CVE-2023-25669 — TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Affected: tensorflow

TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, if the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give a floating point exception. A fix is included in TensorFlow version 2.12.0 and version 2.11.1.

GHSA-rcf8-g8jv-vg6p — TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact If the stride and window size are not positive for `tf.raw_ops.AvgPoolGrad`, it can give an FPE.

```python import tensorflow as tf import numpy as np

@tf.function(jit_compile=True) def test(): y = tf.raw_ops.AvgPoolGrad(orig_input_shape=[1,0,0,0], grad=[[[[0.39117979]]]], ksize=[1,0,0,0], strides=[1,0,0,0], padding="SAME", data_format="NCHW") return y

print(test()) ```

### Patches We have patched the issue in GitHub commit [1295ae4dbb52fe06b19733b0257e2340d7b63b8d](https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d).

The fix will be included in TensorFlow 2.12. We will also cherrypick this commit on TensorFlow 2.11.1.

### 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 r3pwnx of 360 AIVul Team

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CVE-2023-25669 — TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

GHSA-rcf8-g8jv-vg6p — TensorFlow has Floating Point Exception in AvgPoolGrad with XLA