CVE-2022-41889: Tensorflow Segfault Vulnerability

MODERATE
Advisory Identifier: GHSA-xxcj-rhqg-m46g
CVSS 5.5
CWE-476
Published
Advisory Summary

CVE-2022-41889 is a MODERATE (CVSS 5.5) segfault vulnerability (CWE-476: NULL Pointer Dereference) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves segfault via invalid attributes in `pywrap_tfe_src.cc`. Remediation is available by upgrading affected packages to version 2.8.4, 2.9.3, 2.10.1.

CVE-2022-41889 at a Glance

CVE Identifier CVE-2022-41889
GHSA Identifier GHSA-xxcj-rhqg-m46g
Severity MODERATE
CVSS v3.1 Base Score 5.5
CWE Classification CWE-476: NULL Pointer Dereference
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 5.5

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:N/A:H).

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 None (I:N)
Availability High (A:H)

How to Fix CVE-2022-41889

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: 2.8.4
pip install tensorflow>=2.8.4
tensorflow fixed: 2.9.3
pip install tensorflow>=2.9.3
tensorflow fixed: 2.10.1
pip install tensorflow>=2.10.1
tensorflow-cpu fixed: 2.8.4
pip install tensorflow-cpu>=2.8.4
tensorflow-gpu fixed: 2.8.4
pip install tensorflow-gpu>=2.8.4
tensorflow-cpu fixed: 2.9.3
pip install tensorflow-cpu>=2.9.3
tensorflow-gpu fixed: 2.9.3
pip install tensorflow-gpu>=2.9.3
tensorflow-cpu fixed: 2.10.1
pip install tensorflow-cpu>=2.10.1
tensorflow-gpu fixed: 2.10.1
pip install tensorflow-gpu>=2.10.1
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-2022-41889, 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 2.8.4), 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-476: NULL Pointer Dereference, where the product dereferences a pointer that it expects to be valid but is null. 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 list of quantized tensors is assigned to an attribute, the pywrap code fails to parse the tensor and returns a `nullptr`, which is not caught. An example can be seen in [`tf.compat.v1.extract_volume_patches`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/image/generate_box_proposals_op.cu.cc) by passing in quantized tensors as input `ksizes`. ```python import numpy as np import tensorflow as tf a_input = np.array([1, -1], dtype= np.int32) a_ksizes = a_strides = tf.constant(dtype=tf.dtypes.qint16, value=[[1, 4], [5, 2]]) tf.compat.v1.extract_volume_patches(input=a_input,ksizes=a_ksizes,strides=a_strides,padding='VALID') ``` ### Patches We have patched the issue in GitHub commit [e9e95553e5411834d215e6770c81a83a3d0866ce](https://github.com/tensorflow/tensorflow/commit/e9e95553e5411834d215e6770c81a83a3d0866ce). The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, 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 Pattarakrit Rattankul.

CVE-2022-41889 Affected Tensorflow Versions

9 component(s)
Fixed Versions:
2.8.42.9.32.10.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
PyPI
< 2.8.4
2.8.4
tensorflow
PyPI
≥ 2.9.0
< 2.9.3
2.9.3
tensorflow
PyPI
≥ 2.10.0
< 2.10.1
2.10.1
tensorflow-cpu
PyPI
< 2.8.4
2.8.4
tensorflow-gpu
PyPI
< 2.8.4
2.8.4
tensorflow-cpu
PyPI
≥ 2.9.0
< 2.9.3
2.9.3
tensorflow-gpu
PyPI
≥ 2.9.0
< 2.9.3
2.9.3
tensorflow-cpu
PyPI
≥ 2.10.0
< 2.10.1
2.10.1
tensorflow-gpu
PyPI
≥ 2.10.0
< 2.10.1
2.10.1

References

Frequently Asked Questions

What is CVE-2022-41889?
CVE-2022-41889 is a security vulnerability in Tensorflow involving Segfault via invalid attributes in `pywrap_tfe_src.cc` under CWE-476: NULL Pointer Dereference.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.8.4, 2.9.3, 2.10.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2022-41889?
Upgrading to 2.8.4, 2.9.3, 2.10.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.8.4, 2.9.3, 2.10.1. Upgrade your dependency to 2.8.4, 2.9.3, 2.10.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.8.4, 2.9.3, 2.10.1. Upgrade your dependency to 2.8.4, 2.9.3, 2.10.1 or later.
What is the CVSS score of CVE-2022-41889?
CVE-2022-41889 has a CVSS v3.1 base score of 5.5 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.
What CWE is associated with CVE-2022-41889?
CVE-2022-41889 is classified under CWE-476: NULL Pointer Dereference (The product dereferences a pointer that it expects to be valid but is NULL.).
How can I check PyPI dependencies for CVE-2022-41889?
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
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