Heap-based Buffer Overflow Affecting tensorflow package, versions [2.3.0, 2.3.1)
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-TENSORFLOW-1013537
- published 28 Sep 2020
- disclosed 28 Sep 2020
- credit Unknown
Introduced: 28 Sep 2020
CVE-2020-15201 Open this link in a new tabHow to fix?
Upgrade tensorflow to version 2.3.1 or higher.
Overview
tensorflow is a machine learning framework.
Affected versions of this package are vulnerable to Heap-based Buffer Overflow. The RaggedCountSparseOutput implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the splits tensor generate a valid partitioning of the values tensor. Hence, the code is prone to heap buffer overflow.If split_values does not end with a value at least num_values then the while loop condition will trigger a read outside of the bounds of split_values once batch_idx grows too large.