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CVE-2021-29563

Estado: ModificadaMedia (5.5)—

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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-2021-29563",
  "cveTags": [],
  "metrics": {
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        "type": "Primary",
        "source": "nvd@nist.gov",
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          "baseScore": 2.1,
          "accessVector": "LOCAL",
          "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,
        "baseSeverity": "LOW",
        "obtainAllPrivilege": false,
        "exploitabilityScore": 3.9,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
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    "cvssMetricV31": [
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        "type": "Secondary",
        "source": "security-advisories@github.com",
        "cvssData": {
          "scope": "UNCHANGED",
          "version": "3.1",
          "baseScore": 2.5,
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          "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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  "published": "2021-05-14T20:15:13.513",
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    {
      "url": "https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1",
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        "Third Party Advisory"
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      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w",
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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-617"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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;Un atacante puede causar una denegación de servicio al explotar una fallo \"CHECK\" proveniente de la implementación de \"tf.raw_ops.RFFT\".&#xa0;El código propio que opera en una matriz vacía puede desencadenar en una aserción y causará la terminación del programa.&#xa0;La corrección será incluída 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 admitido"
    }
  ],
  "lastModified": "2026-06-17T03:47:55.090",
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      "nodes": [
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