PYSEC-2020-131

Vulnerability from pysec - Published: 2020-09-25 19:15 - Updated: 2020-10-29 16:15
VLAI?
Details

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.

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": "8ee24e7949a203d234489f9da2c5bf45a7d5157d"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "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": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0rc0",
        "0.12.0rc1",
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0rc0",
        "1.1.0rc1",
        "1.1.0rc2",
        "1.1.0",
        "1.2.0rc0",
        "1.2.0rc1",
        "1.2.0rc2",
        "1.2.0",
        "1.2.1",
        "1.3.0rc0",
        "1.3.0rc1",
        "1.3.0rc2",
        "1.3.0",
        "1.4.0rc0",
        "1.4.0rc1",
        "1.4.0",
        "1.4.1",
        "1.5.0rc0",
        "1.5.0rc1",
        "1.5.0",
        "1.5.1",
        "1.6.0rc0",
        "1.6.0rc1",
        "1.6.0",
        "1.7.0rc0",
        "1.7.0rc1",
        "1.7.0",
        "1.7.1",
        "1.8.0rc0",
        "1.8.0rc1",
        "1.8.0",
        "1.9.0rc0",
        "1.9.0rc1",
        "1.9.0rc2",
        "1.9.0",
        "1.10.0rc0",
        "1.10.0rc1",
        "1.10.0",
        "1.10.1",
        "1.11.0rc0",
        "1.11.0rc1",
        "1.11.0rc2",
        "1.11.0",
        "1.12.0rc0",
        "1.12.0rc1",
        "1.12.0rc2",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.0rc0",
        "1.13.0rc1",
        "1.13.0rc2",
        "1.13.1",
        "1.13.2",
        "1.14.0rc0",
        "1.14.0rc1",
        "1.14.0",
        "1.15.0rc0",
        "1.15.0rc1",
        "1.15.0rc2",
        "1.15.0rc3",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.1.0",
        "2.1.1",
        "2.2.0",
        "2.3.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2020-15208",
    "GHSA-mxjj-953w-2c2v"
  ],
  "details": "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.",
  "id": "PYSEC-2020-131",
  "modified": "2020-10-29T16:15:00Z",
  "published": "2020-09-25T19:15:00Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/8ee24e7949a203d234489f9da2c5bf45a7d5157d"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mxjj-953w-2c2v"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
    },
    {
      "type": "WEB",
      "url": "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
    }
  ]
}


Log in or create an account to share your comment.




Tags
Taxonomy of the tags.




Sightings

Author Source Type Date

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



Detection rules are retrieved from Rulezet.