---
id: CVE-2023-25669
aliases:
  - GHSA-rcf8-g8jv-vg6p
  - BIT-tensorflow-2023-25669
  - PYSEC-2026-1964
  - PYSEC-2026-3236
  - PYSEC-2026-3366
title: TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
summary: TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
severity: high
cvss: 7.5
cvssVector: 'CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.11.1
  - tensorflow-cpu < 2.11.1
  - tensorflow-gpu < 2.11.1
patched:
  - tensorflow 2.11.1
  - tensorflow-cpu 2.11.1
  - tensorflow-gpu 2.11.1
published: '2023-03-24'
updated: '2026-09-10'
sourceUpdated: '2026-09-10T03:49:56.991538651Z'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-rcf8-g8jv-vg6p'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rcf8-g8jv-vg6p
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2023-25669'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d
  - url: 'https://github.com/tensorflow/tensorflow'
tags:
  - osv
  - pip
epss: 0.00394
epssPercentile: 0.30772
ingestedAt: '2026-07-08T18:25:52.691Z'
---

## Overview

### 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

- `tensorflow < 2.11.1`
- `tensorflow-cpu < 2.11.1`
- `tensorflow-gpu < 2.11.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.11.1`
- `tensorflow-cpu 2.11.1`
- `tensorflow-gpu 2.11.1`