CVE-2022-29205: Segfault due to missing support for quantized types in TensorFlow

Published May 20, 2022
·
Updated

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1. ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the pyvalue argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Affected Software

9 affected components
Google TensorFlow<2.6.4
Google TensorFlow>=2.7.0<2.7.2
Google TensorFlow=2.7.0-rc0
Google TensorFlow=2.7.0-rc1
Google TensorFlow=2.8.0
Google TensorFlow=2.8.0-rc0
Google TensorFlow=2.8.0-rc1
Google TensorFlow=2.9.0-rc0
Google TensorFlow=2.9.0-rc1

Event History

May 20, 2022
CVE Published
via MITRE·10:25 PM
Data Sourced
via MITRE·10:25 PM
DescriptionSeverityWeakness

Frequently Asked Questions

1

What is the severity of CVE-2022-29205?

CVE-2022-29205 has a medium severity rating due to its potential for causing segmentation faults and denial of service.

2

How do I fix CVE-2022-29205?

To fix CVE-2022-29205, upgrade TensorFlow to versions 2.9.0 or later, or to 2.8.1, 2.7.2, or 2.6.4.

3

What versions of TensorFlow are affected by CVE-2022-29205?

CVE-2022-29205 affects TensorFlow versions prior to 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

4

What causes CVE-2022-29205 in TensorFlow?

CVE-2022-29205 is caused by the calling of `tf.compat.v1.*` operations that do not support quantized types.

5

Is CVE-2022-29205 remote exploitable?

CVE-2022-29205 is not directly remote exploitable as it requires specifically crafted input to trigger a segmentation fault.

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