CVE-2022-23591: Stack overflow in Tensorflow

Published Feb 4, 2022
·
Updated

Impact The GraphDef format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a GraphDef containing a fragment such as the following can be consumed when loading a SavedModel:

library { function { signature { name: "SomeOp" description: "Self recursive op" } nodedef { name: "1" op: "SomeOp" } nodedef { name: "2" op: "SomeOp" } } }

This would result in a stack overflow during execution as resolving each NodeDef means resolving the function itself and its nodes.

Patches We have patched the issue in GitHub commit 448a16182065bd08a202d9057dd8ca541e67996c.

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 GraphDef format in TensorFlow does not allow self recursive functions. The runtime assumes that this invariant is satisfied. However, a GraphDef containing a fragment such as the following can be consumed when loading a SavedModel. This would result in a stack overflow during execution as resolving each NodeDef means resolving the function itself and its nodes. 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.

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·11:30 PM

Frequently Asked Questions

1

What is the severity of CVE-2022-23591?

CVE-2022-23591 is a high severity vulnerability due to its impact on TensorFlow's GraphDef format.

2

How do I fix CVE-2022-23591?

To fix CVE-2022-23591, upgrade to TensorFlow version 2.7.1 or later, or apply the appropriate patch.

3

What platforms are affected by CVE-2022-23591?

CVE-2022-23591 affects multiple versions of TensorFlow packaged for both GPU and CPU.

4

What type of vulnerability is CVE-2022-23591?

CVE-2022-23591 is categorized as a code execution vulnerability due to the improper handling of self-recursive functions.

5

What are the recommended versions to mitigate CVE-2022-23591?

The recommended versions to mitigate CVE-2022-23591 are TensorFlow 2.7.1, 2.6.3, or 2.5.3 depending on your current version.

Contact

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