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CVE-2022-29212

Estado: ModificadaMedia (5.5)—

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch 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-2022-29212",
  "cveTags": [],
  "metrics": {
    "ssvcV203": [
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        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2022-29212",
          "role": "CISA Coordinator",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "version": "2.0.3",
          "timestamp": "2025-04-22T15:46:27.755578Z"
        }
      }
    ],
    "cvssMetricV2": [
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        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "version": "2.0",
          "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"
        },
        "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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        "cvssData": {
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          "version": "3.1",
          "baseScore": 5.5,
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          "baseSeverity": "MEDIUM",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "LOW",
          "confidentialityImpact": "NONE"
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        "impactScore": 3.6,
        "exploitabilityScore": 1.8
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          "integrityImpact": "NONE",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
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          "confidentialityImpact": "NONE"
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        "impactScore": 3.6,
        "exploitabilityScore": 1.8
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  "published": "2022-05-21T00:15:11.720",
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-20"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue."
    },
    {
      "lang": "es",
      "value": "TensorFlow es una plataforma de código abierto para el aprendizaje automático. En versiones anteriores a 2.9.0, 2.8.1, 2.7.2 y 2.6.4, algunos modelos TFLite creados con el convertidor de modelos TFLite eran bloqueados cuando eran cargados en el intérprete TFLite. El culpable es que durante la cuantificación la escala de los valores podía ser mayor que 1 pero el código siempre asumía una escala de subunidades. Así, como el código llamaba a \"QuantizeMultiplierSmallerThanOneExp\", la aserción \"TFLITE_CHECK_LT\" era disparada y abortaba el proceso. Las versiones 2.9.0, 2.8.1, 2.7.2 y 2.6.4 contienen un parche para este problema"
    }
  ],
  "lastModified": "2026-06-17T04:39:50.233",
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