CVE-2022-29205

Segfault due to missing support for quantized types 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, there is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault. 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 0.8 points since May 21, 2022

What each source reports

CVE List Score used 5.5

Segfault due to missing support for quantized types in TensorFlow

Record: CVE-2022-29205
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-908, CWE-476
Updated: 2026-11-02

EUVDEUVD-2022-2494 5.5

Record: EUVD-2022-2494
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-54ch-gjq5-4976 5.5

Segfault due to missing support for quantized types

Impact

There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):

import numpy as np
import tensorflow as tf

tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))

In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.

Patches

We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.

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 Hong Jin from Singapore Management University.

Record: GHSA-54ch-gjq5-4976
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-476, CWE-908
Updated: 2026-11-02

NVD 5.5

Record: CVE-2022-29205
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-476, CWE-908
Updated: 2026-11-02

OSV 5.5

Segfault due to missing support for quantized types in TensorFlow

Record: CVE-2022-29205
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-476, CWE-908
Updated: 2026-11-02

OSVGHSA-54ch-gjq5-4976 5.5

Segfault due to missing support for quantized types

Impact

There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):

import numpy as np
import tensorflow as tf

tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))

In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.

Patches

We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.

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 Hong Jin from Singapore Management University.

Record: GHSA-54ch-gjq5-4976
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-476, CWE-908
Updated: 2026-11-02

Show 4 moreShow less

OSVPYSEC-2026-3104 5.5

Segfault due to missing support for quantized types

Impact

There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):

import numpy as np
import tensorflow as tf

tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))

In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.

Patches

We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.

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 Hong Jin from Singapore Management University.

Record: PYSEC-2026-3104
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-2026-3274 5.5

Segfault due to missing support for quantized types

Impact

There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):

import numpy as np
import tensorflow as tf

tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))

In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.

Patches

We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.

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 Hong Jin from Singapore Management University.

Record: PYSEC-2026-3274
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-2026-950 5.5

Segfault due to missing support for quantized types

Impact

There is a potential for segfault / denial of service in TensorFlow by calling tf.compat.v1.* ops which don't yet have support for quantized types (added after migration to TF 2.x):

import numpy as np
import tensorflow as tf

tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))

In these scenarios, since the kernel is missing, a nullptr value is passed to ParseDimensionValue for the py_value argument. Then, this is dereferenced, resulting in segfault.

Patches

We have patched the issue in GitHub commit 237822b59fc504dda2c564787f5d3ad9c4aa62d9.

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 Hong Jin from Singapore Management University.

Record: PYSEC-2026-950
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-2022-29205 No score

Segfault due to missing support for quantized types in TensorFlow

Record: BIT-tensorflow-2022-29205
Updated: 2026-11-02

Affected products

Affected packages

Affected packages
Package	Affected	Fixed
`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
Package	Affected	Fixed
`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` 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
`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

History

History
Recorded	Changed	Sources
Nov 2, 2026	first indexed	CVE List, EUVD, GitHub Advisories, NVD, OSV

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

In short

CVE-2022-29205 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 25th percentile. Fixed in tensorflow 2.6.4.

References

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This page doesn't list everything

Left out here: 60 versions. The JSON record has them.