GHSA-3J78-PF43-6MVQ

Vulnerability from github – Published: 2026-06-25 09:31 – Updated: 2026-06-25 09:31
VLAI
Details

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

netfilter: nft_exthdr: fix register tracking for F_PRESENT flag

nft_exthdr_init() passes user-controlled priv->len to nft_parse_register_store(), which marks that many bytes in the register bitmap as initialized. However, when NFT_EXTHDR_F_PRESENT is set, the eval paths write only 1 byte (nft_reg_store8) or 4 bytes (*dest = 0 on TCP/DCCP error path). When len > 4, registers beyond the first are never written, retaining uninitialized stack data from nft_regs.

Bail out if userspace requests too much data when F_PRESENT is set.

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{
  "affected": [],
  "aliases": [
    "CVE-2026-53218"
  ],
  "database_specific": {
    "cwe_ids": [],
    "github_reviewed": false,
    "github_reviewed_at": null,
    "nvd_published_at": "2026-06-25T09:16:39Z",
    "severity": null
  },
  "details": "In the Linux kernel, the following vulnerability has been resolved:\n\nnetfilter: nft_exthdr: fix register tracking for F_PRESENT flag\n\nnft_exthdr_init() passes user-controlled priv-\u003elen to\nnft_parse_register_store(), which marks that many bytes in the\nregister bitmap as initialized.  However, when NFT_EXTHDR_F_PRESENT\nis set, the eval paths write only 1 byte (nft_reg_store8) or\n4 bytes (*dest = 0 on TCP/DCCP error path).  When len \u003e 4,\nregisters beyond the first are never written, retaining\nuninitialized stack data from nft_regs.\n\nBail out if userspace requests too much data when F_PRESENT is set.",
  "id": "GHSA-3j78-pf43-6mvq",
  "modified": "2026-06-25T09:31:21Z",
  "published": "2026-06-25T09:31:21Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-53218"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/19748967d59c31d24d21d40b728570788310b237"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/46fc15a044e9938e7ea77786fb37edd2cd74f031"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/67b27434c43b68a97becda98c9f0c8cf6cba2134"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/772cecf198da732faebb5dcfc46d66a505be8495"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/78069a6d8bc86c9e036eb82c2af4a19cc1871a53"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/8738b1b6d0e639ca1fc0f61516afd3557ac4ecc6"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/cd513e43b4b2bd1de39e2367bc4261c699a8652f"
    },
    {
      "type": "WEB",
      "url": "https://git.kernel.org/stable/c/f08fb3d42fd3aad0b7a263da3ac3ebaf0845e265"
    }
  ],
  "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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