Improper Input Validation Affecting tensorflow-gpu package, versions [2.5.0,2.5.1)[2.4.0,2.4.3)[,2.3.4)


Severity

Recommended
0.0
high
0
10

CVSS assessment made by Snyk's Security Team. Learn more

Threat Intelligence

EPSS
0.04% (15th percentile)

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  • Snyk IDSNYK-PYTHON-TENSORFLOWGPU-1540685
  • published13 Aug 2021
  • disclosed13 Aug 2021
  • creditUnknown

Introduced: 13 Aug 2021

CVE-2021-37663  (opens in a new tab)
CWE-20  (opens in a new tab)

How to fix?

Upgrade tensorflow-gpu to version 2.5.1, 2.4.3, 2.3.4 or higher.

Overview

tensorflow-gpu 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.

References

CVSS Scores

version 3.1