CVE-2022-23582: `CHECK`-failures in `TensorByteSize` in Tensorflow

Published Feb 4, 2022
·
Updated

Impact A malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures.

cc int64t TensorByteSize(const TensorProto& t) { // numelements returns -1 if shape is not fully defined. int64t numelems = TensorShape(t.tensorshape()).numelements(); return numelems < 0 ? -1 : numelems DataTypeSize(t.dtype()); } TensorShape constructor throws a CHECK-fail if shape is partial or has a number of elements that would overflow the size of an int. The PartialTensorShape constructor instead does not cause a CHECK-abort if the shape is partial, which is exactly what this function needs to be able to return -1.

Patches We have patched the issue in GitHub commit c2426bba00a01de6913738df8fa78e0215fcce02.

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. A malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures. TensorShape constructor throws a CHECK-fail if shape is partial or has a number of elements that would overflow the size of an int. The PartialTensorShape constructor instead does not cause a CHECK-abort if the shape is partial, which is exactly what this function needs to be able to return -1. 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
Data Sourced
via NVD·11:15 PM
RemedyDescriptionSeverityWeaknessAffected Software
Feb 10, 2022
Advisory Published
via GitHub·12:34 AM

Frequently Asked Questions

1

What is the severity of CVE-2022-23582?

CVE-2022-23582 has a severity rating that classifies it as a denial of service vulnerability.

2

How do I fix CVE-2022-23582?

To fix CVE-2022-23582, upgrade to TensorFlow version 2.7.1 or later.

3

Which versions of TensorFlow are affected by CVE-2022-23582?

CVE-2022-23582 affects TensorFlow versions up to 2.5.2 and between 2.6.0 and 2.6.2, as well as version 2.7.0.

4

What type of vulnerability is CVE-2022-23582?

CVE-2022-23582 is classified as a denial of service vulnerability.

5

Can CVE-2022-23582 lead to application crashes?

Yes, CVE-2022-23582 can lead to application crashes due to the associated CHECK failure.

Contact

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