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CVE-2026-42627

Estado: AplazadaMedia (6.2)—

In Arm ArmNN through 2026-03-27, an integer overflow in TensorShape::GetNumElements() in armnn/Tensor.cpp allows a crafted TFLite model file to bypass buffer size validation and trigger a heap-based buffer over-read during model optimization. The overflow occurs when multiplying tensor dimensions using 32-bit unsigned arithmetic without overflow detection, causing GetNumBytes() to return an understated allocation size. During Optimize()->InferOutputShapes(), the BatchToSpaceNdLayer reads beyond the allocated buffer.

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.

ARM — ArmnnAI

CWE

Referencias

JSON original (NVD)

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{
  "id": "CVE-2026-42627",
  "cveTags": [
    {
      "tags": [
        "unsupported-when-assigned"
      ],
      "sourceIdentifier": "cve@mitre.org"
    }
  ],
  "metrics": {
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-42627",
          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2026-05-26T15:16:30.315213Z"
        }
      }
    ],
    "cvssMetricV31": [
      {
        "type": "Secondary",
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "cvssData": {
          "scope": "UNCHANGED",
          "version": "3.1",
          "baseScore": 6.2,
          "attackVector": "LOCAL",
          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "NONE"
        },
        "impactScore": 3.6,
        "exploitabilityScore": 2.5
      }
    ]
  },
  "affected": [
    {
      "source": "cve@mitre.org",
      "affectedData": [
        {
          "vendor": "n/a",
          "product": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ]
    }
  ],
  "published": "2026-05-22T18:16:22.593",
  "references": [
    {
      "url": "https://github.com/ARM-software/armnn/blob/main/src/armnn/Tensor.cpp",
      "source": "cve@mitre.org"
    },
    {
      "url": "https://github.com/ARM-software/armnn/blob/main/src/armnnTfLiteParser/TfLiteParser.cpp",
      "source": "cve@mitre.org"
    }
  ],
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "description": [
        {
          "lang": "en",
          "value": "CWE-190"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "In Arm ArmNN through 2026-03-27, an integer overflow in TensorShape::GetNumElements() in armnn/Tensor.cpp allows a crafted TFLite model file to bypass buffer size validation and trigger a heap-based buffer over-read during model optimization. The overflow occurs when multiplying tensor dimensions using 32-bit unsigned arithmetic without overflow detection, causing GetNumBytes() to return an understated allocation size. During Optimize()->InferOutputShapes(), the BatchToSpaceNdLayer reads beyond the allocated buffer."
    },
    {
      "lang": "es",
      "value": "En Arm ArmNN hasta el 27-03-2026, un desbordamiento de entero en TensorShape::GetNumElements() en armnn/Tensor.cpp permite que un archivo de modelo TFLite manipulado omita la validación del tamaño del búfer y desencadene una lectura excesiva del búfer basada en el montón durante la optimización del modelo. El desbordamiento ocurre al multiplicar las dimensiones del tensor usando aritmética sin signo de 32 bits sin detección de desbordamiento, lo que provoca que GetNumBytes() devuelva un tamaño de asignación subestimado. Durante Optimize()->InferOutputShapes(), la capa BatchToSpaceNdLayer lee más allá del búfer asignado."
    }
  ],
  "lastModified": "2026-07-23T16:10:00.137",
  "sourceIdentifier": "cve@mitre.org"
}