GHSA-f2vv-v9cg-qhh7 Assertion failure based denial of service in Tensorflow

• PyPI tensorflow: < 2.5.3 → fixed in 2.5.3 • PyPI tensorflow: >= 2.6.0, < 2.6.3 → fixed in 2.6.3 • PyPI tensorflow: >= 2.7.0, < 2.7.1 → fixed in 2.7.1 • PyPI tensorflow-cpu: < 2.5.3 → fixed in 2.5.3 • PyPI tensorflow-cpu: >= 2.6.0, < 2.6.3 → fixed in 2.6.3 • PyPI tensorflow-cpu: >= 2.7.0, < 2.7.1 → fixed in 2.7.1 • PyPI tensorflow-gpu: < 2.5.3 → fixed in 2.5.3 • PyPI tensorflow-gpu: >= 2.6.0, < 2.6.3 → fixed in 2.6.3 • PyPI tensorflow-gpu: >= 2.7.0, < 2.7.1 → fixed in 2.7.1

Impact The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail: ```python import tensorflow as tf tf.raw_ops.DenseBincount( input=[[0], [1], [2]], size=[1], weights=[3,2,1], binary_output=False) ``` There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. Patches We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range. For more information Please consult our security guide for more information regarding the security model and how to contact us with issues and questions. Attribution This vulnerability has been reported by Faysal Hossain Shezan from University of Virginia.