Onnx · Onnx · CVE-2026-28500
**Name of the Vulnerable Software and Affected Versions**
Open Neural Network Exchange (ONNX) versions through 1.20.1
**Description**
ONNX is an open standard for machine learning interoperability. A security control bypass exists in the `onnx.hub.load()` function due to flawed repository trust verification logic. The `silent=True` parameter suppresses security warnings and confirmation prompts, enabling Zero-Interaction Supply-Chain Attacks. When combined with file-system weaknesses, an attacker can silently exfiltrate sensitive files, such as SSH keys and cloud credentials, from a victim's machine when a model is loaded. The vulnerability stems from the short-circuit evaluation in `onnx/hub.py`, where the `silent` parameter overrides the trust requirement. The SHA256 integrity check is also susceptible because the attacker controls both the model files and the manifest used for verification.
**Recommendations**
For all versions up to and including 1.20.1, avoid using the `silent=True` parameter in `onnx.hub.load()`. As a temporary workaround, consider loading models from local files after manual verification. Compute SHA256 hashes independently instead of relying on the hub manifest. Audit your codebase for usages of `silent=True` with `grep -r "silent.*True" --include="*.py"`.