{
  "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-2020-15190",
    "sourceURL": "https://www.cve.org/CVERecord?id=CVE-2020-15190",
    "idYear": 2020,
    "status": "PUBLISHED",
    "publishedAt": "2020-09-25T18:35:13.000Z",
    "updatedAt": "2024-08-04T13:08:22.683Z",
    "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": "Segfault in Tensorflow",
      "summary": "In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `tf.raw_ops.Switch` operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is `nullptr`, hence we are binding a reference to `nullptr`. This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, 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"
            }
          ]
        }
      ]
    }
  }
}