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CVE-2022-35982

Segfault in `SparseBincount` in TensorFlow

5.9 MediumFix available

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
High
Privileges needed
None
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
High

Exploit likelihood

0.51%Down 0.4 points since Sep 17, 2022
90%50%10%1%

What each source reports

CVE List Score used 5.9

Segfault in `SparseBincount` in TensorFlow

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
CVE-2022-35982
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
EUVDEUVD-2022-6675 5.9

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
EUVD-2022-6675
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
GitHub AdvisoriesGHSA-397c-5g2j-qxpv 5.9

TensorFlow vulnerable to segfault in `SparseBincount`

Impact

If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.

import tensorflow as tf
binary_output = True
indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288)
values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366)
dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)

Patches

We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 by Di Jin, Secure Systems Labs, Brown University

Record
GHSA-397c-5g2j-qxpv
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
NVD 5.9

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
CVE-2022-35982
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
CVSS 3.1
7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
OSV 5.9

Segfault in `SparseBincount` in TensorFlow

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
CVE-2022-35982
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
OSVGHSA-397c-5g2j-qxpv 5.9

TensorFlow vulnerable to segfault in `SparseBincount`

Impact

If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.

import tensorflow as tf
binary_output = True
indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288)
values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366)
dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)

Patches

We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 by Di Jin, Secure Systems Labs, Brown University

Record
GHSA-397c-5g2j-qxpv
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
Show 5 moreShow less
OSVPYSEC-2026-3093 5.9

TensorFlow vulnerable to segfault in `SparseBincount`

Impact

If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.

import tensorflow as tf
binary_output = True
indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288)
values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366)
dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)

Patches

We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 by Di Jin, Secure Systems Labs, Brown University

Record
PYSEC-2026-3093
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVPYSEC-2026-3270 5.9

TensorFlow vulnerable to segfault in `SparseBincount`

Impact

If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.

import tensorflow as tf
binary_output = True
indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288)
values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366)
dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)

Patches

We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 by Di Jin, Secure Systems Labs, Brown University

Record
PYSEC-2026-3270
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVPYSEC-2026-947 5.9

TensorFlow vulnerable to segfault in `SparseBincount`

Impact

If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack.

import tensorflow as tf
binary_output = True
indices = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int64, seed=-1288)
values = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-9366)
dense_shape = tf.random.uniform(shape=[0], minval=-10000, maxval=10000, dtype=tf.int64, seed=-9878)
size = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.int32, seed=-10000)
weights = tf.random.uniform(shape=[], minval=-10000, maxval=10000, dtype=tf.float32, seed=-10000)
tf.raw_ops.SparseBincount(indices=indices, values=values, dense_shape=dense_shape, size=size, weights=weights, binary_output=binary_output)

Patches

We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa.

The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, 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 by Di Jin, Secure Systems Labs, Brown University

Record
PYSEC-2026-947
CVSS 3.1
5.9 MediumCVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVBIT-tensorflow-2022-35982 No score

Segfault in `SparseBincount` in TensorFlow

TensorFlow is an open source platform for machine learning. If SparseBincount is given inputs for indices, values, and dense_shape that do not make a valid sparse tensor, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 40adbe4dd15b582b0210dfbf40c243a62f5119fa. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

Record
BIT-tensorflow-2022-35982
Updated
2026-11-02
OSVopenSUSE-SU-2024:12355-1 No score

tensorflow-lite-2.10.0-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.10.0-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2024:12355-1
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.7.2
2.7.2
tensorflow
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow
PyPI
 2.9.0 up to 2.9.1
2.9.1
tensorflow-cpu
PyPI
 before 2.7.2
2.7.2
tensorflow-cpu
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow-cpu
PyPI
 2.9.0 up to 2.9.1
2.9.1
tensorflow-gpu
PyPI
 before 2.7.2
2.7.2
tensorflow-gpu
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow-gpu
PyPI
 2.9.0 up to 2.9.1
2.9.1
tensorflow
Bitnami
 before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1
2.7.22.8.12.9.1
Show 6 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.7.2, 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
2.7.2
tensorflow-cpu
PyPI
 before 2.7.2, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 27 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.1
2.7.2
tensorflow-gpu
PyPI
 before 2.7.2, 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
2.7.2
tensorflow
PyPI
 before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, 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
2.7.22.8.12.9.1
tensorflow-cpu
PyPI
 before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 27 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.1
2.7.22.8.12.9.1
tensorflow-gpu
PyPI
 before 2.7.2, 2.8.0 up to 2.8.1, 2.9.0 up to 2.9.1, 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
2.7.22.8.12.9.1

History

History
RecordedChangedSources
facts
first indexedCVE List, EUVD, GitHub Advisories, NVD, OSV

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

In short

CVE-2022-35982 is a medium vulnerability (CVSS 5.9) in Google Tensorflow, published September 16, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.51%, the 43rd percentile. Fixed in tensorflow 2.7.2.

References

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