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cs.CR2026
AgentSnare: Learning to Delay, Divert, and Defuse Autonomous Penetration Agents
Ruoyu Wang, Heng Zhao, Renjie Wu +4
Large language model (LLM) agents automate penetration testing through an observation-action loop, selecting actions based on observations returned by tools. This dependence allows…
cs.CR2026
CoreUnlearn: Rethinking Concept Unlearning through Disentangled Component-Level Erasure in Text-guided Diffusion Models
Mengnan Zhao, Lihe Zhang, Baocai Yin
Text guided diffusion models have revolutionized image synthesis but also raise ethical concerns, such as privacy violation and harmful content generation. To mitigate these issues…