Out-of-Bounds Affecting tensorflow package, versions [,1.15.4) [2.0.0, 2.0.3) [2.1.0, 2.1.2) [2.2.0, 2.2.1) [2.3.0, 2.3.1)
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Test your applications- Snyk ID SNYK-PYTHON-TENSORFLOW-1013548
- published 28 Sep 2020
- disclosed 28 Sep 2020
- credit Aivul Team from Qihoo 360
Introduced: 28 Sep 2020
CVE-2020-15208 Open this link in a new tabHow to fix?
Upgrade tensorflow to version 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or higher.
Overview
tensorflow is a machine learning framework.
Affected versions of this package are vulnerable to Out-of-Bounds. When determining the common dimension size of two tensors, TFLite uses a DCHECK which is no-op outside of debug compilation modes.Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors.