# Google Cloud Alerts Users to Data Leak Risks in AMD Turin CPUs

*Published November 13, 2026*
*Source: [https://thehackernews.com/2026/11/google-cloud-warns-three-amd-turin-cpu.html](https://thehackernews.com/2026/11/google-cloud-warns-three-amd-turin-cpu.html)*

## Executive Summary

Google Cloud has identified three side-channel vulnerabilities in AMD Turin CPUs that could potentially allow data leakage across processes within virtual machines. Users are advised to apply operating system patches and restart their virtual machines to mitigate these risks.

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## Article

Google Cloud has alerted users of its virtual machines running on AMD Turin CPUs to three vulnerabilities that may allow attackers to leak data across processes within virtual machines. These vulnerabilities are classified as side-channel flaws and affect several machine series including C4D, N4D, H4D, Z4D, and G4. Users are advised to apply a guest operating system patch and restart their virtual machines to mitigate the risks. The vulnerabilities, identified as Transient Scheduler Attacks, affect AMD's fifth-generation EPYC processors, known under the code name Turin. While two of these flaws, TSA-SQ and TSA-L1, were previously disclosed for earlier EPYC processors, a new flaw, TSA-Fill, has been identified specifically for these newer processors. Google has already implemented mitigations for attacks between virtual machines and between virtual machines and the host. However, within a virtual machine, these flaws may allow an attacker running code on the same processor core to infer data from other processes or the kernel. The flaws are categorized by AMD as local attacks with high complexity but requiring only low privileges. Currently, no known exploitations have been reported by Google or AMD. Despite the medium severity rating by Google, users are urged to take action to protect their systems. AMD recommends platform firmware and operating system updates for those managing Turin servers on their hardware. Administrators should also consider potential performance impacts when applying these mitigations.