CVE-2021-41206: Incomplete validation of shapes in multiple TF ops

Published Nov 5, 2021
·
Updated

Impact Several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or CHECK-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible.

We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues.

Patches We have patched the issue in GitHub commits 68422b215e618df5ad375bcdc6d2052e9fd3080a, 4d74d8a00b07441cba090a02e0dd9ed385145bf4, 579261dcd446385831fe4f7457d802a59685121d, da4aad5946be30e5f049920fa076e1f7ef021261, 4dddb2fd0b01cdd196101afbba6518658a2c9e07, and e7f497570abb6b4ae5af4970620cd880e4c0c904.

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 several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or CHECK-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible. We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues. 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.

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·10:05 PM
Data Sourced
via MITRE·10:05 PM
DescriptionSeverityWeakness
Nov 10, 2021
Advisory Published
via GitHub·07:03 PM

Frequently Asked Questions

1

What is the severity of CVE-2021-41206?

CVE-2021-41206 has a high severity due to potential crashes and undefined behavior resulting from missing tensor shape validation.

2

How do I fix CVE-2021-41206?

To fix CVE-2021-41206, update TensorFlow to version 2.4.4 or later, including versions 2.5.2 and 2.6.1.

3

Which TensorFlow versions are affected by CVE-2021-41206?

CVE-2021-41206 affects TensorFlow versions from 2.4.0 to 2.4.4 and from 2.6.0 to 2.6.1, as well as specific release candidates.

4

What types of issues can CVE-2021-41206 cause?

CVE-2021-41206 can lead to segmentation faults, CHECK-fail crashes, and potentially unsafe reads and writes from the heap.

5

Is CVE-2021-41206 specific to TensorFlow GPU or CPU?

CVE-2021-41206 applies to both TensorFlow GPU and TensorFlow CPU as they share the same vulnerable code.

Contact

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