GHSA-mw6j-hh29-h379: Tensorflow `CHECK` Failure Vulnerability

MODERATE
Share
CWE-190
Published
Advisory Summary

GHSA-mw6j-hh29-h379 is a MODERATE `check` failure vulnerability (CWE-190: Integer Overflow or Wraparound) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves `check` failure in depthwise ops via overflows. Remediation is available by upgrading affected packages to version 2.6.4, 2.7.2, 2.8.1.

GHSA-mw6j-hh29-h379 at a Glance

CVE Identifier N/A
GHSA Identifier GHSA-mw6j-hh29-h379
Severity MODERATE
CVSS v3.1 Base Score N/A
CWE Classification CWE-190: Integer Overflow or Wraparound
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

How to Fix GHSA-mw6j-hh29-h379

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: 2.6.4 
pip install tensorflow>=2.6.4
tensorflow fixed: 2.7.2 
pip install tensorflow>=2.7.2
tensorflow fixed: 2.8.1 
pip install tensorflow>=2.8.1
tensorflow-cpu fixed: 2.6.4 
pip install tensorflow-cpu>=2.6.4
tensorflow-cpu fixed: 2.7.2 
pip install tensorflow-cpu>=2.7.2
tensorflow-cpu fixed: 2.8.1 
pip install tensorflow-cpu>=2.8.1
tensorflow-gpu fixed: 2.6.4 
pip install tensorflow-gpu>=2.6.4
tensorflow-gpu fixed: 2.7.2 
pip install tensorflow-gpu>=2.7.2
tensorflow-gpu fixed: 2.8.1 
pip install tensorflow-gpu>=2.8.1
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 GHSA-mw6j-hh29-h379, 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 2.6.4), 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-190: Integer Overflow or Wraparound, where the product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. this occurs when an integer value is incremented to a value that is too large to store in the associated representation. when this occurs, the value may become a very small or negative number. 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 The implementation of depthwise ops in TensorFlow is vulnerable to a denial of service via `CHECK`-failure (assertion failure) caused by overflowing the number of elements in a tensor: ```python import tensorflow as tf input = tf.constant(1, shape=[1, 4, 4, 3], dtype=tf.float32) filter_sizes = tf.constant(1879048192, shape=[13], dtype=tf.int32) out_backprop = tf.constant(1, shape=[1, 4, 4, 3], dtype=tf.float32) tf.raw_ops.DepthwiseConv2dNativeBackpropFilter( input=input, filter_sizes=filter_sizes, out_backprop=out_backprop, strides=[1, 1, 1, 1], padding="SAME") ``` This is another instance of [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md) (CVE-2021-41197). ### Patches We have patched the issue in GitHub commit [3796cc4fcd93ae55812a457abc96dcd55fbb854b](https://github.com/tensorflow/tensorflow/commit/3796cc4fcd93ae55812a457abc96dcd55fbb854b). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### 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 reported by Neophytos Christou from Secure Systems Lab at Brown University.

GHSA-mw6j-hh29-h379 Affected Tensorflow Versions

9 component(s)
Fixed Versions:
2.6.42.7.22.8.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 2.6.4
2.6.4
tensorflow
pypi/tensorflow
PyPI
≥ 2.7.0
< 2.7.2
2.7.2
tensorflow
pypi/tensorflow
PyPI
≥ 2.8.0
< 2.8.1
2.8.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.6.4
2.6.4
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.7.0
< 2.7.2
2.7.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.8.0
< 2.8.1
2.8.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.6.4
2.6.4
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.7.0
< 2.7.2
2.7.2
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.8.0
< 2.8.1
2.8.1

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-mw6j-hh29-h379
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/3796cc4fcd93ae55812a457abc96dcd55fbb854b
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md

Frequently Asked Questions

What is GHSA-mw6j-hh29-h379?
GHSA-mw6j-hh29-h379 is a security vulnerability in Tensorflow involving `CHECK` failure in depthwise ops via overflows under CWE-190: Integer Overflow or Wraparound.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.6.4, 2.7.2, 2.8.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes GHSA-mw6j-hh29-h379?
Upgrading to 2.6.4, 2.7.2, 2.8.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.6.4, 2.7.2, 2.8.1. Upgrade your dependency to 2.6.4, 2.7.2, 2.8.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.6.4, 2.7.2, 2.8.1. Upgrade your dependency to 2.6.4, 2.7.2, 2.8.1 or later.
What CWE is associated with GHSA-mw6j-hh29-h379?
GHSA-mw6j-hh29-h379 is classified under CWE-190: Integer Overflow or Wraparound (The product performs a calculation that can produce an integer overflow or wraparound when the logic assumes that the resulting value will always be larger than the original value. This occurs when an integer value is incremented to a value that is too large to store in the associated representation. When this occurs, the value may become a very small or negative number.).
How can I check PyPI dependencies for GHSA-mw6j-hh29-h379?
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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