CVE-2021-41202: Overflow/crash in `tf.range`

Published Nov 5, 2021
·
Updated

Impact While calculating the size of the output within the tf.range kernel, there is a conditional statement of type int64 = condition ? int64 : double. Due to C++ implicit conversion rules, both branches of the condition will be cast to double and the result would be truncated before the assignment. This result in overflows:

python import tensorflow as tf

tf.sparse.eye(numrows=9223372036854775807, numcolumns=None) Similarly, tf.range would result in crashes due to overflows if the start or end point are too large.

python import tensorflow as tf

tf.range(start=-1e+38, limit=1)

Patches We have patched the issue in GitHub commits 6d94002a09711d297dbba90390d5482b76113899 (merging #51359) and 1b0e0ec27e7895b9985076eab32445026ae5ca94 (merging #51711).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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.

Attribution This vulnerability has been reported externally via GitHub issue, GitHub issue and GitHub issue.

Other sources

TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the tf.range kernel, there is a conditional statement of type int64 = condition ? int64 : double. Due to C++ implicit conversion rules, both branches of the condition will be cast to double and the result would be truncated before the assignment. This result in overflows. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

MITRE

Affected Software

13 affected componentsFixes available
pip/tensorflow-gpu<2.4.4
2.4.4
pip/tensorflow-gpu>=2.5.0<2.5.2
2.5.2
pip/tensorflow-gpu>=2.6.0<2.6.1
2.6.1
pip/tensorflow-cpu<2.4.4
2.4.4
pip/tensorflow-cpu>=2.5.0<2.5.2
2.5.2
pip/tensorflow-cpu>=2.6.0<2.6.1
2.6.1
pip/tensorflow<2.4.4
2.4.4
pip/tensorflow>=2.5.0<2.5.2
2.5.2
pip/tensorflow>=2.6.0<2.6.1
2.6.1
Google TensorFlow>=2.4.0<2.4.4
Google TensorFlow>=2.6.0<2.6.1
Google TensorFlow=2.7.0-rc0
Google TensorFlow=2.7.0-rc1

Event History

Nov 5, 2021
CVE Published
via MITRE·09:45 PM
Data Sourced
via MITRE·09:45 PM
DescriptionSeverityWeakness
Nov 10, 2021
Advisory Published
via GitHub·07:13 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-41202?

CVE-2021-41202 has a severity rating that indicates a moderate risk of exploitation due to improper size calculations in the tf.range kernel.

2

Which versions of TensorFlow are affected by CVE-2021-41202?

CVE-2021-41202 affects TensorFlow versions from 2.4.0 to 2.4.4, 2.6.0 to 2.6.1, and certain release candidates of 2.7.0.

3

How do I fix CVE-2021-41202?

To fix CVE-2021-41202, upgrade TensorFlow to version 2.4.4, 2.5.2, or 2.6.1 as applicable.

4

What causes the vulnerability in CVE-2021-41202?

The vulnerability in CVE-2021-41202 is caused by C++ implicit conversion rules affecting size calculations in the tf.range kernel.

5

Is CVE-2021-41202 a critical security issue?

CVE-2021-41202 is not classified as critical, but it poses a risk that should be addressed by updating the affected software.

Contact

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