GHSA-4W6C-74PX-57RX

Vulnerability from github – Published: 2025-10-23 12:31 – Updated: 2025-10-23 12:31
VLAI
Details

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

KVM: VMX: Prevent RSB underflow before vmenter

On VMX, there are some balanced returns between the time the guest's SPEC_CTRL value is written, and the vmenter.

Balanced returns (matched by a preceding call) are usually ok, but it's at least theoretically possible an NMI with a deep call stack could empty the RSB before one of the returns.

For maximum paranoia, don't allow any returns (balanced or otherwise) between the SPEC_CTRL write and the vmenter.

[ bp: Fix 32-bit build. ]

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2022-49610"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2025-02-26T07:01:36Z",
    "severity": "MODERATE"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nKVM: VMX: Prevent RSB underflow before vmenter\n\nOn VMX, there are some balanced returns between the time the guest\u0027s\nSPEC_CTRL value is written, and the vmenter.\n\nBalanced returns (matched by a preceding call) are usually ok, but it\u0027s\nat least theoretically possible an NMI with a deep call stack could\nempty the RSB before one of the returns.\n\nFor maximum paranoia, don\u0027t allow *any* returns (balanced or otherwise)\nbetween the SPEC_CTRL write and the vmenter.\n\n  [ bp: Fix 32-bit build. ]",
  "id": "GHSA-4w6c-74px-57rx",
  "modified": "2025-10-23T12:31:15Z",
  "published": "2025-10-23T12:31:15Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-49610"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/07853adc29a058c5fd143c14e5ac528448a72ed9"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/afd743f6dde87296c6f3414706964c491bb85862"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}



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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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