{
  "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-2020-15208",
    "sourceURL": "https://www.cve.org/CVERecord?id=CVE-2020-15208",
    "idYear": 2020,
    "status": "PUBLISHED",
    "publishedAt": "2020-09-25T18:45:40.000Z",
    "updatedAt": "2024-08-04T13:08:22.832Z",
    "importedAt": "2026-10-24T01:56:17.081Z",
    "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": "Data corruption in tensorflow-lite",
      "summary": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
      "affected": [
        {
          "vendor": "tensorflow",
          "product": "tensorflow",
          "versions": [
            {
              "version": "< 1.15.4",
              "status": "affected"
            },
            {
              "version": ">= 2.0.0, < 2.0.3",
              "status": "affected"
            },
            {
              "version": ">= 2.1.0, < 2.1.2",
              "status": "affected"
            },
            {
              "version": ">= 2.2.0, < 2.2.1",
              "status": "affected"
            },
            {
              "version": ">= 2.3.0, < 2.3.1",
              "status": "affected"
            }
          ]
        }
      ]
    }
  }
}