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-1013616
- published 29 Sep 2020
- disclosed 25 Sep 2020
- credit Unknown
Introduced: 25 Sep 2020
CVE-2020-15200 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. A BatchedMap is equivalent to a vector where each element is a hashmap. However, if the first element of splits_values is not 0, batch_idx will never be 1, hence there will be no hashmap at index 0 in per_batch_counts. Trying to access that in the user code results in a segmentation fault.