Vulnerability from bitnami_vulndb
Published
2024-03-06 11:20
Modified
2025-05-20 10:02
Summary
Segmentation fault in tensorflow-lite
Details

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.


{
  "affected": [
    {
      "package": {
        "ecosystem": "Bitnami",
        "name": "tensorflow",
        "purl": "pkg:bitnami/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.15.4"
            },
            {
              "introduced": "2.0.0"
            },
            {
              "fixed": "2.0.3"
            },
            {
              "introduced": "2.1.0"
            },
            {
              "fixed": "2.1.2"
            },
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.1"
            },
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.1"
            }
          ],
          "type": "SEMVER"
        }
      ],
      "severity": [
        {
          "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:H",
          "type": "CVSS_V3"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15210"
  ],
  "database_specific": {
    "cpes": [
      "cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*"
    ],
    "severity": "Medium"
  },
  "details": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, if a TFLite saved model uses the same tensor as both input and output of an operator, then, depending on the operator, we can observe a segmentation fault or just memory corruption. We have patched the issue in d58c96946b and will release patch releases for all versions between 1.15 and 2.3. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.",
  "id": "BIT-tensorflow-2020-15210",
  "modified": "2025-05-20T10:02:07.006Z",
  "published": "2024-03-06T11:20:27.420Z",
  "references": [
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/d58c96946b2880991d63d1dacacb32f0a4dfa453"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-x9j7-x98r-r4w2"
    },
    {
      "type": "WEB",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2020-15210"
    }
  ],
  "schema_version": "1.5.0",
  "summary": "Segmentation fault in tensorflow-lite"
}


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