CVE-2023-25801 — TensorFlow is an open source machine learning platform

TensorFlow is an open source machine learning platform. Prior to versions 2.12.0 and 2.11.1, `nn_ops.fractional_avg_pool_v2` and `nn_ops.fractional_max_pool_v2` require the first and fourth elements of their parameter `pooling_ratio` to be equal to 1.0, as pooling on batch and ch

01What is this vulnerability?

TensorFlow is an open source machine learning platform. Prior to versions 2.12.0 and 2.11.1, `nn_ops.fractional_avg_pool_v2` and `nn_ops.fractional_max_pool_v2` require the first and fourth elements of their parameter `pooling_ratio` to be equal to 1.0, as pooling on batch and channel dimensions is not supported. A fix is included in TensorFlow 2.12.0 and 2.11.1.

02Affected products

Vendor	Product	Versions
tensorflow	tensorflow	< 2.11.1

03Active exploitation status

Not currently listed on the CISA Known Exploited Vulnerabilities (KEV) catalog. EPSS is the best forward-looking signal — see the EPSS row above.

04Recommended remediation

• Patch to a fixed version listed in the vendor advisory (see references below).
• Mitigate with WAF rules, network egress filters, or feature flags where the patch is not yet available.
• Hunt historical logs for exploitation indicators — see Detection signatures below.

05Technical details

For the full vendor write-up, exploit chains, and reference implementations, see the references list in section 09.

06Detection signatures

Ask SARA in chat to draft a starting detection for this CVE in your stack of choice.

07Related CVEs

No directly-cited follow-up CVEs in the KB record for this advisory. The references list in section 09 carries the vendor cross-references.

08Timeline

• Published: 2023-03-24T23:08:50.251Z
• Last modified: 2025-02-19T20:44:31.150Z

09References

• github.com — https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f49c-87jh-g47q
• github.com — https://github.com/tensorflow/tensorflow/commit/ee50d1e00f81f62a4517453f721c634b…