Improper Input Validation Affecting tensorflow-cpu package, versions [2.5.0,2.5.1) [2.4.0,2.4.3) [,2.3.4)
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Test your applications- Snyk ID SNYK-PYTHON-TENSORFLOWCPU-1540687
- published 13 Aug 2021
- disclosed 13 Aug 2021
- credit Unknown
Introduced: 13 Aug 2021
CVE-2021-37663 Open this link in a new tabHow to fix?
Upgrade tensorflow-cpu to version 2.5.1, 2.4.3, 2.3.4 or higher.
Overview
tensorflow-cpu is a machine learning framework.
Affected versions of this package are vulnerable to Improper Input Validation as, due to incomplete validation in tf.raw_ops.QuantizeV2, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The implementation has some validation but does not check that min_range and max_range both have the same non-zero number of elements. If axis is provided (i.e., not -1), then validation should check that it is a value in range for the rank of input tensor and then the lengths of min_range and max_range inputs match the axis dimension of the input tensor.