PYSEC-2021-390

Vulnerability from pysec - Published: 2021-11-05 20:15 - Updated: 2021-11-13 06:52
VLAI?
Details

TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an int64_t. If an overflow occurs, MultiplyWithoutOverflow would return a negative result. In the majority of TensorFlow codebase this then results in a CHECK-failure. Newer constructs exist which return a Status instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Impacted products
Name purl
tensorflow pkg:pypi/tensorflow
Aliases
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "a871989d7b6c18cdebf2fb4f0e5c5b62fbc19edf"
            },
            {
              "fixed": "d81b1351da3e8c884ff836b64458d94e4a157c15"
            },
            {
              "fixed": "7c1692bd417eb4f9b33ead749a41166d6080af85"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            },
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            },
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            },
            {
              "introduced": "2.7.0rc0"
            },
            {
              "fixed": "2.7.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.10.0",
        "1.10.1",
        "1.11.0",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.1",
        "1.13.2",
        "1.14.0",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "1.15.4",
        "1.15.5",
        "1.2.0",
        "1.2.1",
        "1.3.0",
        "1.4.0",
        "1.4.1",
        "1.5.0",
        "1.5.1",
        "1.6.0",
        "1.7.0",
        "1.7.1",
        "1.8.0",
        "1.9.0",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.2.0",
        "2.2.0rc0",
        "2.2.0rc1",
        "2.2.0rc2",
        "2.2.0rc3",
        "2.2.0rc4",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.0rc0",
        "2.3.0rc1",
        "2.3.0rc2",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.3.4",
        "2.4.0",
        "2.4.0rc0",
        "2.4.0rc1",
        "2.4.0rc2",
        "2.4.0rc3",
        "2.4.0rc4",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.5.0",
        "2.5.1",
        "2.6.0",
        "2.7.0rc0",
        "2.7.0rc1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41197",
    "GHSA-prcg-wp5q-rv7p"
  ],
  "details": "TensorFlow is an open source platform for machine learning. In affected versions TensorFlow allows tensor to have a large number of dimensions and each dimension can be as large as desired. However, the total number of elements in a tensor must fit within an `int64_t`. If an overflow occurs, `MultiplyWithoutOverflow` would return a negative result. In the majority of TensorFlow codebase this then results in a `CHECK`-failure. Newer constructs exist which return a `Status` instead of crashing the binary. This is similar to CVE-2021-29584. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
  "id": "PYSEC-2021-390",
  "modified": "2021-11-13T06:52:41.833730Z",
  "published": "2021-11-05T20:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-prcg-wp5q-rv7p"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/a871989d7b6c18cdebf2fb4f0e5c5b62fbc19edf"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/d81b1351da3e8c884ff836b64458d94e4a157c15"
    },
    {
      "type": "REPORT",
      "url": "https://github.com/tensorflow/tensorflow/issues/46890"
    },
    {
      "type": "REPORT",
      "url": "https://github.com/tensorflow/tensorflow/issues/51908"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/7c1692bd417eb4f9b33ead749a41166d6080af85"
    }
  ]
}


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  • Confirmed: The vulnerability has been validated from an analyst's perspective.
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