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arxiv: 1605.06610 · v1 · submitted 2016-05-21 · 💻 cs.CR

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Vulnerable GPU Memory Management: Towards Recovering Raw Data from GPU

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classification 💻 cs.CR
keywords memorydatamanagementadversariesapplicationsattackscommoditydirectly
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In this paper, we present that security threats coming with existing GPU memory management strategy are overlooked, which opens a back door for adversaries to freely break the memory isolation: they enable adversaries without any privilege in a computer to recover the raw memory data left by previous processes directly. More importantly, such attacks can work on not only normal multi-user operating systems, but also cloud computing platforms. To demonstrate the seriousness of such attacks, we recovered original data directly from GPU memory residues left by exited commodity applications, including Google Chrome, Adobe Reader, GIMP, Matlab. The results show that, because of the vulnerable memory management strategy, commodity applications in our experiments are all affected.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. GPUBreach: Privilege Escalation Attacks on GPUs using Rowhammer

    cs.CR 2026-05 unverdicted novelty 8.0

    Unprivileged CUDA kernels can use Rowhammer to tamper with GPU page tables for targeted privilege escalation, leaking cryptographic keys and escalating to CPU root access by bypassing IOMMU.