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CVE-2022-29194

Missing validation causes denial of service via `DeleteSessionTensor` in TensorFlow

5.5 MediumFix available

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
Low
Privileges needed
Low
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
High

Exploit likelihood

0.33%Down 0.7 points since May 21, 2022
90%50%10%1%

What each source reports

CVE List Score used 5.5

Missing validation causes denial of service via `DeleteSessionTensor` in TensorFlow

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Record
CVE-2022-29194
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
EUVDEUVD-2022-4068 5.5

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Record
EUVD-2022-4068
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
GitHub AdvisoriesGHSA-h5g4-ppwx-48q2 5.5

Missing validation causes denial of service via `DeleteSessionTensor`

Impact

The implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:

import tensorflow as tf

handle = tf.constant("[]", shape=[0], dtype=tf.string)
tf.raw_ops.DeleteSessionTensor(handle=handle)

The code assumes handle is a scalar but there is no validation for this:

    const Tensor& handle = ctx->input(0);
    const string& name = handle.scalar<tstring>()();

Patches

We have patched the issue in GitHub commit cff267650c6a1b266e4b4500f69fbc49cdd773c5.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

Record
GHSA-h5g4-ppwx-48q2
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
NVD 5.5

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Record
CVE-2022-29194
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
CVSS 2.0
2.1 LowAV:L/AC:L/Au:N/C:N/I:N/A:P
Weakness
CWE-20
Updated
2026-11-02
OSV 5.5

Missing validation causes denial of service via `DeleteSessionTensor` in TensorFlow

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Record
CVE-2022-29194
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
OSVGHSA-h5g4-ppwx-48q2 5.5

Missing validation causes denial of service via `DeleteSessionTensor`

Impact

The implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:

import tensorflow as tf

handle = tf.constant("[]", shape=[0], dtype=tf.string)
tf.raw_ops.DeleteSessionTensor(handle=handle)

The code assumes handle is a scalar but there is no validation for this:

    const Tensor& handle = ctx->input(0);
    const string& name = handle.scalar<tstring>()();

Patches

We have patched the issue in GitHub commit cff267650c6a1b266e4b4500f69fbc49cdd773c5.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

Record
GHSA-h5g4-ppwx-48q2
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weakness
CWE-20
Updated
2026-11-02
Show 4 moreShow less
OSVPYSEC-2026-1004 5.5

Missing validation causes denial of service via `DeleteSessionTensor`

Impact

The implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:

import tensorflow as tf

handle = tf.constant("[]", shape=[0], dtype=tf.string)
tf.raw_ops.DeleteSessionTensor(handle=handle)

The code assumes handle is a scalar but there is no validation for this:

    const Tensor& handle = ctx->input(0);
    const string& name = handle.scalar<tstring>()();

Patches

We have patched the issue in GitHub commit cff267650c6a1b266e4b4500f69fbc49cdd773c5.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

Record
PYSEC-2026-1004
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVPYSEC-2026-3197 5.5

Missing validation causes denial of service via `DeleteSessionTensor`

Impact

The implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:

import tensorflow as tf

handle = tf.constant("[]", shape=[0], dtype=tf.string)
tf.raw_ops.DeleteSessionTensor(handle=handle)

The code assumes handle is a scalar but there is no validation for this:

    const Tensor& handle = ctx->input(0);
    const string& name = handle.scalar<tstring>()();

Patches

We have patched the issue in GitHub commit cff267650c6a1b266e4b4500f69fbc49cdd773c5.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

Record
PYSEC-2026-3197
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVPYSEC-2026-3336 5.5

Missing validation causes denial of service via `DeleteSessionTensor`

Impact

The implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack:

import tensorflow as tf

handle = tf.constant("[]", shape=[0], dtype=tf.string)
tf.raw_ops.DeleteSessionTensor(handle=handle)

The code assumes handle is a scalar but there is no validation for this:

    const Tensor& handle = ctx->input(0);
    const string& name = handle.scalar<tstring>()();

Patches

We have patched the issue in GitHub commit cff267650c6a1b266e4b4500f69fbc49cdd773c5.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

Record
PYSEC-2026-3336
CVSS 3.1
5.5 MediumCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Updated
2026-11-02
OSVBIT-tensorflow-2022-29194 No score

Missing validation causes denial of service via `DeleteSessionTensor` in TensorFlow

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of tf.raw_ops.DeleteSessionTensor does not fully validate the input arguments. This results in a CHECK-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Record
BIT-tensorflow-2022-29194
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.6.4
2.6.4
tensorflow
PyPI
 2.7.0 up to 2.7.2
2.7.2
tensorflow
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow-cpu
PyPI
 before 2.6.4
2.6.4
tensorflow-cpu
PyPI
 2.7.0 up to 2.7.2
2.7.2
tensorflow-cpu
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow-gpu
PyPI
 before 2.6.4
2.6.4
tensorflow-gpu
PyPI
 2.7.0 up to 2.7.2
2.7.2
tensorflow-gpu
PyPI
 2.8.0 up to 2.8.1
2.8.1
tensorflow
Bitnami
 before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1
2.6.42.7.22.8.1
Show 9 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.6.4, 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
2.6.4
tensorflow
PyPI
 2.7.0 up to 2.7.2, plus listed versions
2.7.1
2.7.2
tensorflow-cpu
PyPI
 before 2.6.4, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 23 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.3
2.6.4
tensorflow-cpu
PyPI
 2.7.0 up to 2.7.2, plus listed versions
2.7.1
2.7.2
tensorflow-gpu
PyPI
 before 2.6.4, 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
2.6.4
tensorflow-gpu
PyPI
 2.7.0 up to 2.7.2, plus listed versions
2.7.1
2.7.2
tensorflow-gpu
PyPI
 before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1, 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
2.6.42.7.22.8.1
tensorflow
PyPI
 before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1, 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
2.6.42.7.22.8.1
tensorflow-cpu
PyPI
 before 2.6.4, 2.7.0 up to 2.7.2, 2.8.0 up to 2.8.1, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 24 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.7.1
2.6.42.7.22.8.1

History

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

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

In short

CVE-2022-29194 is a medium vulnerability (CVSS 5.5) in Google Tensorflow, published May 20, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.33%, the 26th percentile. Fixed in tensorflow 2.6.4.

References

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