CVE-2026-28500
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.
Does this matter?
High impact if exploited, but EPSS currently rates exploitation as unlikely (0.32%). Schedule it in the normal patch cycle and watch for a rise in EPSS or a public exploit.
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.
- CVSS 3.1
- 9.1 CRITICALCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N
- EPSS
- 0.32% probability · 25th percentile
- CISA KEV
- Not listed
- Weakness
- CWE-345, CWE-494, CWE-693, CWE-829
- Affected
- linuxfoundation/onnx
- Source
- security-advisories@github.com
References
- https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.mdPatch
- https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369mVendor Advisory
- https://access.redhat.com/errata/RHSA-2026:24977
- https://access.redhat.com/security/cve/CVE-2026-28500
- https://bugzilla.redhat.com/show_bug.cgi?id=2448518
- https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.mdPatch
- https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-28500.json
Source: NVD record, EPSS from FIRST.org, KEV from CISA. Refreshed daily.