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CVE-2021-37654

Estado: ModificadaAlta (7.1)—

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a `CHECK`-fail in debug builds of TensorFlow using `tf.raw_ops.ResourceGather` or a read from outside the bounds of heap allocated data in the same API in a release build. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) does not check that the `batch_dims` value that the user supplies is less than the rank of the input tensor.

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Since the implementation uses several for loops over the dimensions of `tensor`, this results in reading data from outside the bounds of heap allocated buffer backing the tensor. We have patched the issue in GitHub commit bc9c546ce7015c57c2f15c168b3d9201de679a1d. 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-2021-37654",
  "cveTags": [],
  "metrics": {
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        "type": "Primary",
        "source": "nvd@nist.gov",
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          "accessVector": "LOCAL",
          "vectorString": "AV:L/AC:L/Au:N/C:P/I:N/A:P",
          "authentication": "NONE",
          "integrityImpact": "NONE",
          "accessComplexity": "LOW",
          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "PARTIAL"
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          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H",
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        "exploitabilityScore": 1.8
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  "published": "2021-08-12T21:15:08.267",
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-125"
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  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a crash via a `CHECK`-fail in debug builds of TensorFlow using `tf.raw_ops.ResourceGather` or a read from outside the bounds of heap allocated data in the same API in a release build. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) does not check that the `batch_dims` value that the user supplies is less than the rank of the input tensor. Since the implementation uses several for loops over the dimensions of `tensor`, this results in reading data from outside the bounds of heap allocated buffer backing the tensor. We have patched the issue in GitHub commit bc9c546ce7015c57c2f15c168b3d9201de679a1d. 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. En las versiones afectadas, un atacante puede desencadenar un bloqueo por medio de un parámetro \"CHECK\" en las versiones de depuración de TensorFlow usando \"tf.raw_ops.ResourceGather\" o una lectura desde fuera de límites de los datos asignados a la pila en la misma API en una versión de lanzamiento. La [implementación](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/resource_variable_ops.cc#L660-L668) no comprueba que el valor de \"batch_dims\" que el usuario proporciona es menor que el rango del tensor de entrada. Dado que la implementación usa varios bucles for sobre las dimensiones de \"tensor\", esto resulta en la lectura de datos desde fuera de límites del búfer asignado en el heap que respalda el tensor. Hemos parcheado el problema en el commit bc9c546ce7015c57c2f15c168b3d9201de679a1d de GitHub. La corrección será incluida en TensorFlow versión 2.6.0. También seleccionaremos este commit en TensorFlow 2.5.1, TensorFlow 2.4.3 y TensorFlow 2.3.4, ya que estos también están afectados y todavía están en el rango de soporte."
    }
  ],
  "lastModified": "2026-06-17T04:00:54.923",
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