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GHSA-43q8-3fv7-pr5x

Improper Validation of Integrity Check Value in TensorFlow

7.0 HighFix available

Impact

The implementation of tf.sparse.split does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read:

import tensorflow as tf
data = tf.random.uniform([1, 32, 32], dtype=tf.float32)
axis = [1, 2]
x = tf.sparse.from_dense(data)
result = tf.sparse.split(x,3, axis=axis)

The code assumes axis is a scalar. This is another instance of TFSA-2021-190 (CVE-2021-41206).

Patches

We have patched the issue in GitHub commit 61bf91e768173b001d56923600b40d9a95a04ad5 (merging #53695).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

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 has been reported externally via a GitHub issue.

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
High
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
High
Integrity
High
Availability
High

What each source reports

GitHub Advisories Score used7.0

Improper Validation of Integrity Check Value in TensorFlow

Impact

The implementation of tf.sparse.split does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read:

import tensorflow as tf
data = tf.random.uniform([1, 32, 32], dtype=tf.float32)
axis = [1, 2]
x = tf.sparse.from_dense(data)
result = tf.sparse.split(x,3, axis=axis)

The code assumes axis is a scalar. This is another instance of TFSA-2021-190 (CVE-2021-41206).

Patches

We have patched the issue in GitHub commit 61bf91e768173b001d56923600b40d9a95a04ad5 (merging #53695).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

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 has been reported externally via a GitHub issue.

Record
GHSA-43q8-3fv7-pr5x
CVSS 3.1
7.0 HighCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
Weakness
CWE-354
Updated
2026-11-02
OSV7.0

Improper Validation of Integrity Check Value in TensorFlow

Impact

The implementation of tf.sparse.split does not fully validate the input arguments. Hence, a malicious user can trigger a denial of service via a segfault or a heap OOB read:

import tensorflow as tf
data = tf.random.uniform([1, 32, 32], dtype=tf.float32)
axis = [1, 2]
x = tf.sparse.from_dense(data)
result = tf.sparse.split(x,3, axis=axis)

The code assumes axis is a scalar. This is another instance of TFSA-2021-190 (CVE-2021-41206).

Patches

We have patched the issue in GitHub commit 61bf91e768173b001d56923600b40d9a95a04ad5 (merging #53695).

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

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 has been reported externally via a GitHub issue.

Record
GHSA-43q8-3fv7-pr5x
CVSS 3.1
7.0 HighCVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
Weakness
CWE-354
Updated
2026-11-02

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
before 2.5.3
2.5.3
tensorflow
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow-cpu
PyPI
before 2.5.3
2.5.3
tensorflow-cpu
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow-cpu
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow-gpu
PyPI
before 2.5.3
2.5.3
tensorflow-gpu
PyPI
2.6.0 up to 2.6.3
2.6.3
tensorflow-gpu
PyPI
2.7.0 to 2.7.0
2.7.1
tensorflow
PyPI
before 2.5.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.3
Show 8 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-cpu
PyPI
before 2.5.3, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 18 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.2
2.5.3
tensorflow-cpu
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow-cpu
PyPI
2.7.0 up to 2.7.1
2.7.1
tensorflow-gpu
PyPI
before 2.5.3, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 45 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4
2.5.3
tensorflow-gpu
PyPI
2.6.0 up to 2.6.3, plus listed versions
2.6.12.6.2
2.6.3
tensorflow-gpu
PyPI
2.7.0 up to 2.7.1
2.7.1

History

History
RecordedChangedSources
first indexedGitHub Advisories, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

GHSA-43q8-3fv7-pr5x is a high vulnerability (CVSS 7.0) in tensorflow, published February 9, 2022. No source lists public exploit code. Fixed in tensorflow 2.5.3.

References

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Left out here: 16 versions. The JSON record has them.

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