GHSA-36QF-2Q77-7JH9

Vulnerability from github – Published: 2026-06-24 18:32 – Updated: 2026-06-28 09:31
VLAI
Details

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

neigh: let neigh_xmit take skb ownership

neigh_xmit always releases the skb, except when no neighbour table is found. But even the first added user of neigh_xmit (mpls) relied on neigh_xmit to release the skb (or queue it for tx).

sashiko reported: If neigh_xmit() is called with an uninitialized neighbor table (for example, NEIGH_ND_TABLE when IPv6 is disabled), it returns -EAFNOSUPPORT and bypasses its internal out_kfree_skb error path. Because the return value of neigh_xmit() is ignored here, does this leak the SKB?

Assume full ownership and remove the last code path that doesn't xmit or free skb.

Severity
7.5 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
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{
  "affected": [],
  "aliases": [
    "CVE-2026-52981"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-24T17:17:08Z",
    "severity": "HIGH"
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nneigh: let neigh_xmit take skb ownership\n\nneigh_xmit always releases the skb, except when no neighbour table is\nfound. But even the first added user of neigh_xmit (mpls) relied on\nneigh_xmit to release the skb (or queue it for tx).\n\nsashiko reported:\n If neigh_xmit() is called with an uninitialized neighbor table (for\n example, NEIGH_ND_TABLE when IPv6 is disabled), it returns -EAFNOSUPPORT\n and bypasses its internal out_kfree_skb error path.  Because the return\n value of neigh_xmit() is ignored here, does this leak the SKB?\n\nAssume full ownership and remove the last code path that doesn\u0027t\nxmit or free skb.",
  "id": "GHSA-36qf-2q77-7jh9",
  "modified": "2026-06-28T09:31:37Z",
  "published": "2026-06-24T18:32:42Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-52981"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/0084712e0bee204b284510cdb63182fd5a30c2b7"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/4438113be604ee67a7bf4f81da6e1cca41332ce4"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/445e45a2c3a078316a62d2d331a570cf34ef5079"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/63063ba60d2dc334e34f1e3f9271d7f3f6f30307"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8a89054a1ec0767aec25ed2bbac933da6ba3cf5a"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/9247d59ca15bf60a57dca08103f055d8a4340877"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/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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