Leaky Buddies: Cross-Component Covert Channels on Integrated CPU-GPU Systems

Cyberattacks across from the GPU to the CPU or vice versa


Find Technical Paper link here.

“Graphics Processing Units (GPUs) are ubiquitous components used across the range of today’s computing platforms, from phones and tablets, through personal computers, to high-end server class platforms. With the increasing importance of graphics and video workloads, recent processors are shipped with GPU devices that are integrated on the same chip. Integrated GPUs share some resources with the CPU and as a result, there is a potential for microarchitectural attacks from the GPU to the CPU or vice versa. We consider the potential for covert channel attacks that arise either from shared microarchitectural components (such as caches) or through shared contention domains (e.g., shared buses). We illustrate these two types of channels by developing two reliable covert channel attacks. The first covert channel uses the shared LLC cache in Intel’s integrated GPU architectures. The second is a contention based channel targeting the ring bus connecting the CPU and GPU to the LLC. This is the first demonstrated microarchitectural attack crossing the component boundary (GPU to CPU or vice versa). Cross-component channels introduce a number of new challenges that we had to overcome since they occur across heterogeneous components that use different computation models and are interconnected using asymmetric memory hierarchies. We also exploit GPU parallelism to increase the bandwidth of the communication, even without relying on a common clock. The LLC based channel achieves a bandwidth of 120 kbps with a low error rate of 2%, while the contention based channel delivers up to 400 kbps with a 0.8% error rate. We also demonstrate a proof-of-concept prime-and-probe side channel attack that probes the full LLC from the GPU.”

S. B. Dutta, H. Naghibijouybari, N. Abu-Ghazaleh, A. Marquez and K. Barker, “Leaky Buddies: Cross-Component Covert Channels on Integrated CPU-GPU Systems,” 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA), 2021, pp. 972-984, doi: 10.1109/ISCA52012.2021.00080.

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