CVE-2023-25669

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

7.5 HighFix available

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.

Attack profile

How easy it is to exploit

Attack vector: Network
Complexity: Low
Privileges needed: None
User interaction: None

What an attacker can affect

Confidentiality: None
Integrity: None
Availability: High

Exploit likelihood

0.39%Up 0.3 points since Mar 25, 2023

What each source reports

CVE List Score used 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Record: CVE-2023-25669
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-697
Updated: 2026-11-02

EUVDEUVD-2023-1095 7.5

Record: EUVD-2023-1095
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

GitHub AdvisoriesGHSA-rcf8-g8jv-vg6p 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Impact

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

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

Record: GHSA-rcf8-g8jv-vg6p
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-697
Updated: 2026-11-02

NVD 7.5

Record: CVE-2023-25669
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-697
Updated: 2026-11-02

OSVAZL-31207 7.5

CVE-2023-25669 affecting package tensorflow for versions less than 2.11.1-1

Record: AZL-31207
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVAZL-35314 7.5

CVE-2023-25669 affecting package tensorflow for versions less than 2.11.1-1

Record: AZL-35314
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

Show 6 moreShow less

OSV 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Record: CVE-2023-25669
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-697
Updated: 2026-11-02

OSVGHSA-rcf8-g8jv-vg6p 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Impact

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

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

Record: GHSA-rcf8-g8jv-vg6p
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-697
Updated: 2026-11-02

OSVPYSEC-2026-1964 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Impact

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

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

Record: PYSEC-2026-1964
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVPYSEC-2026-3236 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Impact

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

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

Record: PYSEC-2026-3236
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVPYSEC-2026-3366 7.5

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Impact

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

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

Record: PYSEC-2026-3366
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVBIT-tensorflow-2023-25669 No score

TensorFlow has Floating Point Exception in AvgPoolGrad with XLA

Record: BIT-tensorflow-2023-25669
Updated: 2026-11-02

Affected products

Affected packages

Affected packages
Package	Affected	Fixed
`tensorflow` PyPI	before 2.11.1	2.11.1
`tensorflow-cpu` PyPI	before 2.11.1	2.11.1
`tensorflow-gpu` PyPI	before 2.11.1	2.11.1
`tensorflow` Azure Linux:2	before 2.11.1-1	2.11.1-1
`tensorflow` Azure Linux:3	before 2.11.1-1	2.11.1-1
`tensorflow` Bitnami	before 2.12.0	2.12.0
`tensorflow` PyPI	before 2.11.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less 1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.10.02.10.0rc02.10.0rc12.10.0rc22.10.0rc32.10.12.11.02.11.0rc02.11.0rc1	2.11.1
`tensorflow-cpu` PyPI	before 2.11.1, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 45 moreShow less 2.1.42.10.02.10.0rc02.10.0rc12.10.0rc22.10.0rc32.10.12.11.02.11.0rc02.11.0rc12.11.0rc22.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.32.8.4	2.11.1
`tensorflow-gpu` PyPI	before 2.11.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less 1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.10.02.10.0rc02.10.0rc12.10.0rc22.10.0rc32.10.12.11.02.11.0rc02.11.0rc1	2.11.1

History

History
Recorded	Changed	Sources
Nov 2, 2026	first indexed	CVE List, EUVD, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2023-25669 is a high vulnerability (CVSS 7.5) in Google Tensorflow, published March 24, 2023. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.39%, the 33rd percentile. Fixed in tensorflow 2.11.1.

References

This page doesn't list everything

Left out here: 102 versions. The JSON record has them.