GPU.zip: On the Side-Channel Implications of Hardware-Based Graphical Data Compression

Abstract

Compression is a widely-deployed optimization that reduces data movement throughout modern computing stacks. Unfortunately, it is also a well-known source of side-channel leakage capable of leaking (potentially) fine-grained functions of the underlying data. There has, however, been a saving grace. Compression is typically software visible. Thus, software can "opt out" of harm’s way by disabling compression when sensitive data is involved, and tailor mitigations to known, public compression algorithms.This paper challenges the above conventional wisdom by demonstrating the existence of, and exploiting, software-transparent uses of compression. Specifically, we find that integrated GPUs from Intel and AMD vendors compress graphical data in vendor-specific and undocumented ways—even when software does not specifically request compression. Compression induces data-dependent DRAM traffic and cache utilization, which can be measured through side-channel analysis. We show the efficacy of this side channel by performing cross-origin SVG filter pixel stealing attacks through the browser.