{
  "affected": [
    {
      "ranges": [
        {
          "database_specific": {
            "extracted_events": [
              {
                "introduced": "0"
              },
              {
                "fixed": "0.28.0"
              }
            ],
            "source": [
              "AFFECTED_FIELD",
              "REFERENCES"
            ]
          },
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "283893c72292ede38d277e3cd2b9b64c3e4f1dda"
            },
            {
              "fixed": "ba22152096b2484faa3579624a253d54804d876d"
            }
          ],
          "repo": "https://github.com/vllm-project/vllm",
          "type": "GIT"
        }
      ]
    }
  ],
  "aliases": [
    "GHSA-8pw2-6jv3-mj5j"
  ],
  "database_specific": {
    "cna_assigner": "GitHub_M",
    "cwe_ids": [
      "CWE-400",
      "CWE-770"
    ],
    "osv_generated_from": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/69xxx/CVE-2026-69147.json"
  },
  "details": "vLLM is an inference and serving engine for large language models. Prior to 0.28.0, request bodies for Chat Completions and Responses can set media_io_kwargs.video.video_backend to pynvvideocodec, and MediaConnector.fetch_video forwards that choice to VideoMediaIO even when startup configuration selected a software decoder. The engine's _reserve_mm_ipc_gpu_memory logic budgets decoder memory only from static configuration, so the request-selected VIDEO_LOADER_REGISTRY backend can create a CUDA context, decoder surfaces, and decoded-frame allocations that were not removed from the engine's KV-cache budget. An attacker able to submit video requests to a video-capable GPU deployment with PyNvVideoCodec installed can exhaust shared GPU memory, causing request failures, worker crashes, or denial of service. The first release containing the fix is version 0.28.0.",
  "id": "CVE-2026-69147",
  "modified": "2026-09-18T03:30:26.044636951Z",
  "published": "2026-09-16T17:49:20.427Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/69xxx/CVE-2026-69147.json"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-8pw2-6jv3-mj5j"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-69147"
    },
    {
      "type": "FIX",
      "url": "https://github.com/vllm-project/vllm/commit/283893c72292ede38d277e3cd2b9b64c3e4f1dda"
    },
    {
      "type": "FIX",
      "url": "https://github.com/vllm-project/vllm/commit/ba22152096b2484faa3579624a253d54804d876d"
    },
    {
      "type": "FIX",
      "url": "https://github.com/vllm-project/vllm/pull/47259"
    }
  ],
  "schema_version": "1.9.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "vLLM: Request-selected PyNvVideoCodec GPU decode bypasses static VRAM reservation"
}