Paper ID: 2402.05526

Buffer Overflow in Mixture of Experts

Jamie Hayes, Ilia Shumailov, Itay Yona

Mixture of Experts (MoE) has become a key ingredient for scaling large foundation models while keeping inference costs steady. We show that expert routing strategies that have cross-batch dependencies are vulnerable to attacks. Malicious queries can be sent to a model and can affect a model's output on other benign queries if they are grouped in the same batch. We demonstrate this via a proof-of-concept attack in a toy experimental setting.

Submitted: Feb 8, 2024