GHSA-56RG-F4QQ-GHHV

Vulnerability from github – Published: 2026-08-15 15:30 – Updated: 2026-08-19 18:32
VLAI
Details

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

ALSA: usb-audio: Clamp frame size in implicit-feedback mode

snd_usb_handle_sync_urb() scales received sync packet sizes by the sender's stride and stores the result directly in out_packet->packet_size[i]. If a connected USB device sends an oversized sync packet, this frame count can exceed ep->maxframesize.

The un-clamped frame count then propagates to the playback endpoint queue, potentially driving packet transfers beyond the endpoint's hardware frame limits.

Cap the calculated frame count against ep->maxframesize in snd_usb_handle_sync_urb() to prevent oversized packets from entering the playback queue.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-74497"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-15T13:17:54Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nALSA: usb-audio: Clamp frame size in implicit-feedback mode\n\nsnd_usb_handle_sync_urb() scales received sync packet sizes by the sender\u0027s\nstride and stores the result directly in out_packet-\u003epacket_size[i]. If a\nconnected USB device sends an oversized sync packet, this frame count can\nexceed ep-\u003emaxframesize.\n\nThe un-clamped frame count then propagates to the playback endpoint queue,\npotentially driving packet transfers beyond the endpoint\u0027s hardware frame\nlimits.\n\nCap the calculated frame count against ep-\u003emaxframesize in\nsnd_usb_handle_sync_urb() to prevent oversized packets from entering the\nplayback queue.",
  "id": "GHSA-56rg-f4qq-ghhv",
  "modified": "2026-08-19T18:32:28Z",
  "published": "2026-08-15T15:30:34Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-74497"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/09cf3dbbb4256a43feb91d2f51f274510a9ada47"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2d39fea6d3c19a2f5811d123114d92e3d0115fd1"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2db4535d6af79276a64449201c5be5feffb31c64"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/53f0aa37eb945f3c983f61d12fc35eb33debb8a9"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/56ac3e7c90f6b45969c3fd07a98fad760ffd6901"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8d7a30c50c2e58a6839634ed0acde14466d1dc61"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/be97fea7451d758881b95af78e900dd0d58a382a"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/cfa8d3e0e8b812c4db4d5241f62b6bdbab2bd7be"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/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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