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CVE-2021-37678

Arbitrary code execution due to YAML deserialization

9.3 CriticalPublic exploitFix available

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Attack profile

How easy it is to exploit

Attack vector
Local
Complexity
Low
Privileges needed
None
User interaction
None

What an attacker can affect

Confidentiality
High
Integrity
High
Availability
High

Exploit likelihood

0.45%Down 0.6 points since Aug 13, 2021
90%50%10%1%

What each source reports

CVE List Score used 9.3

Arbitrary code execution due to YAML deserialization

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
CVE-2021-37678
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Weakness
CWE-502
Updated
2026-11-02
EUVDEUVD-2021-0404 9.3

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
EUVD-2021-0404
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Updated
2026-11-03
GitHub AdvisoriesGHSA-r6jx-9g48-2r5r 8.5

Arbitrary code execution due to YAML deserialization

Impact

TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format.

from tensorflow.keras import models

payload = '''
!!python/object/new:type
args: ['z', !!python/tuple [], {'extend': !!python/name:exec }]
listitems: "__import__('os').system('cat /etc/passwd')"
'''
  
models.model_from_yaml(payload)

The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input.

Patches

Given that YAML format support requires a significant amount of work, we have removed it for now.

We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Arjun Shibu.

Record
GHSA-r6jx-9g48-2r5r
CVSS 4.0
8.5 HighCVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Weakness
CWE-502
Updated
2026-11-02
NVD 9.3

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
CVE-2021-37678
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
CVSS 3.1
8.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
CVSS 2.0
4.6 MediumAV:L/AC:L/Au:N/C:P/I:P/A:P
Weakness
CWE-502
Updated
2026-11-02
OSV 8.8

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
CVE-2021-37678
CVSS 3.1
8.8 HighCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:H/A:H
Updated
2026-11-02
OSVGHSA-r6jx-9g48-2r5r 8.5

Arbitrary code execution due to YAML deserialization

Impact

TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format.

from tensorflow.keras import models

payload = '''
!!python/object/new:type
args: ['z', !!python/tuple [], {'extend': !!python/name:exec }]
listitems: "__import__('os').system('cat /etc/passwd')"
'''
  
models.model_from_yaml(payload)

The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input.

Patches

Given that YAML format support requires a significant amount of work, we have removed it for now.

We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Arjun Shibu.

Record
GHSA-r6jx-9g48-2r5r
CVSS 4.0
8.5 HighCVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
CVSS 3.1
9.3 CriticalCVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Weakness
CWE-502
Updated
2026-11-02
Show 6 moreShow less
OSVBIT-tensorflow-2021-37678 No score

Arbitrary code execution due to YAML deserialization

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
BIT-tensorflow-2021-37678
Updated
2026-11-02
OSVopenSUSE-SU-2022:10014-1 No score

Security update for tensorflow2

This update for tensorflow fixes the following issues:

Update to TF2 2.6.0 which fixes multiple CVEs (boo#1189423).

  • Introduction of bazel6.3 and basel-skylib1.0.3 as build dependencies. The latter has been adapted to all a version in its package name (if %set_ver_suffix is set to 1). This allows multiple versions to exist for one product (not installed). NOTE: basel-skylib1.0.3 does not exist in oS:Factory: basel-skylib in oS:Factory - the base version - is 1.0.3.
Record
openSUSE-SU-2022:10014-1
Updated
2026-11-02
OSVopenSUSE-SU-2024:12116-1 No score

tensorflow-lite-2.9.1-1.1 on GA media

These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.

Record
openSUSE-SU-2024:12116-1
Updated
2026-11-02
OSVPYSEC-2021-300 No score

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
PYSEC-2021-300
Updated
2026-11-02
OSVPYSEC-2021-591 No score

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
PYSEC-2021-591
Updated
2026-11-02
OSVPYSEC-2021-789 No score

TensorFlow is an end-to-end open source platform for machine learning. In affected versions TensorFlow and Keras can be tricked to perform arbitrary code execution when deserializing a Keras model from YAML format. The implementation uses yaml.unsafe_load which can perform arbitrary code execution on the input. Given that YAML format support requires a significant amount of work, we have removed it for now. We have patched the issue in GitHub commit 23d6383eb6c14084a8fc3bdf164043b974818012. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Record
PYSEC-2021-789
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.3.4
2.3.4
tensorflow
PyPI
 2.4.0 up to 2.4.3
2.4.3
tensorflow
PyPI
 2.5.0 to 2.5.0
2.5.1
tensorflow-cpu
PyPI
 before 2.3.4
2.3.4
tensorflow-cpu
PyPI
 2.4.0 up to 2.4.3
2.4.3
tensorflow-cpu
PyPI
 2.5.0 to 2.5.0
2.5.1
tensorflow-gpu
PyPI
 before 2.3.4
2.3.4
tensorflow-gpu
PyPI
 2.4.0 up to 2.4.3
2.4.3
tensorflow-gpu
PyPI
 2.5.0 to 2.5.0
2.5.1
tensorflow
Bitnami
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, 2.5.0 up to 2.5.1
2.3.42.4.32.5.1
Show 24 moreShow less
Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 2.3.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 44 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.3
2.3.4
tensorflow
PyPI
 2.4.0 up to 2.4.3, plus listed versions
2.4.12.4.2
2.4.3
tensorflow
PyPI
 2.5.0 up to 2.5.1
2.5.1
tensorflow-cpu
PyPI
 before 2.3.4, plus listed versions
1.15.02.1.02.1.12.1.22.1.3
Show 9 moreShow less
2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.3
2.3.4
tensorflow-cpu
PyPI
 2.4.0 up to 2.4.3, plus listed versions
2.4.12.4.2
2.4.3
tensorflow-cpu
PyPI
 2.5.0 up to 2.5.1
2.5.1
tensorflow-gpu
PyPI
 before 2.3.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 44 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.3
2.3.4
tensorflow-gpu
PyPI
 2.4.0 up to 2.4.3, plus listed versions
2.4.12.4.2
2.4.3
tensorflow-gpu
PyPI
 2.5.0 up to 2.5.1
2.5.1
tensorflow
PyPI
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, plus listed versions
2.3.12.3.22.3.32.4.12.4.2
2.3.42.4.3
tensorflow-cpu
PyPI
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, plus listed versions
2.3.12.3.22.3.32.4.12.4.2
2.3.42.4.3
tensorflow-gpu
PyPI
 2.3.0 up to 2.3.4, 2.4.0 up to 2.4.3, plus listed versions
2.3.12.3.22.3.32.4.12.4.2
2.3.42.4.3
bazel-skylib1.0.3
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 1.0.3-bp153.2.1
1.0.3-bp153.2.1
bazel3.7
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 3.7.2-bp153.4.1
3.7.2-bp153.4.1
tensorflow2
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2-lite
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-hpc
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-openmpi2-hpc
SUSE:Package Hub 15 SP3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
bazel-skylib1.0.3
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 1.0.3-bp153.2.1
1.0.3-bp153.2.1
bazel3.7
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 3.7.2-bp153.4.1
3.7.2-bp153.4.1
tensorflow2
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2-lite
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-hpc
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1
tensorflow2_2_6_0-gnu-openmpi2-hpc
openSUSE:Leap 15.3
From an advisory covering 63 CVEs
 before 2.6.0-bp153.2.3.1
2.6.0-bp153.2.3.1

Public exploits

Links only. Every CVE stores no exploit code.

Public exploits
SourceLinkDate
PoC in GitHubfran-CICS/ExploitTensorflowCVE-2021-376782021-09-09

History

History
RecordedChangedSources
affected, facts
aliasesEUVD
first indexedCVE List, GitHub Advisories, NVD, OSV, PoC in GitHub

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

In short

CVE-2021-37678 is a critical vulnerability (CVSS 9.3) in Google Tensorflow, published August 12, 2021. Public exploit code exists. EPSS puts the chance of exploitation in the next 30 days at 0.45%, the 39th percentile. Fixed in tensorflow 2.3.4.

References

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