GHSA-W62H-8XJM-FV49

Vulnerability from github – Published: 2022-09-16 21:19 – Updated: 2022-09-19 19:38
VLAI?
Summary
TensorFlow vulnerable to `CHECK` fail in `DenseBincount`
Details

Impact

DenseBincount assumes its input tensor weights to either have the same shape as its input tensor input or to be length-0. A different weights shape will trigger a CHECK fail that can be used to trigger a denial of service attack.

import tensorflow as tf
binary_output = True
input = tf.random.uniform(shape=[0, 0], minval=-10000, maxval=10000, dtype=tf.int32, seed=-2460)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.DenseBincount(input=input, size=size, weights=weights, binary_output=binary_output)

Patches

We have patched the issue in GitHub commit bf4c14353c2328636a18bfad1e151052c81d5f43.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Di Jin, Secure Systems Labs, Brown University

Show details on source website

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.7.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.9.0"
            },
            {
              "fixed": "2.9.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2022-35987"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-09-16T21:19:15Z",
    "nvd_published_at": "2022-09-16T22:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\n`DenseBincount` assumes its input tensor `weights` to either have the same shape as its input tensor `input` or to be length-0. A different `weights` shape will trigger a `CHECK` fail that can be used to trigger a denial of service attack.\n```python\nimport tensorflow as tf\nbinary_output = True\ninput = tf.random.uniform(shape=[0, 0], minval=-10000, maxval=10000, dtype=tf.int32, seed=-2460)\nsize = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)\nweights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)\ntf.raw_ops.DenseBincount(input=input, size=size, weights=weights, binary_output=binary_output)\n```\n\n### Patches\nWe have patched the issue in GitHub commit [bf4c14353c2328636a18bfad1e151052c81d5f43](https://github.com/tensorflow/tensorflow/commit/bf4c14353c2328636a18bfad1e151052c81d5f43).\n\nThe fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 Di Jin, Secure Systems Labs, Brown University\n",
  "id": "GHSA-w62h-8xjm-fv49",
  "modified": "2022-09-19T19:38:33Z",
  "published": "2022-09-16T21:19:15Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w62h-8xjm-fv49"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-35987"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/bf4c14353c2328636a18bfad1e151052c81d5f43"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "TensorFlow vulnerable to `CHECK` fail in `DenseBincount`"
}


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