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CVE-2021-37645

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.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor.

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But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, 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-2021-37645",
  "cveTags": [],
  "metrics": {
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        "type": "Primary",
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          "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "authentication": "NONE",
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          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "NONE"
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          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
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  "published": "2021-08-12T21:15:07.887",
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      "url": "https://github.com/tensorflow/tensorflow/commit/96f364a1ca3009f98980021c4b32be5fdcca33a1",
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-681"
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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.QuantizeAndDequantizeV4Grad` is vulnerable to an integer overflow issue caused by converting a signed integer value to an unsigned one and then allocating memory based on this value. The [implementation](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) uses the `axis` value as the size argument to `absl::InlinedVector` constructor. But, the constructor uses an unsigned type for the argument, so the implicit conversion transforms the negative value to a large integer. We have patched the issue in GitHub commit 96f364a1ca3009f98980021c4b32be5fdcca33a1. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, and TensorFlow 2.4.3, 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, la implementación \"tf.raw_ops.QuantizeAndDequantizeV4Grad\" es vulnerable a un problema de desbordamiento de enteros causado al convertir un valor entero con signo a uno sin signo y la posterior asignación de memoria basada en este valor. La [implementación](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L126) usa el valor de \"axis\" como argumento del tamaño del constructor de \"absl::InlinedVector\". Pero, el constructor usa un tipo sin signo para el argumento, por lo que la conversión implícita transforma el valor negativo en un entero grande. Hemos parcheado el problema en el commit 96f364a1ca3009f98980021c4b32be5fdcca33a1 de GitHub. La corrección será incluida en TensorFlow versión 2.6.0. También seleccionaremos este commit en TensorFlow 2.5.1, y TensorFlow 2.4.3, ya que estos también están afectados y todavía en el rango de soporte."
    }
  ],
  "lastModified": "2026-06-17T04:00:53.767",
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