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Ludwig: Path traversal in dataset archive extraction allows arbitrary file write via symlink members

Type: advisorySources: OSV

Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extract_archive() validated tar member names before calling TarFile.extractall() but did not validate symlink members or hard-link members. A crafted archive could create a link that escaped the extraction directory and then write a later member through that link, placing attacker-controlled content at an arbitrary filesystem path with the extracting process's privileges. The same containment check used os.path.commonprefix, so a sibling path sharing the destination's character prefix could also pass. The dataset-loading path can download and extract configured archive URLs, but exploitation requires a user to process an archive from a source controlled or compromised by the attacker on supported Python 3.12 and 3.13 runtimes. Python 3.14 is not affected because its default tar data filter rejects escaping links. This issue is fixed in version 0.17.8.

Products
Not specified
Affected versions
Not specified
Fixed versions
Not specified
CVEs
CVE-2026-104103
Confirmed fixed CVEs
Not specified
Updated in this feed
3 Nov 2026, 17:22 UTC · Revision 1

Source evidence

Ludwig: Path traversal in dataset archive extraction allows arbitrary file write via symlink members

core-osv · Original source

Published 14 Oct 2026, 18:09 UTC

Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extract_archive() validated tar member names before calling TarFile.extractall() but did not validate symlink members or hard-link members. A crafted archive could create a link that escaped the extraction directory and then write a later member through that link, placing attacker-controlled content at an arbitrary filesystem path with the extracting process's privileges. The same containment check used os.path.commonprefix, so a sibling path sharing the destination's character prefix could also pass. The dataset-loading path can download and extract configured archive URLs, but exploitation requires a user to process an archive from a source controlled or compromised by the attacker on supported Python 3.12 and 3.13 runtimes. Python 3.14 is not affected because its default tar data filter rejects escaping links. This issue is fixed in version 0.17.8.

osv:CVE-2026-104103
Complete source record
{
  "id": "955258fc10814ad0c5a66fb53ffc6060105346447923e3ca52783fd776d8abb9",
  "url": "https://osv.dev/vulnerability/CVE-2026-104103",
  "method": "structured",
  "payload": {
    "kind": "advisory",
    "title": "Ludwig: Path traversal in dataset archive extraction allows arbitrary file write via symlink members",
    "summary": "Ludwig is a low-code framework for building custom LLMs, neural networks, and other AI models. Prior to 0.17.8, ludwig.datasets.archives.extract_archive() validated tar member names before calling TarFile.extractall() but did not validate symlink members or hard-link members. A crafted archive could create a link that escaped the extraction directory and then write a later member through that link, placing attacker-controlled content at an arbitrary filesystem path with the extracting process's privileges. The same containment check used os.path.commonprefix, so a sibling path sharing the destination's character prefix could also pass. The dataset-loading path can download and extract configured archive URLs, but exploitation requires a user to process an archive from a source controlled or compromised by the attacker on supported Python 3.12 and 3.13 runtimes. Python 3.14 is not affected because its default tar data filter rejects escaping links. This issue is fixed in version 0.17.8.",
    "evidence": "osv:CVE-2026-104103",
    "products": [],
    "severity": "high",
    "structured": {
      "id": "CVE-2026-104103",
      "aliases": [
        "CVE-2026-104103",
        "GHSA-qvrm-3x4c-rcxf"
      ],
      "metrics": [
        {
          "type": "CVSS_V3",
          "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:H"
        }
      ],
      "affected": [
        {
          "ranges": [
            {
              "repo": "https://github.com/ludwig-ai/ludwig",
              "type": "GIT",
              "events": [
                {
                  "introduced": "0"
                },
                {
                  "fixed": "de1d65bbf3530fbd33c99abb21d1a1b9c3a64bad"
                },
                {
                  "fixed": "7f534f31e725cc5362c8f6f85537488443de279a"
                }
              ],
              "database_specific": {
                "extracted_events": [
                  {
                    "range": [
                      {
                        "introduced": "0"
                      },
                      {
                        "fixed": "0.17.8"
                      }
                    ],
                    "source": "AFFECTED_FIELD",
                    "strategy": "StringRangeExpression"
                  },
                  {
                    "range": [
                      {
                        "fixed": "7f534f31e725cc5362c8f6f85537488443de279a"
                      }
                    ],
                    "source": "REFERENCES_COMMIT"
                  },
                  {
                    "range": [
                      {
                        "fixed": "de1d65bbf3530fbd33c99abb21d1a1b9c3a64bad"
                      }
                    ],
                    "source": "REFERENCES_TAG",
                    "original_tag": "v0.17.8"
                  }
                ]
              }
            }
          ],
          "versions": [
            "v0.17.7",
            "v0.17.6",
            "v0.17.5",
            "v0.17.4",
            "v0.17.3",
            "v0.17.2",
            "v0.17.1",
            "v0.17.0",
            "v0.16.2",
            "v0.16.1",
            "v0.16.0",
            "v0.15.0",
            "v0.14.1",
            "v0.14.0",
            "v0.13.0",
            "v0.12.0",
            "v0.11.4",
            "v0.11.3",
            "v0.11.2",
            "v0.11.1",
            "v0.11.0",
            "v0.10.0",
            "0.10.0",
            "v0.8",
            "v0.7",
            "v0.7.beta",
            "v0.5.3",
            "v0.5.2",
            "v0.5.1",
            "v0.5",
            "v0.5rc2",
            "v0.5rc1",
            "v0.4",
            "v0.4-rc1",
            "v0.3.3",
            "v0.3.2",
            "v0.3.1",
            "v0.3",
            "v0.2.1",
            "v0.2",
            "v0.1.2",
            "v0.1.1",
            "v0.1.0"
          ],
          "database_specific": {
            "source": "https://storage.googleapis.com/cve-osv-conversion/osv-output/CVE-2026-104103.json"
          }
        }
      ],
      "modified": "2026-10-28T02:30:30.609774866Z",
      "provider": "osv",
      "references": [
        "https://github.com/ludwig-ai/ludwig/releases/tag/v0.17.8",
        "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/104xxx/CVE-2026-104103.json",
        "https://github.com/ludwig-ai/ludwig/security/advisories/GHSA-qvrm-3x4c-rcxf",
        "https://nvd.nist.gov/vuln/detail/CVE-2026-104103",
        "https://github.com/ludwig-ai/ludwig/commit/7f534f31e725cc5362c8f6f85537488443de279a"
      ],
      "provider_metadata": {
        "cwe_ids": [
          "CWE-22",
          "CWE-59"
        ],
        "cna_assigner": "GitHub_M",
        "osv_generated_from": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/104xxx/CVE-2026-104103.json"
      }
    },
    "related_cves": [
      {
        "value": "CVE-2026-104103",
        "evidence": "/id"
      }
    ],
    "security_relevant": true,
    "severity_evidence": "/severity/0/score"
  },
  "source_id": "core-osv",
  "document_id": 497756,
  "published_at": "2026-10-14T18:09:23.015+00:00"
}