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CVE-2020-15190

Segfault in Tensorflow

5.3 MediumFix available

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Attack profile

How easy it is to exploit

Attack vector
Network
Complexity
Low
Privileges needed
None
User interaction
None

What an attacker can affect

Confidentiality
None
Integrity
None
Availability
Low

Exploit likelihood

0.94%Down 0.1 points since Apr 14, 2021
90%50%10%1%

What each source reports

CVE List Score used 5.3

Segfault in Tensorflow

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
CVE-2020-15190
CVSS 3.1
5.3 MediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-20, CWE-476
Updated
2026-11-02
EUVDEUVD-2020-0186 5.3

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
EUVD-2020-0186
CVSS 3.1
5.3 MediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Updated
2026-11-03
GitHub AdvisoriesGHSA-4g9f-63rx-5cw4 5.3

Segfault in Tensorflow

Impact

The tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor.

However, the eager runtime traverses all tensors in the output: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/common_runtime/eager/kernel_and_device.cc#L308-L313

Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault

Patches

We have patched the issue in da8558533d925694483d2c136a9220d6d49d843c and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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 members of the Aivul Team from Qihoo 360.

Record
GHSA-4g9f-63rx-5cw4
CVSS 4.0
5.3 MediumCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
5.3 MediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-20, CWE-476
Updated
2026-11-02
NVD 5.3

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
CVE-2020-15190
CVSS 3.1
5.3 MediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
CVSS 2.0
5.0 MediumAV:N/AC:L/Au:N/C:N/I:N/A:P
Weakness
CWE-20, CWE-476
Updated
2026-11-02
OSV 5.3

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
CVE-2020-15190
CVSS 3.1
5.3 MediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Updated
2026-11-02
OSVGHSA-4g9f-63rx-5cw4 5.3

Segfault in Tensorflow

Impact

The tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor.

However, the eager runtime traverses all tensors in the output: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/common_runtime/eager/kernel_and_device.cc#L308-L313

Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault

Patches

We have patched the issue in da8558533d925694483d2c136a9220d6d49d843c and will release a patch release for all affected versions.

We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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 members of the Aivul Team from Qihoo 360.

Record
GHSA-4g9f-63rx-5cw4
CVSS 4.0
5.3 MediumCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
CVSS 3.1
5.3 MediumCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Weakness
CWE-20, CWE-476
Updated
2026-11-02
Show 6 moreShow less
OSVBIT-tensorflow-2020-15190 No score

Segfault in Tensorflow

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
BIT-tensorflow-2020-15190
Updated
2026-11-02
OSVopenSUSE-SU-2020:1766-1 No score

Security update for tensorflow2

This update for tensorflow2 fixes the following issues:

  • updated to 2.1.2 with following fixes (boo#1177022):
    • Fixes an undefined behavior causing a segfault in tf.raw_ops.Switch (CVE-2020-15190)
    • Fixes three vulnerabilities in conversion to DLPack format (CVE-2020-15191, CVE-2020-15192, CVE-2020-15193)
    • Fixes two vulnerabilities in SparseFillEmptyRowsGrad (CVE-2020-15194, CVE-2020-15195)
    • Fixes an integer truncation vulnerability in code using the work sharder API (CVE-2020-15202)
    • Fixes a format string vulnerability in tf.strings.as_string (CVE-2020-15203)
    • Fixes segfault raised by calling session-only ops in eager mode (CVE-2020-15204)
    • Fixes data leak and potential ASLR violation from tf.raw_ops.StringNGrams (CVE-2020-15205)
    • Fixes segfaults caused by incomplete SavedModel validation (CVE-2020-15206)
    • Fixes a data corruption due to a bug in negative indexing support in TFLite (CVE-2020-15207)
    • Fixes a data corruption due to dimension mismatch in TFLite (CVE-2020-15208)
    • Fixes several vulnerabilities in TFLite saved model format (CVE-2020-15209, CVE-2020-15210, CVE-2020-15211)
Record
openSUSE-SU-2020:1766-1
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-2020-113 No score

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
PYSEC-2020-113
Updated
2026-11-02
OSVPYSEC-2020-270 No score

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
PYSEC-2020-270
Updated
2026-11-02
OSVPYSEC-2020-305 No score

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the tf.raw_ops.Switch operation takes as input a tensor and a boolean and outputs two tensors. Depending on the boolean value, one of the tensors is exactly the input tensor whereas the other one should be an empty tensor. However, the eager runtime traverses all tensors in the output. Since only one of the tensors is defined, the other one is nullptr, hence we are binding a reference to nullptr. This is undefined behavior and reported as an error if compiling with -fsanitize=null. In this case, this results in a segmentation fault The issue is patched in commit da8558533d925694483d2c136a9220d6d49d843c, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Record
PYSEC-2020-305
Updated
2026-11-02

Affected products

Affected packages

Affected packages
PackageAffectedFixed
tensorflow
PyPI
 before 1.15.4
1.15.4
tensorflow
PyPI
 2.0.0 up to 2.0.3
2.0.3
tensorflow
PyPI
 2.1.0 up to 2.1.2
2.1.2
tensorflow
PyPI
 2.2.0 to 2.2.0
2.2.1
tensorflow
PyPI
 2.3.0 to 2.3.0
2.3.1
tensorflow-cpu
PyPI
 before 1.15.4
1.15.4
tensorflow-cpu
PyPI
 2.0.0 up to 2.0.3
2.0.3
tensorflow-cpu
PyPI
 2.1.0 up to 2.1.2
2.1.2
tensorflow-cpu
PyPI
 2.2.0 to 2.2.0
2.2.1
tensorflow-cpu
PyPI
 2.3.0 to 2.3.0
2.3.1
Show 27 moreShow less
Affected packages
PackageAffectedFixed
tensorflow-gpu
PyPI
 before 1.15.4
1.15.4
tensorflow-gpu
PyPI
 2.0.0 up to 2.0.3
2.0.3
tensorflow-gpu
PyPI
 2.1.0 up to 2.1.2
2.1.2
tensorflow-gpu
PyPI
 2.2.0 to 2.2.0
2.2.1
tensorflow-gpu
PyPI
 2.3.0 to 2.3.0
2.3.1
tensorflow
Bitnami
 before 1.15.4, 2.0.0 up to 2.0.3, 2.1.0 up to 2.1.2, 2.2.0 up to 2.2.1, 2.3.0 up to 2.3.1
1.15.42.0.32.1.22.2.12.3.1
tensorflow
PyPI
 before 1.15.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 24 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.0
1.15.4
tensorflow
PyPI
 2.0.0 up to 2.0.3, plus listed versions
2.0.12.0.2
2.0.3
tensorflow
PyPI
 2.1.0 up to 2.1.2, plus listed versions
2.1.1
2.1.2
tensorflow
PyPI
 2.2.0 up to 2.2.1
2.2.1
tensorflow
PyPI
 2.3.0 up to 2.3.1
2.3.1
tensorflow-cpu
PyPI
 before 1.15.4, plus listed versions
1.15.0
1.15.4
tensorflow-cpu
PyPI
 2.1.0 up to 2.1.2, plus listed versions
2.1.1
2.1.2
tensorflow-cpu
PyPI
 2.2.0 up to 2.2.1
2.2.1
tensorflow-cpu
PyPI
 2.3.0 up to 2.3.1
2.3.1
tensorflow-gpu
PyPI
 before 1.15.4, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 24 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.0
1.15.4
tensorflow-gpu
PyPI
 2.0.0 up to 2.0.3, plus listed versions
2.0.12.0.2
2.0.3
tensorflow-gpu
PyPI
 2.1.0 up to 2.1.2, plus listed versions
2.1.1
2.1.2
tensorflow-gpu
PyPI
 2.2.0 up to 2.2.1
2.2.1
tensorflow-gpu
PyPI
 2.3.0 up to 2.3.1
2.3.1
tensorflow
PyPI
 before 1.15.4, 2.0.0 up to 2.0.3, 2.1.0 up to 2.1.2, 2.2.0 up to 2.2.1, 2.3.0 up to 2.3.1, plus listed versions
0.12.0rc00.12.0rc10.12.00.12.11.0.0
Show 45 moreShow less
1.0.11.1.0rc01.1.0rc11.1.0rc21.1.01.2.0rc01.2.0rc11.2.0rc21.2.01.2.11.3.0rc01.3.0rc11.3.0rc21.3.01.4.0rc01.4.0rc11.4.01.4.11.5.0rc01.5.0rc11.5.01.5.11.6.0rc01.6.0rc11.6.01.7.0rc01.7.0rc11.7.01.7.11.8.0rc01.8.0rc11.8.01.9.0rc01.9.0rc11.9.0rc21.9.01.10.0rc01.10.0rc11.10.01.10.11.11.0rc01.11.0rc11.11.0rc21.11.01.12.0rc0
1.15.42.0.32.1.22.2.12.3.1
tensorflow-cpu
PyPI
 before 1.15.4, 2.0.0 up to 2.0.3, 2.1.0 up to 2.1.2, 2.2.0 up to 2.2.1, 2.3.0 up to 2.3.1, plus listed versions
1.15.02.1.1
1.15.42.0.32.1.22.2.12.3.1
tensorflow-gpu
PyPI
 before 1.15.4, 2.0.0 up to 2.0.3, 2.1.0 up to 2.1.2, 2.2.0 up to 2.2.1, 2.3.0 up to 2.3.1, plus listed versions
0.12.00.12.11.0.01.0.11.1.0
Show 27 moreShow less
1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.12.0.22.1.1
1.15.42.0.32.1.22.2.12.3.1
tensorflow2
openSUSE:Leap 15.2
From an advisory covering 16 CVEs
 before 2.1.2-lp152.7.3.1
2.1.2-lp152.7.3.1
tensorflow2-lite
openSUSE:Leap 15.2
From an advisory covering 16 CVEs
 before 2.1.2-lp152.7.3.1
2.1.2-lp152.7.3.1
tensorflow2_2_1_2-gnu-hpc
openSUSE:Leap 15.2
From an advisory covering 16 CVEs
 before 2.1.2-lp152.7.3.1
2.1.2-lp152.7.3.1
tensorflow2_2_1_2-gnu-openmpi2-hpc
openSUSE:Leap 15.2
From an advisory covering 16 CVEs
 before 2.1.2-lp152.7.3.1
2.1.2-lp152.7.3.1

History

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

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

In short

CVE-2020-15190 is a medium vulnerability (CVSS 5.3) in Google Tensorflow, published September 25, 2020. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.94%, the 61st percentile. Fixed in tensorflow 1.15.4.

References

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Left out here: 23 versions. The JSON record has them.

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