GHSA-5R2J-H2G4-5H5V

Vulnerability from github – Published: 2026-09-11 21:31 – Updated: 2026-09-14 15:32
VLAI
Details

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

HID: sensor: custom: Fix field sysfs group cleanup on failure

hid_sensor_custom_add_attributes() creates one sysfs group for each custom sensor field. If sysfs_create_group() fails after some groups have already been created, the function returns the error without removing the previously created groups.

Add a local unwind path to remove the groups that were already created. With enable_sensor exposed only after the field attributes are ready, this path can free sensor_inst->fields without leaving enable_sensor able to access pointers into that array.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-89626"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-11T20:19:48Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nHID: sensor: custom: Fix field sysfs group cleanup on failure\n\nhid_sensor_custom_add_attributes() creates one sysfs group for each\ncustom sensor field. If sysfs_create_group() fails after some groups\nhave already been created, the function returns the error without\nremoving the previously created groups.\n\nAdd a local unwind path to remove the groups that were already created.\nWith enable_sensor exposed only after the field attributes are ready,\nthis path can free sensor_inst-\u003efields without leaving enable_sensor\nable to access pointers into that array.",
  "id": "GHSA-5r2j-h2g4-5h5v",
  "modified": "2026-09-14T15:32:32Z",
  "published": "2026-09-11T21:31:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-89626"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/10b05fafff932e325896d59dde40938954ab4577"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2409779f3096fcef41bcf57b5f4887d0fa0dc8dd"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/3789d0802ddb4b3be04062caf4bfadd23496e9a7"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/416194933af63bd58d03b7605b1ebc1711186838"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/79154fad98ee843e5363940841e2d831503c190a"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d0e15091e88d18e30b67daf85b88f6528bb9bf41"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d96f8958d4469ac02d9c563686cdd968005b944d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f3f37b937a6ea2a00fb5e6189e74f855caa43eb5"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:A/AC:L/PR:N/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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Nomenclature

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