Insufficient Verification of Data Authenticity Affecting nemo package, versions <2.7.2-r1


Severity

Recommended
0.0
critical
0
10

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Threat Intelligence

EPSS
0.01% (2nd percentile)

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  • Snyk IDSNYK-CHAINGUARDLATEST-NEMO-16078069
  • published16 Apr 2026
  • disclosed18 Mar 2026

Introduced: 18 Mar 2026

CVE-2026-28500  (opens in a new tab)
CWE-345  (opens in a new tab)
CWE-494  (opens in a new tab)
CWE-693  (opens in a new tab)

How to fix?

Upgrade Chainguard nemo to version 2.7.2-r1 or higher.

NVD Description

Note: Versions mentioned in the description apply only to the upstream nemo package and not the nemo package as distributed by Chainguard. See How to fix? for Chainguard relevant fixed versions and status.

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 Base Scores

version 3.1