GCVE Workshop - 22 September 2026 (14:00-18:00), Luxembourg Before The Vulnopticon Conference - Registration

GHSA-5968-J93G-C79F

Vulnerability from github – Published: 2026-06-24 18:32 – Updated: 2026-06-28 09:31
VLAI
Details

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

NFSD: fix nfs4_file access extra count in nfsd4_add_rdaccess_to_wrdeleg

In nfsd4_add_rdaccess_to_wrdeleg, if fp->fi_fds[O_RDONLY] is already set by another thread, __nfs4_file_get_access should not be called to increment the nfs4_file access count since that was already done by the thread that added READ access to the file. The extra fi_access count in nfs4_file can prevent the corresponding nfsd_file from being freed.

When stopping nfs-server service, these extra access counts trigger a BUG in kmem_cache_destroy() that shows nfsd_file object remaining on __kmem_cache_shutdown.

This problem can be reproduced by running the Git project's test suite over NFS.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-53026"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-24T17:17:13Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nNFSD: fix nfs4_file access extra count in nfsd4_add_rdaccess_to_wrdeleg\n\nIn nfsd4_add_rdaccess_to_wrdeleg, if fp-\u003efi_fds[O_RDONLY] is already\nset by another thread, __nfs4_file_get_access should not be called\nto increment the nfs4_file access count since that was already done\nby the thread that added READ access to the file. The extra fi_access\ncount in nfs4_file can prevent the corresponding nfsd_file from being\nfreed.\n\nWhen stopping nfs-server service, these extra access counts trigger a\nBUG in kmem_cache_destroy() that shows nfsd_file object remaining on\n__kmem_cache_shutdown.\n\nThis problem can be reproduced by running the Git project\u0027s test\nsuite over NFS.",
  "id": "GHSA-5968-j93g-c79f",
  "modified": "2026-06-28T09:31:39Z",
  "published": "2026-06-24T18:32:44Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-53026"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/4584229395d0d65bd517780afe97ffea07cb2c3d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/b48f44f36e6607b2f818560f19deb86b4a9c717b"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/b81572b073441dfd32213e41857676d0dbff4665"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ]
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.


Loading…