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Security Advisories: GSA_kwCzR0hTQS1ncTJqLWNyOTYtZ3ZxeM4AAv-2

`MirrorPadGrad` heap out of bounds read

Impact

If MirrorPadGrad is given outsize input paddings, TensorFlow will give a heap OOB error.

import tensorflow as tf
tf.raw_ops.MirrorPadGrad(input=[1],
             paddings=[[0x77f00000,0xa000000]],
             mode = 'REFLECT')

Patches

We have patched the issue in GitHub commit 717ca98d8c3bba348ff62281fdf38dcb5ea1ec92.

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 Vul AI.

Permalink: https://github.com/advisories/GHSA-gq2j-cr96-gvqx
JSON: https://advisories.ecosyste.ms/api/v1/advisories/GSA_kwCzR0hTQS1ncTJqLWNyOTYtZ3ZxeM4AAv-2
Source: GitHub Advisory Database
Origin: Unspecified
Severity: Moderate
Classification: General
Published: almost 2 years ago
Updated: almost 2 years ago


CVSS Score: 4.8
CVSS vector: CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H

Identifiers: GHSA-gq2j-cr96-gvqx, CVE-2022-41895
References: Repository: https://github.com/tensorflow/tensorflow
Blast Radius: 23.4

Affected Packages

pypi:tensorflow-gpu
Dependent packages: 155
Dependent repositories: 11,499
Downloads: 547,144 last month
Affected Version Ranges: >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Fixed in: 2.10.1, 2.9.3, 2.8.4
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, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.9.0, 2.9.1, 2.9.2, 2.10.0
All unaffected versions: 2.8.4, 2.9.3, 2.10.1, 2.11.0, 2.12.0
pypi:tensorflow-cpu
Dependent packages: 88
Dependent repositories: 2,483
Downloads: 959,202 last month
Affected Version Ranges: >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Fixed in: 2.10.1, 2.9.3, 2.8.4
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, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.9.0, 2.9.1, 2.9.2, 2.10.0
All unaffected versions: 2.8.4, 2.9.3, 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, 2.16.2, 2.17.0, 2.17.1, 2.18.0
pypi:tensorflow
Dependent packages: 2,172
Dependent repositories: 73,755
Downloads: 18,843,694 last month
Affected Version Ranges: >= 2.10.0, < 2.10.1, >= 2.9.0, < 2.9.3, < 2.8.4
Fixed in: 2.10.1, 2.9.3, 2.8.4
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, 2.7.2, 2.7.3, 2.7.4, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.9.0, 2.9.1, 2.9.2, 2.10.0
All unaffected versions: 2.8.4, 2.9.3, 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, 2.16.2, 2.17.0, 2.17.1, 2.18.0