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    <title>Most recent entries from all</title>
    <link>https://cve.radiocsirt.org</link>
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    <lastBuildDate>Fri, 02 Oct 2026 14:49:50 +0000</lastBuildDate>
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      <title>CVE-2026-28500 — ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack</title>
      <link>https://cve.radiocsirt.org/vuln/cve-2026-28500</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; onnx, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI (RHOAI)&lt;/p&gt;
&lt;p&gt;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&amp;#39;s machine the moment the model is loaded. As of time of publication, no known patched versions are available.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; onnx, Red Hat OpenShift AI 2.25, Red Hat OpenShift AI (RHOAI)&lt;/p&gt;
&lt;p&gt;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&amp;#39;s machine the moment the model is loaded. As of time of publication, no known patched versions are available.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/cve-2026-28500</guid>
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    <item>
      <title>GHSA-hqmj-h5c6-369m — ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-hqmj-h5c6-369m</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: onnx&lt;/p&gt;
&lt;p&gt;## What&amp;#39;s the issue
Passing `silent=True` to `onnx.hub.load()` kills all trust warnings and user prompts. This means a model can be downloaded from any unverified GitHub repo with zero user awareness.
 
```python
if not _verify_repo_ref(repo) and not silent:
    # completely skipped when silent=True
    print(&amp;#34;The model repo... is not trusted&amp;#34;)
    if input().lower() != &amp;#34;y&amp;#34;:
        return None
```
 
On top of that, the SHA256 integrity check is useless here — it validates against a manifest that lives in the same repo the attacker controls, so the hash will always match.&lt;/p&gt;
&lt;p&gt;## Impact
Any pipeline using `hub.load()` with `silent=True` and an external repo string is silently loading whatever the repo owner ships. If that model executes arbitrary code on load, the attacker has access to the machine.
 
## Resolved by removing the feature 
## References
 
- [Write-up](https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md)&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: onnx&lt;/p&gt;
&lt;p&gt;## What&amp;#39;s the issue
Passing `silent=True` to `onnx.hub.load()` kills all trust warnings and user prompts. This means a model can be downloaded from any unverified GitHub repo with zero user awareness.
 
```python
if not _verify_repo_ref(repo) and not silent:
    # completely skipped when silent=True
    print(&amp;#34;The model repo... is not trusted&amp;#34;)
    if input().lower() != &amp;#34;y&amp;#34;:
        return None
```
 
On top of that, the SHA256 integrity check is useless here — it validates against a manifest that lives in the same repo the attacker controls, so the hash will always match.&lt;/p&gt;
&lt;p&gt;## Impact
Any pipeline using `hub.load()` with `silent=True` and an external repo string is silently loading whatever the repo owner ships. If that model executes arbitrary code on load, the attacker has access to the machine.
 
## Resolved by removing the feature 
## References
 
- [Write-up](https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md)&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-hqmj-h5c6-369m</guid>
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