CVE-2023-25669 json
TensorFlow has Floating Point Exception in AvgPoolGrad with XLA
published 2023-03-24 3 y ago modified 2026-09-10 1 mo ago also BIT-tensorflow-2023-25669 , EUVD-2023-1095 , GHSA-rcf8-g8jv-vg6p , PYSEC-2026-1964 , PYSEC-2026-3236 , PYSEC-2026-3366
- cvss
- 7.5
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.4%
- EPSS 0.4% chance of exploitation in 30 days, percentile 33%
- public exploits
- 0
- none known
Summary
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.
Patch / fix
- pypi tensorflow 2.11.1
- pypi tensorflow-cpu 2.11.1
- pypi tensorflow-gpu 2.11.1
- bitnami tensorflow 2.12.0
- google tensorflow 2.12.0
- tensorflow CBL-Mariner 2.0, Azure Linux 3.0 2.11.1-1
azure linux advisories AZL-31207AZL-35314
Azure Linux vulnerability data, Copyright (c) Microsoft Corporation, from https://github.com/microsoft/AzureLinuxVulnerabilityData via OSV, under the MIT licence; changed: normalised to fixed package versions per release. MIT
CISA SSVC
- Exploitation
- none
- Automatable
- yes
- Technical impact
- partial
- Assessed
- 20 mo ago
Exploit prediction
0.39% chance of exploitation in the next 30 days, higher than 33% of all scored CVEs (FIRST EPSS, 2026-11-08).
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| GitHub | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| NVD | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| OSV | 3.1 | 7.5 | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | tensorflow | <2.11.1 |
2.11.1 |
| pypi | tensorflow-cpu | <2.11.1 |
2.11.1 |
| pypi | tensorflow-gpu | <2.11.1 |
2.11.1 |
| bitnami | tensorflow | <2.12.0 |
2.12.0 |
Affected products
- tensorflow tensorflow
Classification
- Weakness
-
- CWE-697 Incorrect Comparison
References
-
github.com
/tensorflow/tensorflow/commit/1295ae4dbb52fe06b19733b0257e2340d7b63b8d
web, patch
-
github.com
/tensorflow/tensorflow/security/advisories/GHSA-rcf8-g8jv-vg6p
web, patch, vendor-advisory, advisory
-
nvd.nist.gov
/vuln/detail/CVE-2023-25669
advisory, web
-
github.com
/tensorflow/tensorflow
package
-
pypi.org
/project/tensorflow-gpu
package
-
github.com
/advisories/GHSA-rcf8-g8jv-vg6p
advisory
-
pypi.org
/project/tensorflow
package
-
pypi.org
/project/tensorflow-cpu
package
Sources
- CVE List CVE-2023-25669
- GitHub Advisory GHSA-rcf8-g8jv-vg6p
- NVD CVE-2023-25669
- OSV BIT-tensorflow-2023-25669
- OSV PYSEC-2026-1964
- OSV PYSEC-2026-3236
- OSV PYSEC-2026-3366
Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.