GitHub Advisoryadvisory · PyPI
GHSA-rcf8-g8jv-vg6p TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
HIGH
Official page ↗
- Aliases
- CVE-2023-25669
- Ecosystem
- PyPI
- Packages
- tensorflow, tensorflow-cpu, tensorflow-gpu
- Severity
- High
- CVSS vector
- CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
- Weaknesses
- CWE-697
- Reviewed
- 2023-03-24
Affected packages
• PyPI tensorflow: < 2.11.1 → fixed in 2.11.1
• PyPI tensorflow-cpu: < 2.11.1 → fixed in 2.11.1
• PyPI tensorflow-gpu: < 2.11.1 → fixed in 2.11.1
Description
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.
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 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
Related
Alias · CVE (1)
- CVE-2023-25669 TensorFlow is an open source platform for machine learning. vulnerability
Weakness · CWE (1)
- CWE-697 Incorrect Comparison weakness