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Division by zero in TFLite's implementation of `EmbeddingLookup`

Low severity GitHub Reviewed Published May 13, 2021 in tensorflow/tensorflow • Updated Feb 1, 2023

Package

pip tensorflow (pip)

Affected versions

< 2.1.4
>= 2.2.0, < 2.2.3
>= 2.3.0, < 2.3.3
>= 2.4.0, < 2.4.2

Patched versions

2.1.4
2.2.3
2.3.3
2.4.2

Description

The implementation of the EmbeddingLookup TFLite operator is vulnerable to a division by zero error:

const int row_size = SizeOfDimension(value, 0);
const int row_bytes = value->bytes / row_size;

An attacker can craft a model such that the first dimension of the value input is 0.

Patches

We have patched the issue in GitHub commit f61c57bd425878be108ec787f4d96390579fb83e.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 May 13, 2021
Published by the National Vulnerability Database May 14, 2021
Reviewed May 17, 2021
Published to the GitHub Advisory Database May 21, 2021
Last updated Feb 1, 2023

Severity

Low
2.5
/ 10

CVSS base metrics

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

Weaknesses

CVE ID

CVE-2021-29596

GHSA ID

GHSA-4vrf-ff7v-hpgr

Source code

No known source code
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