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🛡️ CVE-2023-25801 — tensorflow

🟠 CVSS 8.0 — High ✅ No Known Exploit CWE-415 OSV
8.0
CVSS Score
0 Low4 Medium7 High9 Critical10

Description

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

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

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](https://github.com/tensorflow/tensorflow/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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability was reported by [dmc1778](https://github.com/dmc1778), of [[email protected]](mailto:[email protected]).

How this vulnerability can be exploited

This issue can be reached with local access to the system, attack complexity is low, an attacker needs no privileges on the target. No user interaction is required. The scope is unchanged, so the impact stays within the vulnerable component. Rated impact: confidentiality low, integrity high, availability high.

CVSS metrics in full

The score comes from this vector: CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:H

  • Attack vector: Local — a local account, shell or session on the host is needed.
  • Attack complexity: Low — the attack works reliably, with no preparation.
  • Privileges required: None — an unauthenticated stranger can try it.
  • User interaction: None — nobody has to be tricked into anything.
  • Scope: Unchanged — the damage stays inside the vulnerable component.
  • Confidentiality impact: Low — limited, and the attacker does not choose what is affected.
  • Integrity impact: High — total loss, or loss the attacker controls.
  • Availability impact: High — total loss, or loss the attacker controls.

Weakness class

CVE-2023-25801 is classified as CWE-415: Double Free. The same allocation is released twice, corrupting allocator bookkeeping.

Affected software

CVE-2023-25801 is recorded against 3 packages.

  • tensorflow (fixed in 2.11.1)
  • tensorflow-cpu (fixed in 2.11.1)
  • tensorflow-gpu (fixed in 2.11.1)

Timeline and source

Published on 24 March 2023 and last revised on 13 July 2026. No public exploit is currently recorded for this entry. A vendor advisory or fix has been published. Record sourced from OSV.

References

github.com (Web)
nvd.nist.gov (Advisory)
github.com (Web)
github.com (Package)

Other advisories for this package

tensorflow has other advisories on record. If you are patching this one, these are worth checking on the same host:

Same weakness in other software

These advisories are the same class of weakness (CWE-415: Double Free) in other software:

Details

Severity HIGH
CVSS Score 8.0
CVSS Vector CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:H
CWE CWE-415
Public Exploit ✅ No
Source OSV
Published 2023-03-24
Updated 2026-08-20
Modified 2026-07-13

Affected Packages

Software From version Fixed in
tensorflow — 2.11.1
tensorflow-cpu — 2.11.1
tensorflow-gpu — 2.11.1

Similar Threats

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ⓘ Data Notice: The information presented above has been compiled from publicly available internet sources. Boteraser aggregates this data solely for informational purposes and does not independently classify, evaluate, or endorse any findings about the vulnerabilities listed. The accuracy and completeness of this information is the sole responsibility of the original publishers. Boteraser and its operators accept no liability for any decisions made based on this data.

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