CVE-2022-35988: `CHECK` fail in `tf.linalg.matrix_rank` in TensorFlow

Published Sep 16, 2022
·
Updated

TensorFlow is an open source platform for machine learning. When tf.linalg.matrixrank receives an empty input a, the GPU kernel gives a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit c55b476aa0e0bd4ee99d0f3ad18d9d706cd1260a. 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. There are no known workarounds for this issue.

Affected Software

7 affected components
Google TensorFlow<2.7.2
Google TensorFlow>=2.8.0<2.8.1
Google TensorFlow>=2.9.0<2.9.1
Google TensorFlow=2.10-rc0
Google TensorFlow=2.10-rc1
Google TensorFlow=2.10-rc2
Google TensorFlow=2.10-rc3

Event History

Sep 16, 2022
CVE Published
via MITRE·09:35 PM
Data Sourced
via MITRE·09:35 PM
DescriptionSeverityWeakness

Frequently Asked Questions

1

What is the severity of CVE-2022-35988?

CVE-2022-35988 has a medium severity level due to its potential to cause a denial of service.

2

How do I fix CVE-2022-35988?

To fix CVE-2022-35988, update TensorFlow to a version beyond 2.10-rc3 or apply the relevant patches as noted in the official GitHub repository.

3

Which versions of TensorFlow are affected by CVE-2022-35988?

CVE-2022-35988 affects TensorFlow versions up to 2.7.2 and those between 2.8.0 and 2.9.1, as well as specific release candidates of 2.10.

4

What is the impact of CVE-2022-35988?

The impact of CVE-2022-35988 includes a potential denial of service due to the GPU kernel failing when an empty input is processed.

5

Is there a workaround for CVE-2022-35988?

There is no official workaround for CVE-2022-35988 other than upgrading to patched versions of TensorFlow.

Contact

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