FKIE_CVE-2026-42627

Vulnerability from fkie_nvd - Published: 2026-05-22 18:16 - Updated: 2026-06-17 10:48
Severity
6.2 (Medium) - CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Summary
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.
References
cve@mitre.orghttps://github.com/ARM-software/armnn/blob/main/src/armnn/Tensor.cpp
cve@mitre.orghttps://github.com/ARM-software/armnn/blob/main/src/armnnTfLiteParser/TfLiteParser.cpp
Impacted products
Vendor Product Version
To clipboard 

{
  "affected": [
    {
      "affectedData": [
        {
          "product": "n/a",
          "vendor": "n/a",
          "versions": [
            {
              "status": "affected",
              "version": "n/a"
            }
          ]
        }
      ],
      "source": "cve@mitre.org"
    }
  ],
  "cveTags": [
    {
      "sourceIdentifier": "cve@mitre.org",
      "tags": [
        "unsupported-when-assigned"
      ]
    }
  ],
  "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()-\u003eInferOutputShapes(), the BatchToSpaceNdLayer reads beyond the allocated buffer."
    }
  ],
  "id": "CVE-2026-42627",
  "lastModified": "2026-06-17T10:48:11.943",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "HIGH",
          "baseScore": 6.2,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "version": "3.1"
        },
        "exploitabilityScore": 2.5,
        "impactScore": 3.6,
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-42627",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-05-26T15:16:30.315213Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-05-22T18:16:22.593",
  "references": [
    {
      "source": "cve@mitre.org",
      "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"
    }
  ],
  "sourceIdentifier": "cve@mitre.org",
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-190"
        }
      ],
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "type": "Secondary"
    }
  ]
}



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