Vulnerability-Lookup

GHSA-HQMJ-H5C6-369M

Vulnerability from github – Published: 2026-03-16 16:23 – Updated: 2026-04-06 23:11

Summary

ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack

Details

What'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.

if not _verify_repo_ref(repo) and not silent:
    # completely skipped when silent=True
    print("The model repo... is not trusted")
    if input().lower() != "y":
        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.

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

Severity ?

8.6 (High)


                  
                    CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c= 1.20.1"
      },
      "package": {
        "ecosystem": "PyPI",
        "name": "onnx"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "1.21.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-28500"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-345",
      "CWE-494",
      "CWE-693"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-03-16T16:23:28Z",
    "nvd_published_at": "2026-03-18T02:16:24Z",
    "severity": "HIGH"
  },
  "details": "## What\u0027s the issue\nPassing `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.\n \n```python\nif not _verify_repo_ref(repo) and not silent:\n    # completely skipped when silent=True\n    print(\"The model repo... is not trusted\")\n    if input().lower() != \"y\":\n        return None\n```\n \nOn top of that, the SHA256 integrity check is useless here \u2014 it validates against a manifest that lives in the same repo the attacker controls, so the hash will always match.\n\n \n## Impact\nAny 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.\n \n## Resolved by removing the feature \n## References\n \n- [Write-up](https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md)",
  "id": "GHSA-hqmj-h5c6-369m",
  "modified": "2026-04-06T23:11:55Z",
  "published": "2026-03-16T16:23:28Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-28500"
    },
    {
      "type": "WEB",
      "url": "https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/onnx/onnx"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() \u2014 Silent Supply-Chain Attack"
}

CVE-2026-28500 (GCVE-0-2026-28500)

Vulnerability from cvelistv5 – Published: 2026-03-18 01:15 – Updated: 2026-03-18 14:08

Title

ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack

Summary

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.

Severity ?

8.6 (High)


                        
                          CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N

CWE

CWE-345 - Insufficient Verification of Data Authenticity
CWE-494 - Download of Code Without Integrity Check
CWE-693 - Protection Mechanism Failure

Assigner

GitHub_M

References

URL

Tags

	https://github.com/onnx/onnx/security/advisories/…	x_refsource_CONFIRM
	https://github.com/ZeroXJacks/CVEs/blob/main/2026…	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	onnx	onnx	Affected: <= 1.20.1

Show details on NVD website

JSON

To clipboard

{
  "containers": {
    "adp": [
      {
        "metrics": [
          {
            "other": {
              "content": {
                "id": "CVE-2026-28500",
                "options": [
                  {
                    "Exploitation": "poc"
                  },
                  {
                    "Automatable": "yes"
                  },
                  {
                    "Technical Impact": "partial"
                  }
                ],
                "role": "CISA Coordinator",
                "timestamp": "2026-03-18T14:08:46.596652Z",
                "version": "2.0.3"
              },
              "type": "ssvc"
            }
          }
        ],
        "providerMetadata": {
          "dateUpdated": "2026-03-18T14:08:50.003Z",
          "orgId": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
          "shortName": "CISA-ADP"
        },
        "references": [
          {
            "tags": [
              "exploit"
            ],
            "url": "https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md"
          }
        ],
        "title": "CISA ADP Vulnrichment"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "onnx",
          "vendor": "onnx",
          "versions": [
            {
              "status": "affected",
              "version": "\u003c= 1.20.1"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "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\u0027s machine the moment the model is loaded. As of time of publication, no known patched versions are available."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "NETWORK",
            "availabilityImpact": "NONE",
            "baseScore": 8.6,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "CHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-345",
              "description": "CWE-345: Insufficient Verification of Data Authenticity",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-494",
              "description": "CWE-494: Download of Code Without Integrity Check",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-693",
              "description": "CWE-693: Protection Mechanism Failure",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2026-03-18T01:15:07.644Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "name": "https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m",
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m"
        },
        {
          "name": "https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md",
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md"
        }
      ],
      "source": {
        "advisory": "GHSA-hqmj-h5c6-369m",
        "discovery": "UNKNOWN"
      },
      "title": "ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() \u2014 Silent Supply-Chain Attack"
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2026-28500",
    "datePublished": "2026-03-18T01:15:07.644Z",
    "dateReserved": "2026-02-27T20:57:47.708Z",
    "dateUpdated": "2026-03-18T14:08:50.003Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.2"
}

Sightings

Author	Source	Type	Date

Nomenclature

Seen: The vulnerability was mentioned, discussed, or observed by the user.
Confirmed: The vulnerability has been validated from an analyst's perspective.
Published Proof of Concept: A public proof of concept is available for this vulnerability.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
Not confirmed: The user expressed doubt about the validity of the vulnerability.
Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.

Detection rules are retrieved from Rulezet.

Action not permitted

GHSA-HQMJ-H5C6-369M

What's the issue

Impact

Resolved by removing the feature

References

CVE-2026-28500 (GCVE-0-2026-28500)

Tags

Sightings

Nomenclature