CVE-2020-26270: Tensorflow CHECK-fail Vulnerability

MODERATE
Advisory Identifier: GHSA-m648-33qf-v3gp
Share
CVSS 4.4
CWE-20
Published
Advisory Summary

CVE-2020-26270 is a MODERATE (CVSS 4.4) check-fail vulnerability (CWE-20: Improper Input Validation) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves check-fail in lstm with zero-length input in tensorflow. Remediation is available by upgrading affected packages to version 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2.

CVE-2020-26270 at a Glance

CVE Identifier CVE-2020-26270
GHSA Identifier GHSA-m648-33qf-v3gp
Severity MODERATE
CVSS v3.1 Base Score 4.4
CWE Classification CWE-20: Improper Input Validation
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 4.4

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

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

How to Fix CVE-2020-26270

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: 1.15.5 
pip install tensorflow>=1.15.5
tensorflow fixed: 2.0.4 
pip install tensorflow>=2.0.4
tensorflow fixed: 2.1.3 
pip install tensorflow>=2.1.3
tensorflow fixed: 2.2.2 
pip install tensorflow>=2.2.2
tensorflow fixed: 2.3.2 
pip install tensorflow>=2.3.2
tensorflow-cpu fixed: 1.15.5 
pip install tensorflow-cpu>=1.15.5
tensorflow-cpu fixed: 2.0.4 
pip install tensorflow-cpu>=2.0.4
tensorflow-cpu fixed: 2.1.3 
pip install tensorflow-cpu>=2.1.3
tensorflow-cpu fixed: 2.2.2 
pip install tensorflow-cpu>=2.2.2
tensorflow-cpu fixed: 2.3.2 
pip install tensorflow-cpu>=2.3.2
tensorflow-gpu fixed: 1.15.5 
pip install tensorflow-gpu>=1.15.5
tensorflow-gpu fixed: 2.0.4 
pip install tensorflow-gpu>=2.0.4
tensorflow-gpu fixed: 2.1.3 
pip install tensorflow-gpu>=2.1.3
tensorflow-gpu fixed: 2.2.2 
pip install tensorflow-gpu>=2.2.2
tensorflow-gpu fixed: 2.3.2 
pip install tensorflow-gpu>=2.3.2
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-2020-26270, 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 1.15.5), 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-20: Improper Input Validation, where the product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly. 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 Running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a `CHECK` failure when using the CUDA backend. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. ### Patches We have patched the issue in GitHub commit [14755416e364f17fb1870882fa778c7fec7f16e3](https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive. ### 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.

CVE-2020-26270 Affected Tensorflow Versions

15 component(s)
Fixed Versions:
1.15.52.0.42.1.32.2.22.3.2
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 1.15.5
1.15.5
tensorflow
pypi/tensorflow
PyPI
≥ 2.0.0
< 2.0.4
2.0.4
tensorflow
pypi/tensorflow
PyPI
≥ 2.1.0
< 2.1.3
2.1.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.2.0
< 2.2.2
2.2.2
tensorflow
pypi/tensorflow
PyPI
≥ 2.3.0
< 2.3.2
2.3.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 1.15.5
1.15.5
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.0.0
< 2.0.4
2.0.4
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.1.0
< 2.1.3
2.1.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.2.0
< 2.2.2
2.2.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.3.0
< 2.3.2
2.3.2
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 1.15.5
1.15.5
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.0.0
< 2.0.4
2.0.4
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.1.0
< 2.1.3
2.1.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.2.0
< 2.2.2
2.2.2
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.3.0
< 2.3.2
2.3.2

References

Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m648-33qf-v3gp
NVD — CVE-2020-26270 NVD
https://nvd.nist.gov/vuln/detail/CVE-2020-26270
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-301.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-336.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-256.yaml

Frequently Asked Questions

What is CVE-2020-26270?
CVE-2020-26270 is a security vulnerability in Tensorflow involving CHECK-fail in LSTM with zero-length input in TensorFlow under CWE-20: Improper Input Validation.
Which Tensorflow versions are affected?
Affected versions include releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2020-26270?
Upgrading to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2. Upgrade your dependency to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2. Upgrade your dependency to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or later.
What is the CVSS score of CVE-2020-26270?
CVE-2020-26270 has a CVSS v3.1 base score of 4.4 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L.
What CWE is associated with CVE-2020-26270?
CVE-2020-26270 is classified under CWE-20: Improper Input Validation (The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.).
How can I check PyPI dependencies for CVE-2020-26270?
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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  "id" : "GHSA-m648-33qf-v3gp",
  "modified" : "2024-10-28T20:08:27Z",
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  "aliases" : [ "CVE-2020-26270" ],
  "summary" : "CHECK-fail in LSTM with zero-length input in TensorFlow",
  "details" : "### Impact\nRunning an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a `CHECK` failure when using the CUDA backend.\n\nThis can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer.\n\n### Patches\nWe have patched the issue in GitHub commit [14755416e364f17fb1870882fa778c7fec7f16e3](https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\n\nSince this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.\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.",
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}