Sadegh Majidi

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

Sadegh Majidi, Niloofar Mireshghallah, Kazem Taram

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…Read more