GHSA-5G46-HMW3-W78X

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

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

ipc/shm: serialize orphan cleanup with shm_nattch updates

shm_destroy_orphaned() walks the shm idr under shm_ids(ns).rwsem, but that does not serialize all fields tested by shm_may_destroy(). In particular, shm_nattch is updated while holding shm_perm.lock, and attach paths can do that without holding the rwsem.

Do not decide that an orphaned segment is unused before taking the object lock. Move the shm_may_destroy() check under shm_perm.lock, matching the other destroy paths, and unlock the segment when it no longer qualifies for removal.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-52930"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-24T08:16:23Z",
    "severity": null
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nipc/shm: serialize orphan cleanup with shm_nattch updates\n\nshm_destroy_orphaned() walks the shm idr under shm_ids(ns).rwsem, but that\ndoes not serialize all fields tested by shm_may_destroy().  In particular,\nshm_nattch is updated while holding shm_perm.lock, and attach paths can do\nthat without holding the rwsem.\n\nDo not decide that an orphaned segment is unused before taking the object\nlock.  Move the shm_may_destroy() check under shm_perm.lock, matching the\nother destroy paths, and unlock the segment when it no longer qualifies\nfor removal.",
  "id": "GHSA-5g46-hmw3-w78x",
  "modified": "2026-06-24T09:30:48Z",
  "published": "2026-06-24T09:30:48Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-52930"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/030bbc857bd51d4b25a90d931d3f8775ef22823a"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1f0d01e35dbb228084d5187212e32c91a30dcbeb"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2e5c6f4fd4001562781e99bbfc7f1f0127187542"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/6560be3f6a5bb84f006f184f0c966747bb58e1a3"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/92cda2593cf2ed25b0e9d78e5e6d8303bba1a064"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/b1e9aef48e4d8a0c1b54fb913077b0824ed7d650"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/b5107b4ce3ad45fcf369ee2058c8910620f4b5a8"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/db752ebfdaf2c7f27cd9690ef48b616af068319c"
    }
  ],
  "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.

Sightings

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Nomenclature

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