CVE-2022-23573: Uninitialized variable access in Tensorflow

Published Feb 4, 2022
·
Updated

Impact The implementation of AssignOp can result in copying unitialized data to a new tensor. This later results in undefined behavior.

The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. Patches We have patched the issue in GitHub commit ef1d027be116f25e25bb94a60da491c2cf55bd0b. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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.

Other sources

Tensorflow is an Open Source Machine Learning Framework. The implementation of AssignOp can result in copying uninitialized data to a new tensor. This later results in undefined behavior. The implementation has a check that the left hand side of the assignment is initialized (to minimize number of allocations), but does not check that the right hand side is also initialized. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

NVD

Affected Software

12 affected componentsFixes available
pip/tensorflow-gpu=2.7.0
2.7.1
pip/tensorflow-gpu>=2.6.0<2.6.3
2.6.3
pip/tensorflow-gpu<2.5.3
2.5.3
pip/tensorflow-cpu=2.7.0
2.7.1
pip/tensorflow-cpu>=2.6.0<2.6.3
2.6.3
pip/tensorflow-cpu<2.5.3
2.5.3
pip/tensorflow=2.7.0
2.7.1
pip/tensorflow>=2.6.0<2.6.3
2.6.3
pip/tensorflow<2.5.3
2.5.3
Google TensorFlow<=2.5.2
Google TensorFlow>=2.6.0<=2.6.2
Google TensorFlow=2.7.0

Event History

Feb 4, 2022
CVE Published
via MITRE·10:32 PM
Data Sourced
via MITRE·10:32 PM
DescriptionSeverityWeakness
Feb 9, 2022
Advisory Published
via GitHub·11:26 PM

Frequently Asked Questions

1

What is the severity of CVE-2022-23573?

CVE-2022-23573 has a high severity rating due to the potential for undefined behavior caused by copying uninitialized data.

2

How do I fix CVE-2022-23573?

To fix CVE-2022-23573, upgrade to TensorFlow versions 2.5.3, 2.6.3, or 2.7.1 depending on the installed version.

3

What types of software are affected by CVE-2022-23573?

CVE-2022-23573 affects certain versions of Google TensorFlow, including those up to 2.5.2 and versions between 2.6.0 and 2.6.2, as well as 2.7.0.

4

What are the consequences of CVE-2022-23573?

CVE-2022-23573 can lead to unstable software behavior due to undefined actions from uninitialized data being used.

5

Are there workarounds for CVE-2022-23573?

There are no official workarounds for CVE-2022-23573; the only recommended solution is to upgrade to a patched version.

Contact

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