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CVE-2021-37657

Status: ModifiedHigh (7.8)—

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements.

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If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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

Exploitation probability (EPSS)

EPSS (Exploit Prediction Scoring System, FIRST) estimates how likely a vulnerability is to be exploited in the wild within 30 days. It complements CVSS (impact) and CISA KEV (confirmed exploitation).

Affected technologies (1)

Google — Tensorflow

CWEs

References

Raw JSON (NVD)

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{
  "id": "CVE-2021-37657",
  "cveTags": [],
  "metrics": {
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          "accessVector": "LOCAL",
          "vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
          "authentication": "NONE",
          "integrityImpact": "PARTIAL",
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        "obtainAllPrivilege": false,
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          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H",
          "integrityImpact": "HIGH",
          "userInteraction": "NONE",
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          "privilegesRequired": "LOW",
          "confidentialityImpact": "NONE"
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        "impactScore": 5.2,
        "exploitabilityScore": 1.8
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              "version": ">= 2.5.0, < 2.5.1"
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              "version": ">= 2.4.0, < 2.4.3"
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            {
              "status": "affected",
              "version": "< 2.3.4"
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  "published": "2021-08-12T21:15:08.567",
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      "url": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09",
      "tags": [
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        "Third Party Advisory"
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      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m",
      "tags": [
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      "source": "af854a3a-2127-422b-91ae-364da2661108"
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  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-824"
        }
      ]
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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 cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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 causar un comportamiento indefinido por medio de la vinculación de una referencia a un puntero null en todas las operaciones de tipo \"tf.raw_ops.MatrixDiagV*\". La [implementación](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) presenta una comprobación incompleta de que el valor de \"k\" es un tensor válido. Hemos comprobado que este valor es un escalar o un vector, pero no hay ninguna comprobación del número de elementos. Si se trata de un tensor vacío, el código que accede al primer elemento del tensor es erróneo. Hemos parcheado el problema en el commit f2a673bd34f0d64b8e40a551ac78989d16daad09 de GitHub. La corrección será incluida en TensorFlow versión 2.6.0. También seleccionaremos este commit en TensorFlow versión 2.5.1, TensorFlow versión 2.4.3, y TensorFlow versión 2.3.4, ya que estos también están afectados y todavía están en el rango de soporte."
    }
  ],
  "lastModified": "2026-06-17T04:00:55.303",
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