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Security Advisories: GSA_kwCzR0hTQS13eGpqLWNnY3gtcjN2cc4AAu2d

TensorFlow vulnerable to `CHECK` failures in `AvgPool3DGrad`

Impact

The implementation of AvgPool3DGradOp does not fully validate the input orig_input_shape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack:

import tensorflow as tf

ksize = [1, 1, 1, 1, 1]
strides = [1, 1, 1, 1, 1]
padding = "SAME"
data_format = "NDHWC"
orig_input_shape = tf.constant(1879048192, shape=[5], dtype=tf.int32)
grad = tf.constant(1, shape=[1,3,2,4,2], dtype=tf.float32)
tf.raw_ops.AvgPool3DGrad(orig_input_shape=orig_input_shape, grad=grad, ksize=ksize, strides=strides, padding=padding, data_format=data_format)

Patches

We have patched the issue in GitHub commit 9178ac9d6389bdc54638ab913ea0e419234d14eb.

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 Neophytos Christou, Secure Systems Labs, Brown University.

Permalink: https://github.com/advisories/GHSA-wxjj-cgcx-r3vq
JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS13eGpqLWNnY3gtcjN2cc4AAu2d
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: over 1 year ago
Updated: about 1 year ago


CVSS Score: 5.9
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H

Identifiers: GHSA-wxjj-cgcx-r3vq, CVE-2022-35959
References: Repository: https://github.com/tensorflow/tensorflow
Blast Radius: 28.7

Affected Packages

pypi:tensorflow-gpu
Dependent packages: 146
Dependent repositories: 11,499
Downloads: 350,104 last month
Affected Version Ranges: >= 2.9.0, < 2.9.1, >= 2.8.0, < 2.8.1, < 2.7.2
Fixed in: 2.9.1, 2.8.1, 2.7.2
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 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, 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, 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, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.8.0, 2.9.0
All unaffected versions: 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 71
Dependent repositories: 2,483
Downloads: 940,986 last month
Affected Version Ranges: >= 2.9.0, < 2.9.1, >= 2.8.0, < 2.8.1, < 2.7.2
Fixed in: 2.9.1, 2.8.1, 2.7.2
All affected versions: 1.15.0, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.8.0, 2.9.0
All unaffected versions: 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1
pypi:tensorflow
Dependent packages: 1,733
Dependent repositories: 73,755
Downloads: 22,369,513 last month
Affected Version Ranges: >= 2.9.0, < 2.9.1, >= 2.8.0, < 2.8.1, < 2.7.2
Fixed in: 2.9.1, 2.8.1, 2.7.2
All affected versions: 0.12.0, 0.12.1, 1.0.0, 1.0.1, 1.1.0, 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, 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, 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, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0, 2.7.1, 2.8.0, 2.9.0
All unaffected versions: 2.7.2, 2.7.3, 2.7.4, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.1, 2.9.2, 2.9.3, 2.10.0, 2.10.1, 2.11.0, 2.11.1, 2.12.0, 2.12.1, 2.13.0, 2.13.1, 2.14.0, 2.14.1, 2.15.0, 2.15.1, 2.16.1