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CVE-2022-36005

Estado: ModificadaAlta (7.5)—

TensorFlow is an open source platform for machine learning. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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-2022-36005",
  "cveTags": [],
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          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "none"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2025-04-23T13:58:28.142334Z"
        }
      }
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    "cvssMetricV31": [
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        "type": "Secondary",
        "source": "security-advisories@github.com",
        "cvssData": {
          "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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          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
          "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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  "published": "2022-09-16T23:15:10.937",
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      "url": "https://github.com/tensorflow/tensorflow/commit/f3cf67ac5705f4f04721d15e485e192bb319feed",
      "tags": [
        "Patch",
        "Third Party Advisory"
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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. When `tf.quantization.fake_quant_with_min_max_vars_gradient` receives input `min` or `max` that is nonscalar, it gives a `CHECK` fail that can trigger a denial of service attack. We have patched the issue in GitHub commit f3cf67ac5705f4f04721d15e485e192bb319feed. 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. Cuando \"tf.quantization.fake_quant_with_min_max_vars_gradient\" recibe una entrada \"min\" o \"max\" que no es escalar, da un fallo de \"CHECK\" que puede desencadenar un ataque de denegación de servicio. Hemos parcheado el problema en el commit f3cf67ac5705f4f04721d15e485e192bb319feed 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": "2026-06-17T04:52:43.377",
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