GHSA-FPMV-M5RR-683W

Vulnerability from github – Published: 2026-07-25 12:31 – Updated: 2026-07-25 12:31
VLAI
Details

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

USB: idmouse: fix use-after-free on disconnect race

mutex_unlock() may access the mutex structure after releasing the lock and therefore cannot be used to manage lifetime of objects directly (unlike spinlocks and refcounts). [1][2]

Use a kref to release the driver data to avoid use-after-free in mutex_unlock() when release() races with disconnect().

[1] a51749ab34d9 ("locking/mutex: Document that mutex_unlock() is non-atomic") [2] 2b9d9e0a9ba0 ("locking/mutex: Clarify that mutex_unlock(), and most other sleeping locks, can still use the lock object after it's unlocked")

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{
  "affected": [],
  "aliases": [
    "CVE-2026-64344"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-07-25T10:17:16Z",
    "severity": null
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nUSB: idmouse: fix use-after-free on disconnect race\n\nmutex_unlock() may access the mutex structure after releasing the lock\nand therefore cannot be used to manage lifetime of objects directly\n(unlike spinlocks and refcounts). [1][2]\n\nUse a kref to release the driver data to avoid use-after-free in\nmutex_unlock() when release() races with disconnect().\n\n[1] a51749ab34d9 (\"locking/mutex: Document that mutex_unlock() is\n                   non-atomic\")\n[2] 2b9d9e0a9ba0 (\"locking/mutex: Clarify that mutex_unlock(), and most\n                   other sleeping locks, can still use the lock object\n                   after it\u0027s unlocked\")",
  "id": "GHSA-fpmv-m5rr-683w",
  "modified": "2026-07-25T12:31:32Z",
  "published": "2026-07-25T12:31:32Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-64344"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/31e75fed8f90cfea9f8285e7ed135b0e452bf872"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/54c2b7356b4aeea467f9fb13b85e9e036bc428cb"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/60fc5ef4ecea3e3d1fe556cecf53ddd13096ef09"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8d53b14ad4ccbff6d306b3a39c812303f4a87d41"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d0f61acb51a8c8f3fd41c303ddb7770cd83e7ed4"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/e88cff5fbaa629f3cab45c8b46f395d62c2eb515"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f62622e947f82a3854a8502d09492ffbdeb252b4"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/ff002c153f9722caece3983cc23dc4d9d4652cb4"
    }
  ],
  "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.

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