GCVE Workshop - 22 September 2026 (14:00-18:00), Luxembourg Before The Vulnopticon Conference - Registration

PYSEC-2026-405

Vulnerability from pysec - Published: 2026-06-29 11:50 - Updated: 2026-07-01 20:22
VLAI
Details

The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server.

Impacted products
Name purl
ludwig pkg:pypi/ludwig

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "ludwig",
        "purl": "pkg:pypi/ludwig"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "last_affected": "0.10.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.1.0",
        "0.1.1",
        "0.1.2",
        "0.10.0",
        "0.10.1",
        "0.10.2",
        "0.10.3",
        "0.10.4",
        "0.2",
        "0.2.1",
        "0.2.2",
        "0.2.2.2",
        "0.2.2.3",
        "0.2.2.4",
        "0.2.2.5",
        "0.2.2.6",
        "0.2.2.7",
        "0.2.2.8",
        "0.3",
        "0.3.1",
        "0.3.2",
        "0.3.3",
        "0.4",
        "0.4.1",
        "0.4rc1",
        "0.5",
        "0.5.1",
        "0.5.2",
        "0.5.3",
        "0.5.4",
        "0.5.5",
        "0.5rc1",
        "0.5rc2",
        "0.6",
        "0.6.1",
        "0.6.2",
        "0.6.3",
        "0.6.4",
        "0.7",
        "0.7.1",
        "0.7.2",
        "0.7.3",
        "0.7.4",
        "0.7.5",
        "0.8",
        "0.8.1",
        "0.8.1.post1",
        "0.8.2",
        "0.8.3",
        "0.8.4",
        "0.8.5",
        "0.8.6",
        "0.9",
        "0.9.1",
        "0.9.2",
        "0.9.3"
      ]
    }
  ],
  "aliases": [
    "CVE-2026-31238",
    "GHSA-xp5q-5q7g-q26r"
  ],
  "details": "The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server.",
  "id": "PYSEC-2026-405",
  "modified": "2026-07-01T20:22:56.823984Z",
  "published": "2026-06-29T11:50:48.925693Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-31238"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/ludwig-ai/ludwig"
    },
    {
      "type": "WEB",
      "url": "https://www.notion.so/CVE-2026-31238-35d1e1393188819ea77ee98ca85a2878"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/ludwig"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-xp5q-5q7g-q26r"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Ludwig framework is vulnerable to insecure deserialization in its model serving component"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.


Loading…

Loading…

Loading…

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.

Loading…

Detection rules are retrieved from Rulezet.

Loading…

Loading…

Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.


Loading…