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CVE-2020-15201

Estado: ModificadaMedia (4.8)—

In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

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)

CWE

Referencias

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{
  "id": "CVE-2020-15201",
  "cveTags": [],
  "metrics": {
    "cvssMetricV2": [
      {
        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "version": "2.0",
          "baseScore": 6.8,
          "accessVector": "NETWORK",
          "vectorString": "AV:N/AC:M/Au:N/C:P/I:P/A:P",
          "authentication": "NONE",
          "integrityImpact": "PARTIAL",
          "accessComplexity": "MEDIUM",
          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "PARTIAL"
        },
        "acInsufInfo": false,
        "impactScore": 6.4,
        "baseSeverity": "MEDIUM",
        "obtainAllPrivilege": false,
        "exploitabilityScore": 8.6,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
      }
    ],
    "cvssMetricV31": [
      {
        "type": "Secondary",
        "source": "security-advisories@github.com",
        "cvssData": {
          "scope": "UNCHANGED",
          "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:L/I:L/A:N",
          "integrityImpact": "LOW",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "NONE",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "LOW"
        },
        "impactScore": 2.5,
        "exploitabilityScore": 2.2
      },
      {
        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "scope": "UNCHANGED",
          "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:L/I:L/A:N",
          "integrityImpact": "LOW",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "NONE",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "LOW"
        },
        "impactScore": 2.5,
        "exploitabilityScore": 2.2
      }
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  },
  "affected": [
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      "source": "security-advisories@github.com",
      "affectedData": [
        {
          "vendor": "tensorflow",
          "product": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": "= 2.3.0"
            }
          ]
        }
      ]
    }
  ],
  "published": "2020-09-25T19:15:15.353",
  "references": [
    {
      "url": "https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02",
      "tags": [
        "Patch",
        "Third Party Advisory"
      ],
      "source": "security-advisories@github.com"
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    {
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1",
      "tags": [
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    {
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      "tags": [
        "Exploit",
        "Third Party Advisory"
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      "source": "security-advisories@github.com"
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      "url": "https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02",
      "tags": [
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      "source": "af854a3a-2127-422b-91ae-364da2661108"
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    {
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1",
      "tags": [
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
    },
    {
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      "tags": [
        "Exploit",
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
    }
  ],
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-20"
        },
        {
          "lang": "en",
          "value": "CWE-122"
        }
      ]
    },
    {
      "type": "Primary",
      "source": "nvd@nist.gov",
      "description": [
        {
          "lang": "en",
          "value": "CWE-787"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "In Tensorflow before version 2.3.1, the `RaggedCountSparseOutput` implementation does not validate that the input arguments form a valid ragged tensor. In particular, there is no validation that the values in the `splits` tensor generate a valid partitioning of the `values` tensor. Hence, the code is prone to heap buffer overflow. If `split_values` does not end with a value at least `num_values` then the `while` loop condition will trigger a read outside of the bounds of `split_values` once `batch_idx` grows too large. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1."
    },
    {
      "lang": "es",
      "value": "En Tensorflow anteriores a la versión 2.3.1, la implementación de \"RaggedCountSparseOutput\" no comprueba que los argumentos de entrada formen un tensor irregular válido. En particular, no existe comprobación de que los valores en el tensor \"splits\" generen una partición válida del tensor \"values\". Por lo tanto, el código es propenso a un desbordamiento del búfer de la pila. Si \"split_values\" no termina con un valor de al menos \"num_values\", entonces la condición de bucle \"while\" activará una lectura fuera de los límites de \"split_values\" una vez que \"batch_idx\" se incremente demasiado. El problema es parcheado en el commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 y es publicado en TensorFlow versión 2.3.1"
    }
  ],
  "lastModified": "2026-06-17T02:56:15.237",
  "configurations": [
    {
      "nodes": [
        {
          "negate": false,
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:*",
              "vulnerable": true,
              "matchCriteriaId": "D0A7B69E-9388-48F0-B744-49453EBAF5D5"
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          "operator": "OR"
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  "sourceIdentifier": "security-advisories@github.com"
}