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Division by 0 in inplace operations

Moderate severity GitHub Reviewed Published Aug 11, 2021 in tensorflow/tensorflow • Updated Feb 1, 2023

Package

pip tensorflow (pip)

Affected versions

< 2.3.4
>= 2.4.0, < 2.4.3
= 2.5.0

Patched versions

2.3.4
2.4.3
2.5.1
pip tensorflow-cpu (pip)
< 2.3.4
>= 2.4.0, < 2.4.3
= 2.5.0
2.3.4
2.4.3
2.5.1
pip tensorflow-gpu (pip)
< 2.3.4
>= 2.4.0, < 2.4.3
= 2.5.0
2.3.4
2.4.3
2.5.1

Description

Impact

An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0:

import tensorflow as tf

tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1])

The implementation has a logic error: it should skip processing if x and v are empty but the code uses || instead of &&.

Patches

We have patched the issue in GitHub commit e86605c0a336c088b638da02135ea6f9f6753618.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 by members of the Aivul Team from Qihoo 360.

References

@mihaimaruseac mihaimaruseac published to tensorflow/tensorflow Aug 11, 2021
Published by the National Vulnerability Database Aug 12, 2021
Reviewed Aug 24, 2021
Published to the GitHub Advisory Database Aug 25, 2021
Last updated Feb 1, 2023

Severity

Moderate
5.5
/ 10

CVSS base metrics

Attack vector
Local
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

Weaknesses

CVE ID

CVE-2021-37660

GHSA ID

GHSA-cm5x-837x-jf3c

Source code

No known source code
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