GHSA-XFRX-G64H-2X84

Vulnerability from github – Published: 2026-08-10 15:33 – Updated: 2026-08-19 18:32
VLAI
Details

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

USB: serial: io_edgeport: cap received transmit credits

The interrupt-status packet reports transmit credits returned by the device. edge_interrupt_callback() adds the 16-bit value to txCredits without checking maxTxCredits.

edge_write() uses txCredits minus the software FIFO count as the amount of data that fits. Since the FIFO is allocated with maxTxCredits bytes, txCredits exceeding maxTxCredits can cause OOB write in ring buffer.

Cap accumulated credits at maxTxCredits. Conforming devices should never hit the cap.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-68365"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-10T13:20:29Z",
    "severity": null
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nUSB: serial: io_edgeport: cap received transmit credits\n\nThe interrupt-status packet reports transmit credits returned by the\ndevice. edge_interrupt_callback() adds the 16-bit value to txCredits\nwithout checking maxTxCredits.\n\nedge_write() uses txCredits minus the software FIFO count as the amount\nof data that fits. Since the FIFO is allocated with maxTxCredits bytes,\ntxCredits exceeding maxTxCredits can cause OOB write in ring buffer.\n\nCap accumulated credits at maxTxCredits. Conforming devices should never\nhit the cap.",
  "id": "GHSA-xfrx-g64h-2x84",
  "modified": "2026-08-19T18:32:17Z",
  "published": "2026-08-10T15:33:48Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-68365"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1e47d8228b8767c8ac722aedb388f70adeeda43d"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/5b39d3da15344b87ef54a0a04f65b52622747e99"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/63c4e55d0741cfaf00515e807cad9293445cd348"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/64b687f9694777754285d489abbefa3784bc78da"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/cbe00048b69d67c8a78293cb7681b4c9963b26c7"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d9dd87bc1d7e8476d29d68883542ec6198d385c6"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/ee57992c053a6d395e98ced2d4c9cc3b42d8c27a"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/faaddd811c5099f11a5f52e68a6b31a5898cda4f"
    }
  ],
  "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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