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CVE-2022-35971

Estado: ModificadaAlta (7.5)—

TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

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-2022-35971",
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          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2025-04-23T13:59:30.359821Z"
        }
      }
    ],
    "cvssMetricV31": [
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        "type": "Secondary",
        "source": "security-advisories@github.com",
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          "scope": "UNCHANGED",
          "version": "3.1",
          "baseScore": 5.9,
          "attackVector": "NETWORK",
          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "NONE"
        },
        "impactScore": 3.6,
        "exploitabilityScore": 2.2
      },
      {
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        "source": "nvd@nist.gov",
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          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "NONE"
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        "impactScore": 3.6,
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              "status": "affected",
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              "status": "affected",
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  "published": "2022-09-16T21:15:09.360",
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      "url": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0",
      "tags": [
        "Patch",
        "Third Party Advisory"
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      "tags": [
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      "url": "https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0",
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      "source": "af854a3a-2127-422b-91ae-364da2661108"
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-617"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVars` is given `min` or `max` tensors of a nonzero rank, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de código abierto para el aprendizaje automático. Si a \"FakeQuantWithMinMaxVars\" le son dados tensores \"min\" o \"max\" de un rango distinto de cero, es producido un fallo de \"CHECK\" que puede usarse para desencadenar un ataque de denegación de servicio. Hemos parcheado el problema en el commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0 de GitHub. La corrección será incluida en TensorFlow versión 2.10.0. También seleccionaremos este compromiso en TensorFlow versión 2.9.1, TensorFlow versión 2.8.1, y TensorFlow versión 2.7.2, ya que estos también están afectados y todavía están en el rango admitido. No se presentan mitigaciones conocidas para este problema"
    }
  ],
  "lastModified": "2026-06-17T04:52:37.653",
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