ghsa-pmqf-x6x8-p7qw
Vulnerability from github
Published
2025-11-20 21:23
Modified
2025-11-21 15:31
Severity ?
6.5 (Medium) - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
8.3 (High) - CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H
Summary
vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs
Details

Summary

Users can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct ndim but incorrect shape (e.g. hidden dimension is wrong), regardless of whether the model is intended to support such inputs (as defined in the Supported Models page).

The issue has existed ever since we added support for image embedding inputs, i.e. #6613 (released in v0.5.5)

Details

Using image embeddings as an example:

  • For models that support image embedding inputs, the engine crashes when scattering the embeddings to inputs_embeds (mismatched shape)
  • For models that don't support image embedding inputs, the engine crashes when validating the inputs inside get_input_embeddings (validation fails).

This happens because we only validate ndim of the tensor, but not the full shape, in input processor (via MultiModalDataParser).

Impact

  • Denial of service by crashing the engine

Mitigation

  • Use API key to limit access to trusted users.
  • Set --limit-mm-per-prompt to 0 for all non-text modalities to ban multimodal inputs, which includes multimodal embedding inputs. However, the model would then only accept text, defeating the purpose of using a multi-modal model.

Resolution

  • https://github.com/vllm-project/vllm/pull/27204
Show details on source website

To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.5.5"
            },
            {
              "fixed": "0.11.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-62372"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-129"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-11-20T21:23:29Z",
    "nvd_published_at": "2025-11-21T02:15:43Z",
    "severity": "HIGH"
  },
  "details": "### Summary\n\nUsers can crash the vLLM engine serving multimodal models by passing multimodal embedding inputs with correct `ndim` but incorrect `shape` (e.g. hidden dimension is wrong), regardless of whether the model is intended to support such inputs (as defined in the Supported Models page).\n\nThe issue has existed ever since we added support for image embedding inputs, i.e. #6613 (released in v0.5.5)\n\n### Details\n\nUsing image embeddings as an example:\n\n- For models that support image embedding inputs, the engine crashes when scattering the embeddings to `inputs_embeds` (mismatched shape)\n- For models that don\u0027t support image embedding inputs, the engine crashes when validating the inputs inside `get_input_embeddings` (validation fails).\n\nThis happens because we only validate `ndim` of the tensor, but not the full shape, in input processor (via `MultiModalDataParser`).\n\n### Impact\n\n- Denial of service by crashing the engine\n\n### Mitigation\n\n- Use API key to limit access to trusted users.\n- Set `--limit-mm-per-prompt` to 0 for all non-text modalities to ban multimodal inputs, which includes multimodal embedding inputs. However, the model would then only accept text, defeating the purpose of using a multi-modal model.\n\n### Resolution\n\n- https://github.com/vllm-project/vllm/pull/27204",
  "id": "GHSA-pmqf-x6x8-p7qw",
  "modified": "2025-11-21T15:31:38Z",
  "published": "2025-11-20T21:23:29Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-pmqf-x6x8-p7qw"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-62372"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/pull/27204"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/pull/6613"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/commit/58fab50d82838d5014f4a14d991fdb9352c9c84b"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/vllm-project/vllm"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H",
      "type": "CVSS_V4"
    }
  ],
  "summary": "vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs"
}


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