GHSA-QCMX-P4H8-4FHQ

Vulnerability from github – Published: 2024-03-04 18:30 – Updated: 2025-02-03 15:31
VLAI
Details

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

hwmon: (lm90) Prevent integer overflow/underflow in hysteresis calculations

Commit b50aa49638c7 ("hwmon: (lm90) Prevent integer underflows of temperature calculations") addressed a number of underflow situations when writing temperature limits. However, it missed one situation, seen when an attempt is made to set the hysteresis value to MAX_LONG and the critical temperature limit is negative.

Use clamp_val() when setting the hysteresis temperature to ensure that the provided value can never overflow or underflow.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2021-47098"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-190"
    ],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2024-03-04T18:15:08Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nhwmon: (lm90) Prevent integer overflow/underflow in hysteresis calculations\n\nCommit b50aa49638c7 (\"hwmon: (lm90) Prevent integer underflows of\ntemperature calculations\") addressed a number of underflow situations\nwhen writing temperature limits. However, it missed one situation, seen\nwhen an attempt is made to set the hysteresis value to MAX_LONG and the\ncritical temperature limit is negative.\n\nUse clamp_val() when setting the hysteresis temperature to ensure that\nthe provided value can never overflow or underflow.",
  "id": "GHSA-qcmx-p4h8-4fhq",
  "modified": "2025-02-03T15:31:59Z",
  "published": "2024-03-04T18:30:39Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-47098"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/55840b9eae5367b5d5b29619dc2fb7e4596dba46"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d105f30bea9104c590a9e5b495cb8a49bdfe405f"
    }
  ],
  "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.

Sightings

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Nomenclature

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