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CVE-2021-37640

Estado: ModificadaMedia (5.5)—

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) calls the reshaping functor whenever there is at least an index in the input but does not check that shape of the input or the target shape have both a non-zero number of elements.

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The [reshape functor](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) blindly divides by the dimensions of the target shape. Hence, if this is not checked, code will result in a division by 0. We have patched the issue in GitHub commit 4923de56ec94fff7770df259ab7f2288a74feb41. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1 as this is the other affected version.

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)

Google — Tensorflow

CWE

Referencias

JSON original (NVD)

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  "id": "CVE-2021-37640",
  "cveTags": [],
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          "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "authentication": "NONE",
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          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
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          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
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  "published": "2021-08-12T18:15:10.490",
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  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of `tf.raw_ops.SparseReshape` can be made to trigger an integral division by 0 exception. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) calls the reshaping functor whenever there is at least an index in the input but does not check that shape of the input or the target shape have both a non-zero number of elements. The [reshape functor](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) blindly divides by the dimensions of the target shape. Hence, if this is not checked, code will result in a division by 0. We have patched the issue in GitHub commit 4923de56ec94fff7770df259ab7f2288a74feb41. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1 as this is the other affected version."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático. En las versiones afectadas se puede hacer que la implementación \"tf.raw_ops.SparseReshape\" lance una excepción de división integral por 0. La [implementación](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L176-L181) llama al functor de remodelación siempre que haya al menos un índice en la entrada, pero no comprueba que la forma de la entrada o la forma objetivo tengan ambas un número de elementos distinto de cero. El [functor de remodelación](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/reshape_util.cc#L40-L78) divide ciegamente por las dimensiones de la forma objetivo. Por lo tanto, si esto no es comprobado, el código dará lugar a una división por 0. Hemos parcheado el problema en el commit 4923de56ec94fff7770df259ab7f2288a74feb41 de GitHub. La corrección se incluirá en TensorFlow versión 2.6.0. También se incluirá este commit en TensorFlow versión 2.5.1 ya que es la otra versión afectada."
    }
  ],
  "lastModified": "2026-06-17T04:00:53.147",
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