Out-of-Bounds Affecting tensorflow package, versions [2.5.0,2.5.1) [2.4.0,2.4.3) [,2.3.4)
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Test your applications- Snyk ID SNYK-PYTHON-TENSORFLOW-1540839
- published 13 Aug 2021
- disclosed 13 Aug 2021
- credit Unknown
Introduced: 13 Aug 2021
CVE-2021-37639 Open this link in a new tabHow to fix?
Upgrade tensorflow to version 2.5.1, 2.4.3, 2.3.4 or higher.
Overview
tensorflow is a machine learning framework.
Affected versions of this package are vulnerable to Out-of-Bounds. When restoring tensors via raw APIs, if the tensor name is not provided, TensorFlow can be tricked into dereferencing a null pointer. Alternatively, attackers can read memory outside the bounds of heap allocated data by providing some tensor names but not enough for a successful restoration. The implementation retrieves the tensor list corresponding to the tensor_name user controlled input and immediately retrieves the tensor at the restoration index (controlled via preferred_shard argument). This occurs without validating that the provided list has enough values. If the list is empty this results in dereferencing a null pointer (undefined behavior). If, however, the list has some elements, if the restoration index is outside the bounds this results in heap OOB read.