3 citations · 7 across the 24 of their papers we have counts for
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…
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…
Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment
Hao Li, Lijun Li, Zhenghao Lu +4
With rapid advancement and increasing accessibility of LLMs, fine-tuning aligned models has become a critical step for adapting them to real-world applications, which makes the saf…