NULL Pointer Dereference Affecting tensorflow-cpu package, versions [2.5.0,2.5.1) [2.4.0,2.4.3) [,2.3.4)
Snyk CVSS
Threat Intelligence
Do your applications use this vulnerable package?
In a few clicks we can analyze your entire application and see what components are vulnerable in your application, and suggest you quick fixes.
Test your applications- Snyk ID SNYK-PYTHON-TENSORFLOWCPU-1540834
- published 13 Aug 2021
- disclosed 13 Aug 2021
- credit Unknown
Introduced: 13 Aug 2021
CVE-2021-37647 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 NULL Pointer Dereference. When a user does not supply arguments that determine a valid sparse tensor, tf.raw_ops.SparseTensorSliceDataset implementation can be made to dereference a null pointer. The implementation has some argument validation but fails to consider the case when either indices or values are provided for an empty sparse tensor when the other is not. If indices is empty, then code that performs validation (i.e., checking that the indices are monotonically increasing) results in a null pointer dereference. If indices as provided by the user is empty, then indices in the C++ code above is backed by an empty std::vector, hence calling indices->dim_size(0) results in null pointer dereferencing (same as calling std::vector::at() on an empty vector).