vLLM: Downmix Implementation Differences as Attack Vectors Against Audio AI Models

{
  "id": "6ff4ec0eadba5a987a9b4abd2a9caea3fe9b8363faa69185305a455314f713f5",
  "url": "https://osv.dev/vulnerability/CVE-2026-34760",
  "method": "structured",
  "payload": {
    "kind": "advisory",
    "title": "vLLM: Downmix Implementation Differences as Attack Vectors Against Audio AI Models",
    "summary": "vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before version 0.18.0, Librosa defaults to using numpy.mean for mono downmixing (to_mono), while the international standard ITU-R BS.775-4 specifies a weighted downmixing algorithm. This discrepancy results in inconsistency between audio heard by humans (e.g., through headphones/regular speakers) and audio processed by AI models (Which infra via Librosa, such as vllm, transformer). This issue has been patched in version 0.18.0.",
    "evidence": "osv:CVE-2026-34760",
    "products": [],
    "severity": "medium",
    "structured": {
      "id": "CVE-2026-34760",
      "aliases": [
        "CVE-2026-34760",
        "GHSA-6c4r-fmh3-7rh8",
        "PYSEC-2026-2299"
      ],
      "metrics": [
        {
          "type": "CVSS_V3",
          "score": "CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:U/C:N/I:H/A:L"
        }
      ],
      "affected": [
        {
          "ranges": [
            {
              "repo": "https://github.com/vllm-project/vllm",
              "type": "GIT",
              "events": [
                {
                  "introduced": "09c7792610ada9f88bbf87d32b472dd44bf23cc2"
                },
                {
                  "fixed": "bcf2be96120005e9aea171927f85055a6a5c0cf6"
                },
                {
                  "fixed": "c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4"
                }
              ],
              "database_specific": {
                "extracted_events": [
                  {
                    "cpe": "cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*",
                    "range": [
                      {
                        "introduced": "0.5.5"
                      },
                      {
                        "fixed": "0.18.0"
                      }
                    ],
                    "source": "CPE_RANGE"
                  },
                  {
                    "range": [
                      {
                        "fixed": "c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4"
                      }
                    ],
                    "source": "REFERENCES_COMMIT"
                  },
                  {
                    "range": [
                      {
                        "fixed": "bcf2be96120005e9aea171927f85055a6a5c0cf6"
                      }
                    ],
                    "source": "REFERENCES_TAG",
                    "original_tag": "v0.18.0"
                  }
                ]
              }
            }
          ],
          "versions": [
            "v0.18.0rc2",
            "v0.18.0rc1",
            "v0.17.2rc0",
            "v0.18.0rc0",
            "v0.17.1rc0",
            "v0.17.0rc0",
            "v0.16.0rc1",
            "v0.15.2rc0",
            "v0.16.0rc0",
            "v0.15.0rc1",
            "v0.14.0rc1",
            "v0.14.0rc0",
            "v0.13.0rc1",
            "v0.11.1",
            "v0.11.1rc6",
            "v0.11.1rc5",
            "v0.11.1rc4",
            "v0.11.1rc3",
            "v0.11.1rc2",
            "v0.11.1rc1",
            "v0.11.1rc0",
            "v0.11.0rc1",
            "v0.10.2rc2",
            "v0.10.2rc1",
            "v0.10.1rc1",
            "v0.10.0rc2",
            "v0.10.0",
            "v0.10.0rc1",
            "v0.9.2rc1",
            "v0.9.1rc2",
            "v0.9.1",
            "v0.9.1rc1",
            "v0.9.0",
            "v0.8.4",
            "v0.8.3rc1",
            "v0.8.2",
            "v0.8.1",
            "v0.8.0rc2",
            "v0.8.0rc1",
            "v0.7.3",
            "v0.7.2",
            "v0.7.1",
            "v0.7.0",
            "v0.6.6.post1",
            "v0.6.6",
            "v0.6.5",
            "v0.6.4.post1",
            "v0.6.4",
            "v0.6.3.post1",
            "v0.6.3",
            "v0.6.2",
            "v0.6.1.post2",
            "v0.6.1.post1",
            "v0.6.1",
            "v0.6.0",
            "v0.5.5"
          ],
          "database_specific": {
            "source": "https://storage.googleapis.com/cve-osv-conversion/osv-output/CVE-2026-34760.json"
          }
        }
      ],
      "modified": "2026-10-28T02:30:25.126076963Z",
      "provider": "osv",
      "references": [
        "https://github.com/vllm-project/vllm/releases/tag/v0.18.0",
        "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/34xxx/CVE-2026-34760.json",
        "https://github.com/vllm-project/vllm/security/advisories/GHSA-6c4r-fmh3-7rh8",
        "https://nvd.nist.gov/vuln/detail/CVE-2026-34760",
        "https://github.com/vllm-project/vllm/commit/c7f98b4d0a63b32ed939e2b6dfaa8a626e9b46c4",
        "https://github.com/vllm-project/vllm/pull/37058"
      ],
      "provider_metadata": {
        "cwe_ids": [
          "CWE-20"
        ],
        "cna_assigner": "GitHub_M",
        "osv_generated_from": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/34xxx/CVE-2026-34760.json"
      }
    },
    "related_cves": [
      {
        "value": "CVE-2026-34760",
        "evidence": "/id"
      }
    ],
    "security_relevant": true,
    "severity_evidence": "/severity/0/score"
  },
  "source_id": "core-osv",
  "document_id": 491815,
  "published_at": "2026-04-02T18:59:49.638+00:00"
}