CVE-2026-31229
"ART Kubeflow Insecure Deserialization Remote Code Execution"
Description
The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains an insecure deserialization vulnerability (CWE-502) in its Kubeflow component's model loading functionality. When loading model weights from a file (e.g., model.pt) during robustness evaluation, the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by uploading a maliciously crafted model file to an object storage location referenced by the pipeline, or by controlling the model_id parameter to point to such a file. When the pipeline loads the model, the malicious payload is executed, leading to remote code execution.
INFO
Published Date :
May 12, 2026, 6:16 p.m.
Last Modified :
May 12, 2026, 6:16 p.m.
Remotely Exploit :
No
Source :
[email protected]
Affected Products
The following products are affected by CVE-2026-31229
vulnerability.
Even if cvefeed.io is aware of the exact versions of the
products
that
are
affected, the information is not represented in the table below.
No affected product recoded yet
Solution
- Update the Adversarial Robustness Toolbox to version 1.21.0 or later.
- Ensure torch.load uses weights_only=True for model loading.
- Validate model file integrity before loading.
- Restrict access to model storage locations.
References to Advisories, Solutions, and Tools
Here, you will find a curated list of external links that provide in-depth
information, practical solutions, and valuable tools related to
CVE-2026-31229.
| URL | Resource |
|---|---|
| https://github.com/Trusted-AI/adversarial-robustness-toolbox | |
| https://www.notion.so/CVE-2026-31229-35d1e13931888172863dcc20beeb6b70 |
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2026-31229 is
associated with the following CWEs:
Common Attack Pattern Enumeration and Classification (CAPEC)
Common Attack Pattern Enumeration and Classification
(CAPEC)
stores attack patterns, which are descriptions of the common attributes and
approaches employed by adversaries to exploit the CVE-2026-31229
weaknesses.
We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).
Results are limited to the first 15 repositories due to potential performance issues.
The following list is the news that have been mention
CVE-2026-31229 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2026-31229 vulnerability over time.
Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.
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New CVE Received by [email protected]
May. 12, 2026
Action Type Old Value New Value Added Description The Adversarial Robustness Toolbox (ART) thru 1.20.1 contains an insecure deserialization vulnerability (CWE-502) in its Kubeflow component's model loading functionality. When loading model weights from a file (e.g., model.pt) during robustness evaluation, the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by uploading a maliciously crafted model file to an object storage location referenced by the pipeline, or by controlling the model_id parameter to point to such a file. When the pipeline loads the model, the malicious payload is executed, leading to remote code execution. Added Reference https://github.com/Trusted-AI/adversarial-robustness-toolbox Added Reference https://www.notion.so/CVE-2026-31229-35d1e13931888172863dcc20beeb6b70