CVE-2020-15191: Tensorflow Undefined Behavior Vulnerability

MODERATE
Advisory Identifier: GHSA-q8qj-fc9q-cphr
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CVSS 5.3
CWE-252 CWE-20 CWE-476
Published
Advisory Summary

CVE-2020-15191 is a MODERATE (CVSS 5.3) undefined behavior vulnerability (CWE-252: Unchecked Return Value) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves undefined behavior in tensorflow. Remediation is available by upgrading affected packages to version 2.2.1, 2.3.1.

CVE-2020-15191 at a Glance

CVE Identifier CVE-2020-15191
GHSA Identifier GHSA-q8qj-fc9q-cphr
Severity MODERATE
CVSS v3.1 Base Score 5.3
CWE Classification CWE-252: Unchecked Return Value
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 5.3

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality None (C:N)
Integrity None (I:N)
Availability Low (A:L)

How to Fix CVE-2020-15191

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 2.2.1 
pip install tensorflow>=2.2.1
tensorflow fixed: 2.3.1 
pip install tensorflow>=2.3.1
tensorflow-cpu fixed: 2.2.1 
pip install tensorflow-cpu>=2.2.1
tensorflow-cpu fixed: 2.3.1 
pip install tensorflow-cpu>=2.3.1
tensorflow-gpu fixed: 2.2.1 
pip install tensorflow-gpu>=2.2.1
tensorflow-gpu fixed: 2.3.1 
pip install tensorflow-gpu>=2.3.1
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2020-15191, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.2.1), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-252: Unchecked Return Value, where the product does not check the return value from a method or function, which can prevent it from detecting unexpected states and conditions. In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Impact If a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition. However, this `status` argument is not properly checked: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L265-L267 Hence, code following these methods will bind references to null pointers: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L279-L285 This is undefined behavior and reported as an error if compiling with `-fsanitize=null`. ### Patches We have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions. We recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been discovered during variant analysis of [GHSA-rjjg-hgv6-h69v](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v).

CVE-2020-15191 Affected Tensorflow Versions

6 component(s)
Fixed Versions:
2.2.12.3.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
≥ 2.2.0
< 2.2.1
All 1 versions
2.2.0
2.2.1
tensorflow
pypi/tensorflow
PyPI
≥ 2.3.0
< 2.3.1
All 1 versions
2.3.0
2.3.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.2.0
< 2.2.1
All 1 versions
2.2.0
2.2.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.3.0
< 2.3.1
All 1 versions
2.3.0
2.3.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.2.0
< 2.2.1
All 1 versions
2.2.0
2.2.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.3.0
< 2.3.1
All 1 versions
2.3.0
2.3.1

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q8qj-fc9q-cphr
NVD — CVE-2020-15191 NVD
https://nvd.nist.gov/vuln/detail/CVE-2020-15191
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/22e07fb204386768e5bcbea563641ea11f96ceb8
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-271.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-306.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-114.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Release RELEASE
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
Tensorflow Security Information SECURITY
http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

Frequently Asked Questions

What is CVE-2020-15191?
CVE-2020-15191 is a security vulnerability in Tensorflow involving Undefined behavior in Tensorflow under CWE-252: Unchecked Return Value.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.2.1, 2.3.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2020-15191?
Upgrading to 2.2.1, 2.3.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.2.1, 2.3.1. Upgrade your dependency to 2.2.1, 2.3.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.2.1, 2.3.1. Upgrade your dependency to 2.2.1, 2.3.1 or later.
What is the CVSS score of CVE-2020-15191?
CVE-2020-15191 has a CVSS v3.1 base score of 5.3 (MODERATE) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2020-15191?
CVE-2020-15191 is classified under CWE-252: Unchecked Return Value (The product does not check the return value from a method or function, which can prevent it from detecting unexpected states and conditions.).
How can I check PyPI dependencies for CVE-2020-15191?
Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
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  "details" : "### Impact\nIf a user passes an invalid argument to `dlpack.to_dlpack` the expected validations will cause variables to bind to `nullptr` while setting a `status` variable to the error condition.\n\nHowever, this `status` argument is not properly checked:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L265-L267\n\nHence, code following these methods will bind references to null pointers:\nhttps://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/c/eager/dlpack.cc#L279-L285\n\nThis is undefined behavior and reported as an error if compiling with `-fsanitize=null`.\n\n### Patches\nWe have patched the issue in 22e07fb204386768e5bcbea563641ea11f96ceb8 and will release a patch release for all affected versions.\n\nWe recommend users to upgrade to TensorFlow 2.2.1 or 2.3.1.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been discovered during variant analysis of [GHSA-rjjg-hgv6-h69v](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rjjg-hgv6-h69v).",
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