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HIGH severity

CVE-2023-25801 tensorflow

HIGHFix: tensorflow/tensorflow@ee50d1e

CVE-2023-25801 is a high-severity (CVSS 8) CWE-415 vulnerability in tensorflow. A fix is available for tensorflow — see the affected versions and patch details below.

TensorFlow has double free in Fractional(Max/Avg)Pool

Also known asBIT-tensorflow-2023-25801GHSA-f49c-87jh-g47qPYSEC-2026-3166PYSEC-2026-3314PYSEC-2026-985
Published
Mar 24, 2023
Updated
Aug 12, 2026
Affected
3 pkgs
Patched
3 / 3
Exploits
None indexed
Exploitation data as of Sep 22, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • A successful exploit gives an attacker total control of the affected component, not partial access.
  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2023-25801.

EPSS Exploitation Probability

via FIRST.org ↗
0.1%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs5th percentile — riskier than 5% of all scored CVEsHighest risk

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

CVE-2023-25801 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 377,636 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

3 pkgs affected
🐍tensorflow🐍tensorflow-cpu🐍tensorflow-gpu

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Impact

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.

import tensorflow as tf
import os
import numpy as np
from tensorflow.python.ops import nn_ops
try:
  arg_0_tensor = tf.random.uniform([3, 30, 50, 3], dtype=tf.float64)
  arg_0 = tf.identity(arg_0_tensor)
  arg_1_0 = 2
  arg_1_1 = 3
  arg_1_2 = 1
  arg_1_3 = 1
  arg_1 = [arg_1_0,arg_1_1,arg_1_2,arg_1_3,]
  arg_2 = True
  arg_3 = True
  seed = 341261001
  out = nn_ops.fractional_avg_pool_v2(arg_0,arg_1,arg_2,arg_3,seed=seed,)
except Exception as e:
  print("Error:"+str(e))

Patches

We have patched the issue in GitHub commit ee50d1e00f81f62a4517453f721c634bbb478307.

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 was reported by dmc1778, of [email protected].

Affected Packages

3 total 3 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPItensorflowall versions2.11.1pip install --upgrade 'tensorflow==2.11.1'
🐍PyPItensorflow-cpuall versions2.11.1pip install --upgrade 'tensorflow-cpu==2.11.1'
🐍PyPItensorflow-gpuall versions2.11.1pip install --upgrade 'tensorflow-gpu==2.11.1'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for tensorflow, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update tensorflow to 2.11.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2023-25801 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like CVE-2023-25801 can be triaged on real exposure rather than presence alone.

Tailored to CVE-2023-25801. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

### Impact `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. ```python import tensorflow as tf import os import numpy as np from tensorflow.python.ops import nn_ops try: arg_0_tensor = tf.random.uniform([3, 30, 50, 3], dtype=tf.float64) arg_0 = tf.identity(arg_0_tensor) arg_1_0 = 2 arg_1_1 = 3 arg_1_2 = 1 arg_1_3 = 1 arg_1 = [arg_1_0,arg_1_1,arg_1_2,arg_1_3,] arg_2 = True arg_3 = True seed = 341261001
O3 Security · Impact-Aware SCA

Is CVE-2023-25801 in your dependencies?

O3 Security finds CVE-2023-25801 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

CVE-2023-25801: tensorflow (High 8) | O3 Security