VYPR
Moderate severityNVD Advisory· Published Aug 12, 2021· Updated Aug 4, 2024

Missing validation in shape inference for `Dequantize` in TensorFlow

CVE-2021-37677

Description

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for tf.raw_ops.Dequantize has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference implementation uses axis to select between two different values for minmax_rank which is then used to retrieve tensor dimensions. However, code assumes that axis can be either -1 or a value greater than -1, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. 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.

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Affected packages

Versions sourced from the GitHub Security Advisory.

PackageAffected versionsPatched versions
tensorflowPyPI
< 2.3.42.3.4
tensorflowPyPI
>= 2.4.0, < 2.4.32.4.3
tensorflowPyPI
>= 2.5.0, < 2.5.12.5.1
tensorflow-cpuPyPI
< 2.3.42.3.4
tensorflow-cpuPyPI
>= 2.4.0, < 2.4.32.4.3
tensorflow-cpuPyPI
>= 2.5.0, < 2.5.12.5.1
tensorflow-gpuPyPI
< 2.3.42.3.4
tensorflow-gpuPyPI
>= 2.4.0, < 2.4.32.4.3
tensorflow-gpuPyPI
>= 2.5.0, < 2.5.12.5.1

Affected products

17

Patches

Vulnerability mechanics

References

7

News mentions

0

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