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CVE-2026-12491

Estado: Pendiente de análisisMedia (4.8)—

A flaw was found in vLLM, an open-source library for large language model inference. This vulnerability arises from improper handling of image metadata, specifically EXIF orientation and PNG transparency (tRNS) data, during image processing. When images are converted to RGB, transparency information may be implicitly discarded or remapped, leading to unexpected rendering of transparent pixels and distortion of input content. This can result in the model misinterpreting image content, potentially affecting the integrity of processed data.

CVSS

Probabilidad de explotación (EPSS)

EPSS (Exploit Prediction Scoring System, de FIRST) estima la probabilidad de que una vulnerabilidad sea explotada en 30 días. Complementa a CVSS (impacto) y a CISA KEV (explotación confirmada).

Tecnologías afectadas (1)

⚠ Inferidas por IA a partir de la descripción — NVD aún no ha analizado esta CVE; no son CPE verificados.

Vllm — VllmAI

CWE

Referencias

JSON original (NVD)

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  "id": "CVE-2026-12491",
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        "ssvcData": {
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          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2026-06-17T14:47:47.319727Z"
        }
      }
    ],
    "cvssMetricV31": [
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        "source": "secalert@redhat.com",
        "cvssData": {
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          "version": "3.1",
          "baseScore": 4.8,
          "attackVector": "NETWORK",
          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:L/A:L",
          "integrityImpact": "LOW",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "LOW",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "NONE"
        },
        "impactScore": 2.5,
        "exploitabilityScore": 2.2
      }
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  "published": "2026-06-17T13:20:04.323",
  "references": [
    {
      "url": "https://access.redhat.com/security/cve/CVE-2026-12491",
      "source": "secalert@redhat.com"
    },
    {
      "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2489786",
      "source": "secalert@redhat.com"
    }
  ],
  "vulnStatus": "Awaiting Analysis",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "secalert@redhat.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-115"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "A flaw was found in vLLM, an open-source library for large language model inference. This vulnerability arises from improper handling of image metadata, specifically EXIF orientation and PNG transparency (tRNS) data, during image processing. When images are converted to RGB, transparency information may be implicitly discarded or remapped, leading to unexpected rendering of transparent pixels and distortion of input content. This can result in the model misinterpreting image content, potentially affecting the integrity of processed data."
    }
  ],
  "lastModified": "2026-07-07T09:16:29.103",
  "sourceIdentifier": "secalert@redhat.com"
}