« Volver al listado

CVE-2020-15212

Estado: ModificadaAlta (8.6)—

In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits.

Leer descripción completaMostrar menos

The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.

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)

Mostrar
{
  "id": "CVE-2020-15212",
  "cveTags": [],
  "metrics": {
    "cvssMetricV2": [
      {
        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "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"
        },
        "acInsufInfo": false,
        "impactScore": 6.4,
        "baseSeverity": "HIGH",
        "obtainAllPrivilege": false,
        "exploitabilityScore": 10,
        "obtainUserPrivilege": false,
        "obtainOtherPrivilege": false,
        "userInteractionRequired": false
      }
    ],
    "cvssMetricV31": [
      {
        "type": "Secondary",
        "source": "security-advisories@github.com",
        "cvssData": {
          "scope": "CHANGED",
          "version": "3.1",
          "baseScore": 8.1,
          "attackVector": "NETWORK",
          "baseSeverity": "HIGH",
          "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:L/I:L/A:H",
          "integrityImpact": "LOW",
          "userInteraction": "NONE",
          "attackComplexity": "HIGH",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "LOW"
        },
        "impactScore": 5.3,
        "exploitabilityScore": 2.2
      },
      {
        "type": "Primary",
        "source": "nvd@nist.gov",
        "cvssData": {
          "scope": "UNCHANGED",
          "version": "3.1",
          "baseScore": 8.6,
          "attackVector": "NETWORK",
          "baseSeverity": "HIGH",
          "vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H",
          "integrityImpact": "LOW",
          "userInteraction": "NONE",
          "attackComplexity": "LOW",
          "availabilityImpact": "HIGH",
          "privilegesRequired": "NONE",
          "confidentialityImpact": "LOW"
        },
        "impactScore": 4.7,
        "exploitabilityScore": 3.9
      }
    ]
  },
  "affected": [
    {
      "source": "security-advisories@github.com",
      "affectedData": [
        {
          "vendor": "tensorflow",
          "product": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": ">= 2.2.0, < 2.2.1"
            },
            {
              "status": "affected",
              "version": ">= 2.3.0, < 2.3.1"
            }
          ]
        }
      ]
    }
  ],
  "published": "2020-09-25T19:15:16.510",
  "references": [
    {
      "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a",
      "tags": [
        "Patch",
        "Third Party Advisory"
      ],
      "source": "security-advisories@github.com"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1",
      "tags": [
        "Third Party Advisory"
      ],
      "source": "security-advisories@github.com"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq",
      "tags": [
        "Exploit",
        "Patch",
        "Third Party Advisory"
      ],
      "source": "security-advisories@github.com"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a",
      "tags": [
        "Patch",
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1",
      "tags": [
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
    },
    {
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hx2x-85gr-wrpq",
      "tags": [
        "Exploit",
        "Patch",
        "Third Party Advisory"
      ],
      "source": "af854a3a-2127-422b-91ae-364da2661108"
    }
  ],
  "vulnStatus": "Modified",
  "weaknesses": [
    {
      "type": "Secondary",
      "source": "security-advisories@github.com",
      "description": [
        {
          "lang": "en",
          "value": "CWE-787"
        }
      ]
    },
    {
      "type": "Primary",
      "source": "nvd@nist.gov",
      "description": [
        {
          "lang": "en",
          "value": "CWE-787"
        }
      ]
    }
  ],
  "descriptions": [
    {
      "lang": "en",
      "value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger writes outside of bounds of heap allocated buffers by inserting negative elements in the segment ids tensor. Users having access to `segment_ids_data` can alter `output_index` and then write to outside of `output_data` buffer. This might result in a segmentation fault but it can also be used to further corrupt the memory and can be chained with other vulnerabilities to create more advanced exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are all positive, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code."
    },
    {
      "lang": "es",
      "value": "En TensorFlow Lite versiones anteriores a 2.2.1 y 2.3.1, los modelos que utilizan la suma de segmentos pueden activar escrituras fuera de límites de los búferes asignados de la pila insertando elementos negativos en el tensor de los ids de segmento. Los usuarios que tienen acceso a \"segment_ids_data\" pueden alterar \"output_index\" y luego escribir fuera del búfer de \"output_data\". Esto podría resultar en un fallo de segmentación, pero también se puede usar para corromper aún más la memoria y se puede encadenar con otras vulnerabilidades para crear explotaciones más avanzadas. El problema es parcheado en el commit 204945b19e44b57906c9344c0d00120eeeae178a y es publicado en TensorFlow versiones 2.2.1 o 2.3.1. Una solución alternativa potencial sería agregar un \"Verifier\" personalizado al código de carga del modelo para asegurar que los ids de segmento sean todos positivos, aunque esto solo maneja el caso cuando los ids de segmento son almacenados estáticamente en el modelo. Una comprobación similar podría ser realizada si los ids de segmento se generan en el tiempo de ejecución entre los pasos de inferencia. Si los ids de segmento son generados como salidas de un tensor durante los pasos de inferencia, entonces no existe una posible solución alternativa y se recomienda a los usuarios actualizar al código parcheado"
    }
  ],
  "lastModified": "2026-06-17T02:56:16.773",
  "configurations": [
    {
      "nodes": [
        {
          "negate": false,
          "cpeMatch": [
            {
              "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*",
              "vulnerable": true,
              "matchCriteriaId": "323B716A-E8F7-4CDA-B8FD-A56977D59C02",
              "versionEndExcluding": "2.2.1",
              "versionStartIncluding": "2.2.0"
            },
            {
              "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*",
              "vulnerable": true,
              "matchCriteriaId": "C09502A8-B667-4867-BEBD-40333E98A601",
              "versionEndExcluding": "2.3.1",
              "versionStartIncluding": "2.3.0"
            }
          ],
          "operator": "OR"
        }
      ]
    }
  ],
  "sourceIdentifier": "security-advisories@github.com"
}