GHSA-P9H2-4FGM-97Q7

Vulnerability from github – Published: 2026-09-17 18:32 – Updated: 2026-09-18 18:31
VLAI
Details

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

RDMA/erdma: Hold CQ references when processing EQ events

EQ handlers look up CQs from dev->cq_xa and invoke CQ completion or error callbacks outside the xarray lock. erdma_destroy_cq() can erase the CQ from the xarray and free its queue buffer and doorbell record while a previously scheduled EQ handler is still using the CQ.

Add a CQ refcount and take a reference under the xarray lock with refcount_inc_not_zero(). Remove the CQ from the xarray before dropping the destroy-path reference, then wait for in-flight EQ users before releasing CQ resources.

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-90309"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-09-17T17:17:28Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nRDMA/erdma: Hold CQ references when processing EQ events\n\nEQ handlers look up CQs from dev-\u003ecq_xa and invoke CQ completion or\nerror callbacks outside the xarray lock. erdma_destroy_cq() can erase the\nCQ from the xarray and free its queue buffer and doorbell record while a\npreviously scheduled EQ handler is still using the CQ.\n\nAdd a CQ refcount and take a reference under the xarray lock with\nrefcount_inc_not_zero(). Remove the CQ from the xarray before dropping\nthe destroy-path reference, then wait for in-flight EQ users before\nreleasing CQ resources.",
  "id": "GHSA-p9h2-4fgm-97q7",
  "modified": "2026-09-18T18:31:29Z",
  "published": "2026-09-17T18:32:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-90309"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/05b8ca493dd02319bca93c640b259c2ba51ef321"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/1fc9c1933959d2776a1ce7bf424251b8b5b586cd"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/4545f355654d044d35a31cd01cc46f491a8a7c36"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/610ef81797bb4f709e8675c1d8d093bb9ccdcbd8"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/98df2aee1459ee1c62c70cbe9b370d2a532aea36"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/c0a83f29a24c7e7f8516630848ef6db4c174deed"
    }
  ],
  "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.

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