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Sadegh Majidi

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Jul 2026

Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing

This work presents LeakyLMs, a set of attacks that leak proprietary model, architecture, and deployment information from production language models. LeakyLMs is the first to demonstrate that key model and deployment details can be inferred using only token generation timing, even when interacting through remote APIs. L...

Sadegh Majidi, Niloofar Mireshghallah, Kazem Taram · 0 citations

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