GHSA-MC77-R35G-CPMM

Vulnerability from github – Published: 2026-08-04 09:31 – Updated: 2026-08-04 09:31
VLAI
Details

In the Linux kernel, the following vulnerability has been resolved:

KVM: nVMX: Hide shadow VMCS right after VMCLEAR

free_nested() frees the shadow VMCS while vmcs01 still points to it. But because it is asynchronous with respect to loaded_vmcs_clear(), the vCPU might migrate before the pointer is cleared and __loaded_vmcs_clear() may then execute VMCLEAR.

The VMCS needs to stay attached until its explicit VMCLEAR completes, but then it can be hidden and the page safely freed.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-64562"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-04T07:16:31Z",
    "severity": null
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nKVM: nVMX: Hide shadow VMCS right after VMCLEAR\n\nfree_nested() frees the shadow VMCS while vmcs01 still points to it. But\nbecause it is asynchronous with respect to loaded_vmcs_clear(), the vCPU\nmight migrate before the pointer is cleared and __loaded_vmcs_clear()\nmay then execute VMCLEAR.\n\nThe VMCS needs to stay attached until its explicit VMCLEAR completes, but\nthen it can be hidden and the page safely freed.",
  "id": "GHSA-mc77-r35g-cpmm",
  "modified": "2026-08-04T09:31:35Z",
  "published": "2026-08-04T09:31:35Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-64562"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1dabef6e206568bf9d9ade74f6e56a48ea35695d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/589419470030a89f16cf19300658b6dc644ca946"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/622ebfac01ba4f9c0060cebd41257fe46fc4a0b3"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8001d2ce9d9bd09118ce523aef595aa094573ae3"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/af56298e9d86e6098cd1d2e155cb2949b7c45412"
    }
  ],
  "schema_version": "1.4.0",
  "severity": []
}



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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

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