This work formalizes agent reconnaissance by modeling the process and identifying the knowledge assets it seeks to extract, and instantiates KYA, a framework that automates black-box, reconnaissance-driven pentesting by probing agents, building target profiles, and using those profiles to craft stronger attacks.
O. Eliav, Eyal Lenga, Shir Bernstien et al.· arXiv.org· 0 citations
This work proposes a novel data-free model extraction attack that substantially outperforms current methods in efficiency, accuracy, and overall effectiveness and offers extensions to the algorithm to enable it to work on complex models.
Doron Ben Chayim, Maor Biton Dor, Eyal Lenga et al.· ACM Transactions on Intellig...· 0 citations
We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prior attacks that rely on deployment-specific assumptions, such as shared data memory, CPU offloading, or Mixture-of-Experts architectures, our approach targets the detokeni...
Roy Weiss, B. Konstantinov, Eitam Sheetrit et al.· 0 citations
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