GHSA-RFXQ-R256-5MJ8

Vulnerability from github – Published: 2026-09-24 18:31 – Updated: 2026-09-25 06:30
VLAI
Details

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

RDMA/umem: Be careful about boundary conditions in ib_umem_find_best_pgsz()

Several corner cases, especially important on 32 bits:

  • umem->iova is u64, the function argument should pass in u64 or iova will be truncated
  • Check that the length is not too large for the iova
  • Check that lengths > 4G don't overflow the GENMASK
Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-97421"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-24T17:17:19Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nRDMA/umem: Be careful about boundary conditions in ib_umem_find_best_pgsz()\n\nSeveral corner cases, especially important on 32 bits:\n\n- umem-\u003eiova is u64, the function argument should pass in u64 or\n  iova will be truncated\n- Check that the length is not too large for the iova\n- Check that lengths \u003e 4G don\u0027t overflow the GENMASK",
  "id": "GHSA-rfxq-r256-5mj8",
  "modified": "2026-09-25T06:30:31Z",
  "published": "2026-09-24T18:31:32Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-97421"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/09ea6837a0434fb4db99528a5055b6d822135dcf"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/5fc5b73109540809b094710fac44da81dd8a3ff8"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/ae3cf7d2c4d506c5c91746321644e1a08d989e2a"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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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