CVE-2026-28500

HIGH
2026-03-16 https://github.com/onnx/onnx GHSA-hqmj-h5c6-369m
8.6
CVSS 3.1
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CVSS Vector

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Changed
Confidentiality
High
Integrity
None
Availability
None

Lifecycle Timeline

3
Patch Released
Apr 07, 2026 - 02:30 nvd
Patch available
Analysis Generated
Mar 16, 2026 - 17:20 vuln.today
CVE Published
Mar 16, 2026 - 16:23 nvd
HIGH 8.6

Description

### Summary 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. ### The Technical Flaw The vulnerability is located in onnx/hub.py. The security gate uses a short-circuit evaluation that prioritizes the "silent" preference over the trust requirement: ```Python if not _verify_repo_ref(repo) and not silent: # This block (Warning + User Input) is SKIPPED if silent=True print("The model repo... is not trusted") if input().lower() != "y": return None ``` **Key Points of Failure**: Complete Suppression: If a developer or a third-party library sets silent=True, the application will download and execute models from any attacker-controlled GitHub repository without notifying the user. **Integrity Verification Bypass**: The SHA256 integrity check validates the model against a manifest file. Since the attacker controls the repository, they also control the manifest, allowing them to provide a "valid" hash for a malicious model. ### Impact 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.

Analysis

ONNX's hub.load() function can be bypassed to load untrusted models without user confirmation when the silent parameter is enabled, allowing attackers to potentially deliver malicious models to applications that suppress security warnings. The vulnerability stems from improper logic in the repository trust verification mechanism that prioritizes the silent flag over security checks. …

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Remediation

Within 24 hours: Inventory all systems and applications using ONNX hub.load() functionality and identify where silent=True parameter is explicitly set. Within 7 days: Implement network-level restrictions on GitHub access and audit dependency chains for vulnerable ONNX versions in development pipelines. …

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Priority Score

43
Low Medium High Critical
KEV: 0
EPSS: +0.0
CVSS: +43
POC: 0

Vendor Status

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CVE-2026-28500 vulnerability details – vuln.today

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