{
  "configurations": [
    {
      "nodes": [
        {
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:*",
              "matchCriteriaId": "19C6D0C7-632B-4AA7-97E5-CCF21EC350E5",
              "versionEndExcluding": "0.8.5",
              "versionStartIncluding": "0.8.0",
              "vulnerable": true
            }
          ],
          "negate": false,
          "operator": "OR"
        }
      ]
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.8.0 and prior to 0.8.5 are affected by a critical performance vulnerability in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens (e.g., \u003c|audio_|\u003e, \u003c|image_|\u003e) with repeated tokens based on precomputed lengths. Due to \u200b\u200binefficient list concatenation operations\u200b\u200b, the algorithm exhibits \u200b\u200bquadratic time complexity (O(n\u00b2))\u200b\u200b, allowing malicious actors to trigger resource exhaustion via specially crafted inputs. This issue has been patched in version 0.8.5."
    },
    {
      "lang": "es",
      "value": "vLLM es un motor de inferencia y servicio de alto rendimiento y eficiente en memoria para LLM. Las versiones a partir de la 0.8.0 y anteriores a la 0.8.5 se ven afectadas por una vulnerabilidad cr\u00edtica de rendimiento en la l\u00f3gica de preprocesamiento de entrada del tokenizador multimodal. El c\u00f3digo reemplaza din\u00e1micamente los tokens de marcador de posici\u00f3n (p. ej., \u0026lt;|audio_|\u0026gt;, \u0026lt;|image_|\u0026gt;) con tokens repetidos basados ??en longitudes precalculadas. Debido a las ineficientes operaciones de concatenaci\u00f3n de listas, el algoritmo presenta una complejidad temporal cuadr\u00e1tica (O(n\u00b2)), lo que permite a los actores maliciosos activar el agotamiento de recursos mediante entradas especialmente manipuladas. Este problema se ha corregido en la versi\u00f3n 0.8.5."
    }
  ],
  "id": "CVE-2025-46560",
  "lastModified": "2025-05-28T19:15:56.887",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 6.5,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 2.8,
        "impactScore": 3.6,
        "source": "security-advisories@github.com",
        "type": "Secondary"
      },
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "NETWORK",
          "availabilityImpact": "HIGH",
          "baseScore": 7.5,
          "baseSeverity": "HIGH",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 3.9,
        "impactScore": 3.6,
        "source": "nvd@nist.gov",
        "type": "Primary"
      }
    ]
  },
  "published": "2025-04-30T01:15:52.097",
  "references": [
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Product"
      ],
      "url": "https://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197"
    },
    {
      "source": "security-advisories@github.com",
      "tags": [
        "Exploit",
        "Vendor Advisory"
      ],
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "tags": [
        "Exploit",
        "Vendor Advisory"
      ],
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg"
    }
  ],
  "sourceIdentifier": "security-advisories@github.com",
  "vulnStatus": "Analyzed",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-1333"
        }
      ],
      "source": "security-advisories@github.com",
      "type": "Secondary"
    }
  ]
}

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "vllm"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0.8.0"
            },
            {
              "fixed": "0.8.5"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2025-46560"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-1333"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2025-04-29T16:43:10Z",
    "nvd_published_at": "2025-04-30T01:15:52Z",
    "severity": "MODERATE"
  },
  "details": "### Summary\nA critical performance vulnerability has been identified in the input preprocessing logic of the multimodal tokenizer. The code dynamically replaces placeholder tokens (e.g., \u003c|audio_*|\u003e, \u003c|image_*|\u003e) with repeated tokens based on precomputed lengths. Due to \u200b\u200binefficient list concatenation operations\u200b\u200b, the algorithm exhibits \u200b\u200bquadratic time complexity (O(n\u00b2))\u200b\u200b, allowing malicious actors to trigger resource exhaustion via specially crafted inputs.\n\n### Details\n\u200b\u200bAffected Component\u200b\u200b: input_processor_for_phi4mm function.\nhttps://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197\n\nThe code modifies the input_ids list in-place using input_ids = input_ids[:i] + tokens + input_ids[i+1:]. Each concatenation operation copies the entire list, leading to O(n) operations per replacement. For k placeholders expanding to m tokens, total time becomes O(kmn), approximating O(n\u00b2) in worst-case scenarios.\n\n### PoC\nTest data demonstrates exponential time growth:\n```python\ntest_cases = [100, 200, 400, 800, 1600, 3200, 6400]\nrun_times = [0.002, 0.007, 0.028, 0.136, 0.616, 2.707, 11.854]  # seconds\n```\nDoubling input size increases runtime by ~4x (consistent with O(n\u00b2)).\n\n### Impact\n\u200b\u200bDenial-of-Service (DoS):\u200b\u200b An attacker could submit inputs with many placeholders (e.g., 10,000 \u003c|audio_1|\u003e tokens), causing CPU/memory exhaustion.\nExample: 10,000 placeholders \u2192 ~100 million operations.\n\n\n### Remediation Recommendations\u200b\nPrecompute all placeholder positions and expansion lengths upfront.\nReplace dynamic list concatenation with a single preallocated array.\n```python\n# Pseudocode for O(n) solution\nnew_input_ids = []\nfor token in input_ids:\n    if token is placeholder:\n        new_input_ids.extend([token] * precomputed_length)\n    else:\n        new_input_ids.append(token)\n```",
  "id": "GHSA-vc6m-hm49-g9qg",
  "modified": "2025-04-30T17:27:16Z",
  "published": "2025-04-29T16:43:10Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/security/advisories/GHSA-vc6m-hm49-g9qg"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2025-46560"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/vllm-project/vllm"
    },
    {
      "type": "WEB",
      "url": "https://github.com/vllm-project/vllm/blob/8cac35ba435906fb7eb07e44fe1a8c26e8744f4e/vllm/model_executor/models/phi4mm.py#L1182-L1197"
    }
  ],
  "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"
    }
  ],
  "summary": "phi4mm: Quadratic Time Complexity in Input Token Processing\u200b leads to denial of service"
}