NetSight
medium5.9

CVE-2022-36000

TensorFlow vulnerable to null dereference on MLIR on empty function attributes

Impact

### 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](https://github.com/tensorflow/tensorflow/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](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 has been reported by 刘力源, Information System & Security and Countermeasures Experiments Center, Beijing Institute of Technology.

Affected packages

EcosystemPackageAffectedFixed in
piptensorflow< 2.7.22.7.2
piptensorflow-cpu< 2.7.22.7.2
piptensorflow-gpu< 2.7.22.7.2

Affected products

VendorProductAffected versions
GoogleTensorflow
before 2.7.2
from 2.8.0 before 2.8.1
from 2.9.0 before 2.9.1
Version 2.10

Weakness classification

References