GHSA-4HWC-233G-5MV3

Vulnerability from github – Published: 2026-08-27 06:31 – Updated: 2026-08-27 06:31
VLAI
Details

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

netfilter: flowtable: publish GC-visible tuple last

nf_flow_table_iterate() only treats original-direction tuple nodes as owning entries. Publishing the original node first lets GC observe and free a flow while flow_offload_add() is still inserting the reply node. Publish the reply node first and the original node last so GC never sees a partially installed flow.

KASAN can trigger slab-use-after-free read and write reports in the flowtable/rhashtable path (rht_deferred_worker, jhash, flow_offload_del, flow_offload_lookup, etc.).

Show details on source website

{
  "affected": [],
  "aliases": [
    "CVE-2026-74746"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-08-26T15:16:53Z",
    "severity": "CRITICAL"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nnetfilter: flowtable: publish GC-visible tuple last\n\nnf_flow_table_iterate() only treats original-direction tuple nodes as\nowning entries. Publishing the original node first lets GC observe and\nfree a flow while flow_offload_add() is still inserting the reply node.\nPublish the reply node first and the original node last so GC never\nsees a partially installed flow.\n\nKASAN can trigger slab-use-after-free read and write reports in the\nflowtable/rhashtable path (rht_deferred_worker, jhash, flow_offload_del,\nflow_offload_lookup, etc.).",
  "id": "GHSA-4hwc-233g-5mv3",
  "modified": "2026-08-27T06:31:30Z",
  "published": "2026-08-27T06:31:30Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-74746"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/0a00254585827f1695aa2700114af622ea754cfa"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/2014ac62df9d45bb9a004a043e85df7be09ed780"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/211ee5d998d92a7d548811939c65942d06c146e4"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/972fdf7c4f5c282a239c88fea614b056c33dc025"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/be345dcbddb4643a54252b954af974b16eda8f91"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d16b71231e65cb05daea2b45701fcf09cef041e7"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d37917e7bebe078f3c17e47fd6fc1c9f6e8497b2"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/d9d3050a70efe217e73a0751e55fdae6a7092620"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/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.

Sightings

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Nomenclature

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