onnx onnx.hub.load data authenticity

Summaryinfo

A vulnerability labeled as problematic has been found in onnx. Impacted is the function onnx.hub.load. The manipulation results in data authenticity. This vulnerability is reported as CVE-2026-28500. The attack can be launched remotely. No exploit exists.

Detailsinfo

A vulnerability was found in onnx (the affected version unknown). It has been classified as problematic. Affected is the function onnx.hub.load. The manipulation with an unknown input leads to a data authenticity vulnerability. CWE is classifying the issue as CWE-345. The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data. This is going to have an impact on confidentiality. CVE summarizes:

Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. In versions up to and including 1.20.1, a security control bypass exists in onnx.hub.load() due to improper logic in the repository trust verification mechanism. While the function is designed to warn users when loading models from non-official sources, the use of the silent=True parameter completely suppresses all security warnings and confirmation prompts. This vulnerability transforms a standard model-loading function into a vector for Zero-Interaction Supply-Chain Attacks. When chained with file-system vulnerabilities, an attacker can silently exfiltrate sensitive files (SSH keys, cloud credentials) from the victim's machine the moment the model is loaded. As of time of publication, no known patched versions are available.

The advisory is shared for download at github.com. This vulnerability is traded as CVE-2026-28500. The exploitability is told to be easy. It is possible to launch the attack remotely. The exploitation doesn't require any form of authentication. There are known technical details, but no exploit is available. The current price for an exploit might be approx. USD $0-$5k (estimation calculated on 03/22/2026).

The vulnerability scanner Nessus provides a plugin with the ID 302885 (Linux Distros Unpatched Vulnerability : CVE-2026-28500), which helps to determine the existence of the flaw in a target environment.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

The vulnerability is also documented in the vulnerability database at Tenable (302885). VulDB is the best source for vulnerability data and more expert information about this specific topic.

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VulDB is the best source for vulnerability data and more expert information about this specific topic.

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