GHSA-jc87-6vpp-7ff3

Heap buffer overflow in Tensorflow

Source: GitHub Advisory Database (reviewed) Moderate CVE-2020-15198

Packages

Ecosystem	Package	Affected	Fixed in
PyPI	tensorflow	>= 2.3.0, < 2.3.1	2.3.1
PyPI	tensorflow-cpu	>= 2.3.0, < 2.3.1	2.3.1
PyPI	tensorflow-gpu	>= 2.3.0, < 2.3.1	2.3.1

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact The `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has the same shape as the `values` one. The values in these tensors are always accessed in parallel: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/count_ops.cc#L193-L195 Thus, a shape mismatch can result in accesses outside the bounds of heap allocated buffers. ### Patches We have patched the issue in 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and will release a patch release. We recommend users to upgrade to TensorFlow 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability is a variant of [GHSA-p5f8-gfw5-33w4](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4)

References

External links from the advisory. They lead to third-party sites.