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CVE-2021-37677

Estado: ModificadaMedia (5.5)—

TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions.

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However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

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-2021-37677",
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  "published": "2021-08-12T23:15:08.090",
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  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de código abierto de extremo a extremo para el aprendizaje automático.&#xa0;En las versiones afectadas, el código de inferencia de forma para \"tf.raw_ops.Dequantize\" presenta una vulnerabilidad que podría desencadenar una denegación de servicio por medio de un error de seguridad si un atacante proporciona argumentos no válidos.&#xa0;La inferencia de forma [implementación] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) usa \"axis\" para seleccionar entre dos valores diferentes para \"minmax_rank \"que luego se usa para recuperar las dimensiones del tensor.&#xa0;Sin embargo, el código asume que el \"axis\" puede ser \"-1\" o un valor mayor que \"-1\", sin comprobación para los otros valores.&#xa0;Hemos solucionado el problema en GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764.&#xa0;La corrección será incluida en TensorFlow versión 2.6.0.&#xa0;También seleccionaremos este commit en TensorFlow versión 2.5."
    }
  ],
  "lastModified": "2026-06-17T04:00:57.803",
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