Uninitialized memory access in TensorFlow
Moderate severity
GitHub Reviewed
Published
Dec 9, 2020
in
tensorflow/tensorflow
•
Updated Oct 28, 2024
Package
Affected versions
< 1.15.5
>= 2.0.0, < 2.0.4
>= 2.1.0, < 2.1.3
>= 2.2.0, < 2.2.2
>= 2.3.0, < 2.3.2
Patched versions
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2
< 1.15.5
>= 2.0.0, < 2.0.4
>= 2.1.0, < 2.1.3
>= 2.2.0, < 2.2.2
>= 2.3.0, < 2.3.2
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2
< 1.15.5
>= 2.0.0, < 2.0.4
>= 2.1.0, < 2.1.3
>= 2.2.0, < 2.2.2
>= 2.3.0, < 2.3.2
1.15.5
2.0.4
2.1.3
2.2.2
2.3.2
Description
Reviewed
Dec 10, 2020
Published to the GitHub Advisory Database
Dec 10, 2020
Last updated
Oct 28, 2024
Impact
Under certain cases, a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen:
Patches
We have patched the issue in GitHub commit ace0c15a22f7f054abcc1f53eabbcb0a1239a9e2 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.
Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
References