinforcement Learning with Verifiable Rewards (RLVR) have gained significant attention due to their objective and verifiable reward signals, demonstrating s…