CVEvulnerability

CVE-2026-28500

9.1 CRITICAL Published 2026-03-18 Modified 2026-07-15 Official page ↗
Status
Modified
Published
2026-03-18
Last modified
2026-07-15
Assigner
[email protected]
CVSS 3.1 ([email protected])
8.6 HIGH — CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
CVSS 3.1 ([email protected])
9.1 CRITICAL — CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
CVSS 3.1 (0b0ca135-0b70-47e7-9f44-1890c2a1c46c)
8.6 HIGH — CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Weaknesses
CWE-345, CWE-494, CWE-693, CWE-829

Description

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.

Affected configurations

• linuxfoundation onnx (<= 1.20.1)

Related

Weakness · CWE (4)

  • CWE-345 Insufficient Verification of Data Authenticity weakness
  • CWE-494 Download of Code Without Integrity Check weakness
  • CWE-693 Protection Mechanism Failure weakness
  • CWE-829 Inclusion of Functionality from Untrusted Control Sphere weakness

References