fkie_cve-2020-15201
Vulnerability from fkie_nvd
Published
2020-09-25 19:15
Modified
2024-11-21 05:05
Severity ?
4.8 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
4.8 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N
Summary
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.
References
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02Patch, Third Party Advisory
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4Exploit, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/commit/3cbb917b4714766030b28eba9fb41bb97ce9ee02Patch, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/security/advisories/GHSA-p5f8-gfw5-33w4Exploit, Third Party Advisory
Impacted products
Vendor Product Version
google tensorflow 2.3.0


To clipboard 

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              "matchCriteriaId": "D0A7B69E-9388-48F0-B744-49453EBAF5D5",
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  "cveTags": [],
  "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 versi\u00f3n 2.3.1, la implementaci\u00f3n de \"RaggedCountSparseOutput\" no comprueba que los argumentos de entrada formen un tensor irregular v\u00e1lido.\u0026#xa0;En particular, no existe comprobaci\u00f3n de que los valores en el tensor \"splits\" generen una partici\u00f3n v\u00e1lida del tensor \"values\".\u0026#xa0;Por lo tanto, el c\u00f3digo es propenso a un desbordamiento del b\u00fafer de la pila.\u0026#xa0;Si \"split_values\" no termina con un valor de al menos \"num_values\", entonces la condici\u00f3n de bucle \"while\" activar\u00e1 una lectura fuera de los l\u00edmites de \"split_values\" una vez que \"batch_idx\" se incremente demasiado.\u0026#xa0;El problema es parcheado en el commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 y es publicado en TensorFlow versi\u00f3n 2.3.1"
    }
  ],
  "id": "CVE-2020-15201",
  "lastModified": "2024-11-21T05:05:04.303",
  "metrics": {
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          "baseScore": 4.8,
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          "confidentialityImpact": "LOW",
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          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:N",
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        "source": "nvd@nist.gov",
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  "published": "2020-09-25T19:15:15.353",
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  "vulnStatus": "Modified",
  "weaknesses": [
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          "value": "CWE-20"
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      "source": "nvd@nist.gov",
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    }
  ]
}


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