nvd-json-data-feeds/CVE-2021/CVE-2021-411xx/CVE-2021-41196.json

{
  "id": "CVE-2021-41196",
  "sourceIdentifier": "security-advisories@github.com",
  "published": "2021-11-05T20:15:07.780",
  "lastModified": "2021-11-09T13:56:01.853",
  "vulnStatus": "Analyzed",
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de c\u00f3digo abierto para el aprendizaje autom\u00e1tico. En las versiones afectadas, las capas de pooling de Keras pueden provocar un segfault si el tama\u00f1o del pool es 0 o si una dimensi\u00f3n es negativa. Esto es debido a la implementaci\u00f3n de TensorFlow de las operaciones de pooling donde no es comprobado que los valores de la ventana deslizante sean estrictamente positivos. La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.7.0. Tambi\u00e9n ser\u00e1 incluida este commit en TensorFlow versi\u00f3n 2.6.1, TensorFlow versi\u00f3n 2.5.2, y TensorFlow versi\u00f3n 2.4.4, ya que estos tambi\u00e9n est\u00e1n afectados y todav\u00eda est\u00e1n en el rango admitido"
    }
  ],
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          "attackVector": "LOCAL",
          "attackComplexity": "LOW",
          "privilegesRequired": "LOW",
          "userInteraction": "NONE",
          "scope": "UNCHANGED",
          "confidentialityImpact": "NONE",
          "integrityImpact": "NONE",
          "availabilityImpact": "HIGH",
          "baseScore": 5.5,
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      "url": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b",
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