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CVE-2020-15208

Estado: ModificadaCrítica (9.8)—

In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

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).

🎯 Técnicas ATT&CK

Cómo se explota esta vulnerabilidad y qué consigue el atacante, en el lenguaje de MITRE ATT&CK.

Fuente: mapeo oficial MITRE CTID (CVE → ATT&CK).

🛡️ Mitigaciones ATT&CK que cubren estas técnicas

Application Developer GuidanceUser Account ManagementRestrict File and Directory PermissionsRestrict Registry PermissionsFilter Network TrafficExecution Prevention

Tecnologías afectadas (2)

Google — TensorflowOpensuse — Leap

CWE

Referencias

JSON original (NVD)

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  "id": "CVE-2020-15208",
  "cveTags": [],
  "metrics": {
    "cvssMetricV2": [
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        "type": "Primary",
        "source": "nvd@nist.gov",
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          "version": "2.0",
          "baseScore": 7.5,
          "accessVector": "NETWORK",
          "vectorString": "AV:N/AC:L/Au:N/C:P/I:P/A:P",
          "authentication": "NONE",
          "integrityImpact": "PARTIAL",
          "accessComplexity": "LOW",
          "availabilityImpact": "PARTIAL",
          "confidentialityImpact": "PARTIAL"
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        "acInsufInfo": false,
        "impactScore": 6.4,
        "baseSeverity": "HIGH",
        "obtainAllPrivilege": false,
        "exploitabilityScore": 10,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
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          "integrityImpact": "HIGH",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "NONE",
          "privilegesRequired": "NONE",
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  "published": "2020-09-25T19:15:16.103",
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  "vulnStatus": "Modified",
  "weaknesses": [
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      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-125"
        },
        {
          "lang": "en",
          "value": "CWE-787"
        }
      ]
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  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "In tensorflow-lite before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, when determining the common dimension size of two tensors, TFLite uses a `DCHECK` which is no-op outside of debug compilation modes. Since the function always returns the dimension of the first tensor, malicious attackers can craft cases where this is larger than that of the second tensor. In turn, this would result in reads/writes outside of bounds since the interpreter will wrongly assume that there is enough data in both tensors. The issue is patched in commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1."
    },
    {
      "lang": "es",
      "value": "En tensorflow-lite versiones anteriores a 1.15.4, 2.0.3, 2.1.2, 2.2.1 y 2.3.1, al determinar el tamaño de dimensión común de dos tensores, TFLite usa un \"DCHECK\" que no es operativo fuera de los modos de compilación de depuración.&#xa0;Dado que la función siempre devuelve la dimensión del primer tensor, los atacantes maliciosos pueden crear casos en los que este sea mayor que el del segundo tensor.&#xa0;A su vez, esto resultaría en lecturas y escrituras fuera de límites, ya que el intérprete asumirá incorrectamente que existen suficientes datos en ambos tensores.&#xa0;El problema es parcheado en el commit 8ee24e7949a203d234489f9da2c5bf45a7d5157d, y es publicado en TensorFlow versiones 1.15.4, 2.0.3, 2.1.2, 2.2.1 o 2.3.1"
    }
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  "lastModified": "2026-06-17T02:56:16.190",
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