GHSA-3PRQ-7CQF-R4WW

Vulnerability from github – Published: 2026-07-24 18:31 – Updated: 2026-07-27 06:30
VLAI
Details

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

wifi: iwlwifi: mld: validate sta_mask before ffs() in BA session handlers

Three BA session handlers use ffs(ba_data->sta_mask) - 1 to derive a station ID without checking that sta_mask is non-zero. When sta_mask is zero, ffs() returns 0 and the subtraction wraps to 0xFFFFFFFF, causing an out-of-bounds access on fw_id_to_link_sta[].

Add WARN_ON_ONCE(!ba_data->sta_mask) guards before each ffs() call, consistent with the existing check in iwl_mld_ampdu_rx_start().

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-64255"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-07-24T16:16:55Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nwifi: iwlwifi: mld: validate sta_mask before ffs() in BA session handlers\n\nThree BA session handlers use ffs(ba_data-\u003esta_mask) - 1 to derive a\nstation ID without checking that sta_mask is non-zero. When sta_mask is\nzero, ffs() returns 0 and the subtraction wraps to 0xFFFFFFFF, causing\nan out-of-bounds access on fw_id_to_link_sta[].\n\nAdd WARN_ON_ONCE(!ba_data-\u003esta_mask) guards before each ffs() call,\nconsistent with the existing check in iwl_mld_ampdu_rx_start().",
  "id": "GHSA-3prq-7cqf-r4ww",
  "modified": "2026-07-27T06:30:31Z",
  "published": "2026-07-24T18:31:29Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-64255"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1de92789ce31e46fa7e7d8e89c90b19cdb1c103b"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f056fc2b927448d37eca6b6cacc3d1b0f67b20d2"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/fe7f339f63c9dc4ca546ed7ac38ba4bb3a99dcfc"
    }
  ],
  "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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