4 papers
Red-TTT: Test-Time Training for Automated Jailbreaking Large Language Models
Tongyan Hu, Hao Li, Xiaogeng Liu +8
Large language models remain vulnerable to jailbreaks, and automated red teaming is the standard way to find jailbreaks in large language models at scale. Current methods either dr…
APTInvestBench: Evaluating Autonomous APT Investigation under Varying Telemetry
Yu Wang, Shuhao Li, Tao Yin +4
Large language model (LLM) agents could help security operations centers (SOCs) investigate advanced persistent threats (APTs) by turning weak leads into evidence for intrusion sco…
Same Request, Different Boundary: Evaluating Cybersecurity Assistance across Conversational Contexts
Rui Yang, Yang Hong, Yichao Xu +3
Cybersecurity assistance is dual use, requiring decisions about when to answer, limit, or refuse a request. Prior work studies refusal evaluation and conversational jailbreaking, b…
Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs
Xiaoyu Guo, Pengcheng Chen, Jiong Yu +3
Graph-augmented large language models often assume that graph evidence produced by external computation and placed in the input can be used by the native decoder. We test this assu…