{
  "schemaVersion": 1,
  "attribution": [
    {
      "source": "CISA Known Exploited Vulnerabilities",
      "url": "https://www.cisa.gov/known-exploited-vulnerabilities-catalog",
      "licence": "US government work"
    },
    {
      "source": "GitHub Advisory Database",
      "url": "https://github.com/advisories",
      "licence": "CC BY 4.0"
    },
    {
      "source": "Have I Been Pwned",
      "url": "https://haveibeenpwned.com/",
      "licence": "CC BY 4.0"
    },
    {
      "source": "CVE Program (CVE records)",
      "url": "https://www.cve.org/Legal/TermsOfUse",
      "licence": "CVE Terms of Use",
      "notice": "Copyright © 1999-2026, The MITRE Corporation. CVE is a trademark and the CVE logo is a registered trademark of The MITRE Corporation.",
      "terms": "CVE Usage: MITRE hereby grants you a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare derivative works of, publicly display, publicly perform, sublicense, and distribute Common Vulnerabilities and Exposures (CVE™). Any copy you make for such purposes is authorized provided that you reproduce MITRE's copyright designation and this license in any such copy."
    },
    {
      "source": "FIRST EPSS",
      "url": "https://www.first.org/epss/",
      "licence": "free to use; FIRST requests attribution"
    }
  ],
  "record": {
    "id": "CVE-2026-5817",
    "sourceURL": "https://www.cve.org/CVERecord?id=CVE-2026-5817",
    "idYear": 2026,
    "status": "PUBLISHED",
    "publishedAt": "2026-05-22T19:24:15.662Z",
    "updatedAt": "2026-05-27T03:55:37.087Z",
    "importedAt": "2026-10-24T01:58:20.586Z",
    "snapshot": {
      "id": "cve_2026-10-24_midnight_baseline",
      "at": "2026-10-24T00:00:00.000Z",
      "source": "https://github.com/CVEProject/cvelistV5/releases/tag/cve_2026-10-24_0100Z"
    },
    "facts": {
      "title": "Docker Model Runner container-to-host code execution via unsandboxed trust_remote_code in Python inference backends",
      "summary": "The vllm-metal inference backend in Docker Model Runner on macOS unconditionally sets trust_remote_code=True when loading model tokenizers, and runs without sandboxing. This causes transformers.AutoTokenizer.from_pretrained() to import and execute arbitrary Python files included in any model pulled from an OCI registry, resulting in arbitrary code execution on the Docker host as the Docker Desktop user when inference is triggered.\n\nAny container on the Docker network can trigger this by calling the model-runner.docker.internal API to pull a malicious model and request inference.",
      "affected": [
        {
          "vendor": "Docker",
          "product": "Docker Desktop",
          "platforms": [
            "MacOS"
          ],
          "defaultStatus": "unaffected",
          "versions": [
            {
              "version": "4.62.0",
              "status": "affected",
              "versionType": "semver",
              "lessThan": "4.68.0"
            }
          ]
        }
      ]
    }
  }
}