Physical Side-Channel Attacks on Edge LLMs: Extracting Output Tokens and User Prompts

Reported by arXiv cs.CR (Najeh Alhalawani, Gunes Acar, Zhuoran Liu, Lejla Batina)

Summary by Cyber Security News14 Oct 2026, 06:00 CEST

About this summary. This is a short, independently written summary of an article first published by arXiv cs.CR. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.14215

arXiv:2610.14215v1 Announce Type: new Abstract: The deployment of large language models (LLMs) on edge devices is largely motivated by privacy concerns over sharing sensitive user data with cloud servers. In this paper, we demonstrate that keeping inference local does not eliminate privacy risks: an adversary with physical access to the device may exploit hardware leakage to recover sensitive information without compromising or modifying the software system.

Read the full article at arXiv cs.CR →

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