CVE-2021-41203: Missing validation during checkpoint loading

Published Nov 5, 2021
·
Updated

Impact An attacker can trigger undefined behavior, integer overflows, segfaults and CHECK-fail crashes if they can change saved checkpoints from outside of TensorFlow.

This is because the checkpoints loading infrastructure is missing validation for invalid file formats.

Patches We have patched the issue in GitHub commits b619c6f865715ca3b15ef1842b5b95edbaa710ad, e8dc63704c88007ee4713076605c90188d66f3d2, 368af875869a204b4ac552b9ddda59f6a46a56ec, and abcced051cb1bd8fb05046ac3b6023a7ebcc4578.

These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits 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.

Other sources

TensorFlow is an open source platform for machine learning. In affected versions an attacker can trigger undefined behavior, integer overflows, segfaults and CHECK-fail crashes if they can change saved checkpoints from outside of TensorFlow. This is because the checkpoints loading infrastructure is missing validation for invalid file formats. The fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Affected Software

12 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<2.4.4
Google TensorFlow>=2.5.0<2.5.2
Google TensorFlow>=2.6.0<2.6.1

Event History

Nov 5, 2021
CVE Published
via MITRE·09:05 PM
Data Sourced
via MITRE·09:05 PM
DescriptionSeverityWeakness
Nov 10, 2021
Advisory Published
via GitHub·07:12 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-41203?

CVE-2021-41203 is rated as a medium severity vulnerability due to the potential for undefined behavior and crashes.

2

How do I fix CVE-2021-41203?

To mitigate CVE-2021-41203, upgrade TensorFlow to versions 2.4.4, 2.5.2, or 2.6.1.

3

What are the consequences of CVE-2021-41203?

Exploitation of CVE-2021-41203 may lead to application crashes and potential data corruption.

4

Which versions of TensorFlow are affected by CVE-2021-41203?

CVE-2021-41203 affects TensorFlow versions prior to 2.4.4 and those in the ranges of 2.5.0 to 2.5.1 and 2.6.0 to 2.6.0.

5

Can CVE-2021-41203 be exploited remotely?

Yes, CVE-2021-41203 can be exploited if an attacker can manipulate checkpoint files from outside of TensorFlow.

Contact

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