PYSEC-2026-104

Vulnerability from pysec - Published: 2026-04-01 18:16 - Updated: 2026-05-20 09:19
VLAI
Details

Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, there is a symlink traversal vulnerability in external data loading allows reading files outside the model directory. This issue has been patched in version 1.21.0.

Impacted products
Name purl
onnx pkg:pypi/onnx

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "onnx",
        "purl": "pkg:pypi/onnx"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.21.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.1",
        "0.2",
        "0.2.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.1.1",
        "1.1.2",
        "1.10.0",
        "1.10.1",
        "1.10.2",
        "1.11.0",
        "1.12.0",
        "1.13.0",
        "1.13.1",
        "1.14.0",
        "1.14.1",
        "1.15.0",
        "1.16.0",
        "1.16.1",
        "1.16.2",
        "1.17.0",
        "1.18.0",
        "1.19.0",
        "1.19.1",
        "1.19.1rc1",
        "1.2.1",
        "1.2.2",
        "1.2.3",
        "1.20.0",
        "1.20.0rc1",
        "1.20.0rc2",
        "1.20.1",
        "1.20.1rc1",
        "1.21.0rc1",
        "1.21.0rc2",
        "1.21.0rc3",
        "1.21.0rc4",
        "1.3.0",
        "1.4.0",
        "1.4.1",
        "1.5.0",
        "1.6.0",
        "1.7.0",
        "1.8.0",
        "1.8.1",
        "1.9.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-34447",
    "GHSA-p433-9wv8-28xj"
  ],
  "details": "Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, there is a symlink traversal vulnerability in external data loading allows reading files outside the model directory. This issue has been patched in version 1.21.0.",
  "id": "PYSEC-2026-104",
  "modified": "2026-05-20T09:19:09.984613Z",
  "published": "2026-04-01T18:16:30.810Z",
  "references": [
    {
      "type": "EVIDENCE",
      "url": "https://github.com/onnx/onnx/security/advisories/GHSA-p433-9wv8-28xj"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "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

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

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Detection rules are retrieved from Rulezet.

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