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Fencer Vulns
medium 6.5

CVE-2023-25661 json

Denial of Service in TensorFlow

published 2023-03-27 3 y ago modified 2026-09-08 2 mo ago also BIT-tensorflow-2023-25661 , EUVD-2023-1006 , GHSA-fxgc-95xx-grvq , PYSEC-2026-1952 , PYSEC-2026-3182

cvss
6.5
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 38%
public exploits
0
none known

Summary

TensorFlow is an Open Source Machine Learning Framework. In versions prior to 2.11.1 a malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. A proof of concept can be constructed with the `Convolution3DTranspose` function. This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services. An attacker must have privilege to provide input to a `Convolution3DTranspose` call. This issue has been patched and users are advised to upgrade to version 2.11.1. There are no known workarounds for this vulnerability.

Patch / fix

  • pypi tensorflow 2.11.1
  • pypi tensorflow-cpu 2.11.1
  • bitnami tensorflow 2.11.1
  • google tensorflow 2.11.1
  • tensorflow CBL-Mariner 2.0 2.11.1-1

azure linux advisories AZL-31197

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
Proof of concept is public
Automatable
no
Technical impact
partial
Assessed
20 mo ago

Exploit prediction

0.44% chance of exploitation in the next 30 days, higher than 38% of all scored CVEs (FIRST EPSS, 2026-11-08).

Exploits and checks

  • github.com https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq referenced PoC, tagged "exploit" by a source, unverified

CVSS scores

assigned by version score vector
CNA 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
GitHub 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
NVD 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
OSV 3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:L/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
bitnami tensorflow
<2.11.1
2.11.1

Affected products

  • tensorflow tensorflow

Classification

Weakness
  • CWE-20 Improper Input Validation

References

Sources

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.