6 papers
AgentCyberRange: Benchmarking Frontier AI Systems in Realistic Cyber Ranges
Fengyu Liu, Jiarun Dai, Yihe Fan +11
Frontier AI systems are increasingly capable of cybersecurity tasks, including codebase inspection, vulnerability detection, and exploitation. However, evaluating their offensive c…
CyberEvolver: Structured Self-Evolution for Cybersecurity Agents On the Fly
Yihe Fan, Changyi Li, Lichen Xu +4
LLM-based agents are increasingly used for cybersecurity tasks, but most existing systems rely on fixed, human-designed scaffolds that struggle to adapt across diverse targets and…
FlowGuard: Towards Lightweight In-Generation Safety Detection for Diffusion Models via Linear Latent Decoding
Jinghan Yang, Yihe Fan, Xudong Pan +1
Diffusion-based image generation models have advanced rapidly but pose a safety risk due to their potential to generate Not-Safe-For-Work (NSFW) content. Existing NSFW detection me…
Evaluation Faking: Unveiling Observer Effects in Safety Evaluation of Frontier AI Systems
Yihe Fan, Wenqi Zhang, Xudong Pan +1
As foundation models grow increasingly more intelligent, reliable and trustworthy safety evaluation becomes more indispensable than ever. However, an important question arises: Whe…
Large language model-powered AI systems achieve self-replication with no human intervention
Xudong Pan, Jiarun Dai, Yihe Fan +3
Self-replication with no human intervention is broadly recognized as one of the principal red lines associated with frontier AI systems. While leading corporations such as OpenAI a…
Frontier AI systems have surpassed the self-replicating red line
Xudong Pan, Jiarun Dai, Yihe Fan +1
Successful self-replication under no human assistance is the essential step for AI to outsmart the human beings, and is an early signal for rogue AIs. That is why self-replication…