CVE-2026-34445
ONNX: Malicious ONNX models can crash servers by exploiting unprotected object settings.
Description
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
INFO
Published Date :
April 1, 2026, 6:16 p.m.
Last Modified :
April 1, 2026, 6:16 p.m.
Remotely Exploit :
Yes !
Source :
[email protected]
Affected Products
The following products are affected by CVE-2026-34445
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
CVSS Scores
| Score | Version | Severity | Vector | Exploitability Score | Impact Score | Source |
|---|---|---|---|---|---|---|
| CVSS 3.1 | HIGH | [email protected] | ||||
| CVSS 3.1 | HIGH | MITRE-CVE |
Solution
- Update ONNX to version 1.21.0 or later.
- Ensure metadata is validated before loading.
- Avoid loading metadata from untrusted sources.
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-2026-34445.
| URL | Resource |
|---|---|
| https://github.com/onnx/onnx/commit/e30c6935d67cc3eca2fa284e37248e7c0036c46b | |
| https://github.com/onnx/onnx/pull/7751 | |
| https://github.com/onnx/onnx/security/advisories/GHSA-538c-55jv-c5g9 |
CWE - Common Weakness Enumeration
While CVE identifies
specific instances of vulnerabilities, CWE categorizes the common flaws or
weaknesses that can lead to vulnerabilities. CVE-2026-34445 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-2026-34445
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-2026-34445 vulnerability anywhere in the article.
The following table lists the changes that have been made to the
CVE-2026-34445 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]
Apr. 01, 2026
Action Type Old Value New Value Added Description Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0. Added CVSS V3.1 AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H Added CWE CWE-20 Added CWE CWE-400 Added CWE CWE-915 Added Reference https://github.com/onnx/onnx/commit/e30c6935d67cc3eca2fa284e37248e7c0036c46b Added Reference https://github.com/onnx/onnx/pull/7751 Added Reference https://github.com/onnx/onnx/security/advisories/GHSA-538c-55jv-c5g9