CVE-2020-15213
Vulnerability from cvelistv5
Published
2020-09-25 18:50
Modified
2024-08-04 13:08
Severity ?
4.0 (Medium) - CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L
Summary
In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. 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 limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, 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.
References
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178aPatch, Third Party Advisory
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
security-advisories@github.comhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87Exploit, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178aPatch, Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1Third Party Advisory
af854a3a-2127-422b-91ae-364da2661108https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87Exploit, Third Party Advisory
Impacted products
Vendor Product Version
Show details on NVD website

To clipboard 

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-04T13:08:22.853Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"
          },
          {
            "tags": [
              "x_refsource_CONFIRM",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "tensorflow",
          "vendor": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": "= 2.2.0"
            },
            {
              "status": "affected",
              "version": "= 2.3.0"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. 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 limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, 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."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "LOW",
            "baseScore": 4,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "CHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-119",
              "description": "{\"CWE-119\":\"Improper Restriction of Operations within the Bounds of a Memory Buffer\"}",
              "lang": "en",
              "type": "CWE"
            }
          ]
        },
        {
          "descriptions": [
            {
              "cweId": "CWE-770",
              "description": "{\"CWE-770\":\"Allocation of Resources Without Limits or Throttling\"}",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2020-09-25T18:50:29",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
        },
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"
        },
        {
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87"
        }
      ],
      "source": {
        "advisory": "GHSA-hjmq-236j-8m87",
        "discovery": "UNKNOWN"
      },
      "title": "Denial of service in tensorflow-lite",
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2020-15213",
          "STATE": "PUBLIC",
          "TITLE": "Denial of service in tensorflow-lite"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "tensorflow",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "= 2.2.0"
                          },
                          {
                            "version_value": "= 2.3.0"
                          }
                        ]
                      }
                    }
                  ]
                },
                "vendor_name": "tensorflow"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. 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 limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, 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."
            }
          ]
        },
        "impact": {
          "cvss": {
            "attackComplexity": "HIGH",
            "attackVector": "NETWORK",
            "availabilityImpact": "LOW",
            "baseScore": 4,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "NONE",
            "privilegesRequired": "NONE",
            "scope": "CHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L",
            "version": "3.1"
          }
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "{\"CWE-119\":\"Improper Restriction of Operations within the Bounds of a Memory Buffer\"}"
                }
              ]
            },
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "{\"CWE-770\":\"Allocation of Resources Without Limits or Throttling\"}"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87",
              "refsource": "CONFIRM",
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87"
            }
          ]
        },
        "source": {
          "advisory": "GHSA-hjmq-236j-8m87",
          "discovery": "UNKNOWN"
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2020-15213",
    "datePublished": "2020-09-25T18:50:29",
    "dateReserved": "2020-06-25T00:00:00",
    "dateUpdated": "2024-08-04T13:08:22.853Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1",
  "meta": {
    "nvd": "{\"cve\":{\"id\":\"CVE-2020-15213\",\"sourceIdentifier\":\"security-advisories@github.com\",\"published\":\"2020-09-25T19:15:16.603\",\"lastModified\":\"2024-11-21T05:05:06.193\",\"vulnStatus\":\"Modified\",\"cveTags\":[],\"descriptions\":[{\"lang\":\"en\",\"value\":\"In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a denial of service by causing an out of memory allocation in the implementation of segment sum. Since code uses the last element of the tensor holding them to determine the dimensionality of output tensor, attackers can use a very large value to trigger a large allocation. 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 limit the maximum value in the segment ids tensor. This only handles the case when the segment ids are stored statically in the model, but a similar validation could be done if the segment ids are generated at runtime, between inference steps. However, 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 desencadenar una denegaci\u00f3n de servicio al causar una asignaci\u00f3n de memoria insuficiente en la implementaci\u00f3n de la suma de segmentos. Dado que el c\u00f3digo usa el \u00faltimo elemento del tensor que los conserva para determinar la dimensionalidad del tensor de salida, los atacantes pueden usar un valor muy grande para desencadenar una gran asignaci\u00f3n. El problema es parcheado en el commit 204945b19e44b57906c9344c0d00120eeeae178a y es publicado en TensorFlow versiones 2.2.1 o 2.3.1. Una soluci\u00f3n alternativa potencial ser\u00eda agregar un \\\"Verifier\\\" personalizado para limitar el valor m\u00e1ximo en el tensor de los ids de segmento. Esto solo maneja el caso cuando los ids de segmento son almacenados est\u00e1ticamente en el modelo, pero se podr\u00eda realizar una comprobaci\u00f3n similar si los ids de segmento son generados en el tiempo de ejecuci\u00f3n, entre los pasos de inferencia. Sin embargo, si los ids de segmento son generados como salidas de un tensor durante los pasos de inferencia, entonces no existe una soluci\u00f3n posible y se recomienda a los usuarios actualizar al c\u00f3digo parcheado\"}],\"metrics\":{\"cvssMetricV31\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L\",\"baseScore\":4.0,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"HIGH\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"CHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"LOW\"},\"exploitabilityScore\":2.2,\"impactScore\":1.4},{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"3.1\",\"vectorString\":\"CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:L\",\"baseScore\":4.0,\"baseSeverity\":\"MEDIUM\",\"attackVector\":\"NETWORK\",\"attackComplexity\":\"HIGH\",\"privilegesRequired\":\"NONE\",\"userInteraction\":\"NONE\",\"scope\":\"CHANGED\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"LOW\"},\"exploitabilityScore\":2.2,\"impactScore\":1.4}],\"cvssMetricV2\":[{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"cvssData\":{\"version\":\"2.0\",\"vectorString\":\"AV:N/AC:M/Au:N/C:N/I:N/A:P\",\"baseScore\":4.3,\"accessVector\":\"NETWORK\",\"accessComplexity\":\"MEDIUM\",\"authentication\":\"NONE\",\"confidentialityImpact\":\"NONE\",\"integrityImpact\":\"NONE\",\"availabilityImpact\":\"PARTIAL\"},\"baseSeverity\":\"MEDIUM\",\"exploitabilityScore\":8.6,\"impactScore\":2.9,\"acInsufInfo\":false,\"obtainAllPrivilege\":false,\"obtainUserPrivilege\":false,\"obtainOtherPrivilege\":false,\"userInteractionRequired\":false}]},\"weaknesses\":[{\"source\":\"security-advisories@github.com\",\"type\":\"Secondary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-119\"},{\"lang\":\"en\",\"value\":\"CWE-770\"}]},{\"source\":\"nvd@nist.gov\",\"type\":\"Primary\",\"description\":[{\"lang\":\"en\",\"value\":\"CWE-770\"}]}],\"configurations\":[{\"nodes\":[{\"operator\":\"OR\",\"negate\":false,\"cpeMatch\":[{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*\",\"versionStartIncluding\":\"2.2.0\",\"versionEndExcluding\":\"2.2.1\",\"matchCriteriaId\":\"323B716A-E8F7-4CDA-B8FD-A56977D59C02\"},{\"vulnerable\":true,\"criteria\":\"cpe:2.3:a:google:tensorflow:*:*:*:*:lite:*:*:*\",\"versionStartIncluding\":\"2.3.0\",\"versionEndExcluding\":\"2.3.1\",\"matchCriteriaId\":\"C09502A8-B667-4867-BEBD-40333E98A601\"}]}]}],\"references\":[{\"url\":\"https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87\",\"source\":\"security-advisories@github.com\",\"tags\":[\"Exploit\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/commit/204945b19e44b57906c9344c0d00120eeeae178a\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Patch\",\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Third Party Advisory\"]},{\"url\":\"https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hjmq-236j-8m87\",\"source\":\"af854a3a-2127-422b-91ae-364da2661108\",\"tags\":[\"Exploit\",\"Third Party Advisory\"]}]}}"
  }
}


Log in or create an account to share your comment.




Tags
Taxonomy of the tags.




Sightings

Author Source Type Date

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or seen somewhere by the user.
  • Confirmed: The vulnerability is confirmed from an analyst perspective.
  • Exploited: This vulnerability was exploited and seen by the user reporting the sighting.
  • Patched: This vulnerability was successfully patched by the user reporting the sighting.
  • Not exploited: This vulnerability was not exploited or seen by the user reporting the sighting.
  • Not confirmed: The user expresses doubt about the veracity of the vulnerability.
  • Not patched: This vulnerability was not successfully patched by the user reporting the sighting.