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CVE-2021-29522

Estado: ModificadaMedia (5.5)—

TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error.

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The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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-2021-29522",
  "cveTags": [],
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        "source": "nvd@nist.gov",
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          "vectorString": "AV:L/AC:L/Au:N/C:N/I:N/A:P",
          "authentication": "NONE",
          "integrityImpact": "NONE",
          "accessComplexity": "LOW",
          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "NONE"
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        "acInsufInfo": false,
        "impactScore": 2.9,
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        "obtainAllPrivilege": false,
        "exploitabilityScore": 3.9,
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          "version": "3.1",
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          "attackVector": "LOCAL",
          "baseSeverity": "LOW",
          "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "LOW",
          "privilegesRequired": "LOW",
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        "impactScore": 1.4,
        "exploitabilityScore": 1
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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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  "published": "2021-05-14T20:15:11.617",
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      "url": "https://github.com/tensorflow/tensorflow/commit/311403edbc9816df80274bd1ea8b3c0c0f22c3fa",
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      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c968-pq7h-7fxv",
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "source": "security-advisories@github.com",
      "description": [
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          "lang": "en",
          "value": "CWE-369"
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  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. The `tf.raw_ops.Conv3DBackprop*` operations fail to validate that the input tensors are not empty. In turn, this would result in a division by 0. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) does not check that the divisor used in computing the shard size is not zero. Thus, if attacker controls the input sizes, they can trigger a denial of service via a division by zero error. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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;Las operaciones en \"tf.raw_ops.Conv3DBackprop*\" no comprueban que los tensores de entrada no estén vacíos.&#xa0;A su vez, esto resultaría en una división por 0. Esto es debido a que la implementación (https://github.com/tensorflow/tensorflow/blob/a91bb59769f19146d5a0c20060244378e878f140/tensorflow/core/kernels/conv_grad_ops_3d.cc#L430-L450) no comprueba que el divisor usado para calcular el tamaño del fragmento no es cero.&#xa0;Por lo tanto, si el atacante controla los tamaños de entrada, puede desencadenar una denegación de servicio por medio de una error de división por cero.&#xa0;La corrección será incluida en TensorFlow versión 2.5.0.&#xa0;También seleccionaremos este commit en TensorFlow versión 2.4.2, TensorFlow versión 2.3.3, TensorFlow versión 2.2.3 y TensorFlow versión 2.1.4, ya que estos también están afectados y aún están en el rango compatible"
    }
  ],
  "lastModified": "2026-06-17T03:47:49.753",
  "configurations": [
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