Whispering Pixels: Exploiting Uninitialized Register Accesses in Modern GPUs
Frederik Dermot Pustelnik, Xhani Marvin Sa{\ss}, Jean-Pierre Seifert

TL;DR
This paper reveals a new GPU vulnerability where uninitialized registers leak sensitive data, demonstrated across multiple vendors and capable of exposing neural network and LLM intermediate data.
Contribution
It uncovers a novel class of GPU vulnerabilities caused by uninitialized registers, with practical attack demonstrations on various workloads and hardware.
Findings
Leakage of pixel data from fragment shaders
Information extraction from CNN intermediate states
Reconstruction of LLM outputs
Abstract
Graphic Processing Units (GPUs) have transcended their traditional use-case of rendering graphics and nowadays also serve as a powerful platform for accelerating ubiquitous, non-graphical rendering tasks. One prominent task is inference of neural networks, which process vast amounts of personal data, such as audio, text or images. Thus, GPUs became integral components for handling vast amounts of potentially confidential data, which has awakened the interest of security researchers. This lead to the discovery of various vulnerabilities in GPUs in recent years. In this paper, we uncover yet another vulnerability class in GPUs: We found that some GPU implementations lack proper register initialization routines before shader execution, leading to unintended register content leakage of previously executed shader kernels. We showcase the existence of the aforementioned vulnerability on…
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Taxonomy
TopicsAdversarial Robustness in Machine Learning · Security and Verification in Computing · Digital and Cyber Forensics
