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Division by zero in TFLite

Moderate severity GitHub Reviewed Published Aug 11, 2021 in tensorflow/tensorflow • Updated Feb 9, 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

Description

Impact

The implementation of fully connected layers in TFLite is vulnerable to a division by zero error:

const int batch_size = input_size / filter->dims->data[1];

An attacker can craft a model such that filter->dims->data[1] is 0.

Patches

We have patched the issue in GitHub commit 718721986aa137691ee23f03638867151f74935f.

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. Concurrently, it has also been reported by Yakun Zhang of Baidu Security.

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 9, 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-2021-37680

GHSA ID

GHSA-cfpj-3q4c-jhvr

Source code

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