CVE-2026-28500CWE-345CWE-494CWE-693

ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack

High · published March 18, 2026

CVSS v3.1
8.6
EPSS
0%
Percentile
24.2
In the wild
Unconfirmed
What it is

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 record
Technical detail
CVSS v3.1
8.6 · HIGH
Vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
CVSS v4.0
Not supplied
EPSS
0.00324 · 24.2th percentile
Weaknesses
CWE-345 · Insufficient Verification of Data Authenticity; CWE-494 · Download of Code Without Integrity Check; CWE-693 · Protection Mechanism Failure
Published
2026-03-18T01:15Z
EPSS history
Timeline
  • 18 MAR 01:15Z
    ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack
    cvelistv5