CVE-2021-37665 (GCVE-0-2021-37665)

Vulnerability from cvelistv5 – Published: 2021-08-12 22:40 – Updated: 2024-08-04 01:23
VLAI
Title
Incomplete validation in MKL requantization in TensorFlow
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Severity
7.8 (High)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
CWE
  • CWE-20 - Improper Input Validation
Assigner
References
Impacted products
Vendor Product Version CPE status
tensorflow tensorflow Affected: >= 2.5.0, < 2.5.1
Affected: >= 2.4.0, < 2.4.3
Affected: < 2.3.4
guessed Create a notification for this product.
Show details on NVD website
To clipboard 

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-04T01:23:01.435Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_refsource_CONFIRM",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "tensorflow",
          "vendor": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 2.5.0, \u003c 2.5.1"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.4.0, \u003c 2.4.3"
            },
            {
              "status": "affected",
              "version": "\u003c 2.3.4"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 7.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-20",
              "description": "CWE-20: Improper Input Validation",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2021-08-12T22:40:12.000Z",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
        },
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
        },
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
        }
      ],
      "source": {
        "advisory": "GHSA-v82p-hv3v-p6qp",
        "discovery": "UNKNOWN"
      },
      "title": "Incomplete validation in MKL requantization in TensorFlow",
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2021-37665",
          "STATE": "PUBLIC",
          "TITLE": "Incomplete validation in MKL requantization in TensorFlow"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "tensorflow",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "\u003e= 2.5.0, \u003c 2.5.1"
                          },
                          {
                            "version_value": "\u003e= 2.4.0, \u003c 2.4.3"
                          },
                          {
                            "version_value": "\u003c 2.3.4"
                          }
                        ]
                      }
                    }
                  ]
                },
                "vendor_name": "tensorflow"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
            }
          ]
        },
        "impact": {
          "cvss": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 7.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "CWE-20: Improper Input Validation"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp",
              "refsource": "CONFIRM",
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
            }
          ]
        },
        "source": {
          "advisory": "GHSA-v82p-hv3v-p6qp",
          "discovery": "UNKNOWN"
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2021-37665",
    "datePublished": "2021-08-12T22:40:12.000Z",
    "dateReserved": "2021-07-29T00:00:00.000Z",
    "dateUpdated": "2024-08-04T01:23:01.435Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1",
  "vulnerability-lookup:meta": {
    "epss": {
      "cve": "CVE-2021-37665",
      "date": "2026-09-26",
      "epss": "0.00185",
      "percentile": "0.0724"
    },
    "fkie_nvd": {
      "configurations": [
        {
          "nodes": [
            {
              "cpeMatch": [
                {
                  "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                  "matchCriteriaId": "0F83C081-51CC-415F-A8C0-0A44C75E2CD6",
                  "versionEndExcluding": "2.3.4",
                  "versionStartIncluding": "2.3.0",
                  "vulnerable": true
                },
                {
                  "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                  "matchCriteriaId": "BD3F2BF8-EBA9-42BF-8F9B-D918B880B15A",
                  "versionEndExcluding": "2.4.3",
                  "versionStartIncluding": "2.4.0",
                  "vulnerable": true
                },
                {
                  "criteria": "cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:*",
                  "matchCriteriaId": "D03E99A7-4E3D-427D-A156-C0713E9FB02A",
                  "vulnerable": true
                },
                {
                  "criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*",
                  "matchCriteriaId": "70FA6E48-6C57-40CA-809F-4E3D07CBF348",
                  "vulnerable": true
                },
                {
                  "criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*",
                  "matchCriteriaId": "42187561-E491-434D-828C-F36701446634",
                  "vulnerable": true
                },
                {
                  "criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*",
                  "matchCriteriaId": "C66B61C8-450A-4C5E-9174-F970D6DEE778",
                  "vulnerable": true
                }
              ],
              "negate": false,
              "operator": "OR"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
        },
        {
          "lang": "es",
          "value": "TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico.\u0026#xa0;En las versiones afectadas debido a una comprobaci\u00f3n incompleta en la implementaci\u00f3n de recantizaci\u00f3n de MKL, un atacante puede desencadenar un comportamiento indefinido vinculando una referencia a un puntero null o puede acceder a datos fuera de l\u00edmites de las matrices asignadas a la pila.\u0026#xa0;La [implementaci\u00f3n] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) no comprueba las dimensiones del tensor \"input\".\u0026#xa0;Un problema similar ocurre en \"MklRequantizePerChannelOp\".\u0026#xa0;La [implementaci\u00f3n] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) no lleva a cabo una comprobaci\u00f3n completa para todos los argumentos de entrada.\u0026#xa0;Hemos solucionado el problema en el commit de GitHub 9e62869465573cb2d9b5053f1fa02a81fce21d69 y en el commit de Github 203214568f5bc237603dbab6e1fd389f1572f5c9.\u0026#xa0;La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.6.0.\u0026#xa0;Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.5.1, TensorFlow versi\u00f3n 2.4.3 y TensorFlow versi\u00f3n 2.3.4, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan se encuentran en el rango admitido."
        }
      ],
      "id": "CVE-2021-37665",
      "lastModified": "2024-11-21T06:15:38.997",
      "metrics": {
        "cvssMetricV2": [
          {
            "acInsufInfo": false,
            "baseSeverity": "MEDIUM",
            "cvssData": {
              "accessComplexity": "LOW",
              "accessVector": "LOCAL",
              "authentication": "NONE",
              "availabilityImpact": "PARTIAL",
              "baseScore": 4.6,
              "confidentialityImpact": "PARTIAL",
              "integrityImpact": "PARTIAL",
              "vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
              "version": "2.0"
            },
            "exploitabilityScore": 3.9,
            "impactScore": 6.4,
            "obtainAllPrivilege": false,
            "obtainOtherPrivilege": false,
            "obtainUserPrivilege": false,
            "source": "nvd@nist.gov",
            "type": "Primary",
            "userInteractionRequired": false
          }
        ],
        "cvssMetricV31": [
          {
            "cvssData": {
              "attackComplexity": "LOW",
              "attackVector": "LOCAL",
              "availabilityImpact": "HIGH",
              "baseScore": 7.8,
              "baseSeverity": "HIGH",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "HIGH",
              "privilegesRequired": "LOW",
              "scope": "UNCHANGED",
              "userInteraction": "NONE",
              "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
              "version": "3.1"
            },
            "exploitabilityScore": 1.8,
            "impactScore": 5.9,
            "source": "security-advisories@github.com",
            "type": "Secondary"
          },
          {
            "cvssData": {
              "attackComplexity": "LOW",
              "attackVector": "LOCAL",
              "availabilityImpact": "HIGH",
              "baseScore": 7.8,
              "baseSeverity": "HIGH",
              "confidentialityImpact": "HIGH",
              "integrityImpact": "HIGH",
              "privilegesRequired": "LOW",
              "scope": "UNCHANGED",
              "userInteraction": "NONE",
              "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
              "version": "3.1"
            },
            "exploitabilityScore": 1.8,
            "impactScore": 5.9,
            "source": "nvd@nist.gov",
            "type": "Primary"
          }
        ]
      },
      "published": "2021-08-12T23:15:07.333",
      "references": [
        {
          "source": "security-advisories@github.com",
          "tags": [
            "Patch",
            "Third Party Advisory"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
        },
        {
          "source": "security-advisories@github.com",
          "tags": [
            "Patch",
            "Third Party Advisory"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
        },
        {
          "source": "security-advisories@github.com",
          "tags": [
            "Third Party Advisory"
          ],
          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
        },
        {
          "source": "af854a3a-2127-422b-91ae-364da2661108",
          "tags": [
            "Patch",
            "Third Party Advisory"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
        },
        {
          "source": "af854a3a-2127-422b-91ae-364da2661108",
          "tags": [
            "Patch",
            "Third Party Advisory"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
        },
        {
          "source": "af854a3a-2127-422b-91ae-364da2661108",
          "tags": [
            "Third Party Advisory"
          ],
          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
        }
      ],
      "sourceIdentifier": "security-advisories@github.com",
      "vulnStatus": "Modified",
      "weaknesses": [
        {
          "description": [
            {
              "lang": "en",
              "value": "CWE-20"
            }
          ],
          "source": "security-advisories@github.com",
          "type": "Primary"
        }
      ]
    },
    "nvd": {
      "cve": {
        "configurations": [
          {
            "nodes": [
              {
                "cpeMatch": [
                  {
                    "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                    "matchCriteriaId": "0F83C081-51CC-415F-A8C0-0A44C75E2CD6",
                    "versionEndExcluding": "2.3.4",
                    "versionStartIncluding": "2.3.0",
                    "vulnerable": true
                  },
                  {
                    "criteria": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                    "matchCriteriaId": "BD3F2BF8-EBA9-42BF-8F9B-D918B880B15A",
                    "versionEndExcluding": "2.4.3",
                    "versionStartIncluding": "2.4.0",
                    "vulnerable": true
                  },
                  {
                    "criteria": "cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:*",
                    "matchCriteriaId": "D03E99A7-4E3D-427D-A156-C0713E9FB02A",
                    "vulnerable": true
                  },
                  {
                    "criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:*",
                    "matchCriteriaId": "70FA6E48-6C57-40CA-809F-4E3D07CBF348",
                    "vulnerable": true
                  },
                  {
                    "criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:*",
                    "matchCriteriaId": "42187561-E491-434D-828C-F36701446634",
                    "vulnerable": true
                  },
                  {
                    "criteria": "cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:*",
                    "matchCriteriaId": "C66B61C8-450A-4C5E-9174-F970D6DEE778",
                    "vulnerable": true
                  }
                ],
                "negate": false,
                "operator": "OR"
              }
            ]
          }
        ],
        "cveTags": [],
        "descriptions": [
          {
            "lang": "en",
            "value": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in MKL implementation of requantization, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) does not validate the dimensions of the `input` tensor. A similar issue occurs in `MklRequantizePerChannelOp`. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) does not perform full validation for all the input arguments. We have patched the issue in GitHub commit 9e62869465573cb2d9b5053f1fa02a81fce21d69 and in the Github commit 203214568f5bc237603dbab6e1fd389f1572f5c9. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range."
          },
          {
            "lang": "es",
            "value": "TensorFlow es una plataforma de c\u00f3digo abierto de extremo a extremo para el aprendizaje autom\u00e1tico.\u0026#xa0;En las versiones afectadas debido a una comprobaci\u00f3n incompleta en la implementaci\u00f3n de recantizaci\u00f3n de MKL, un atacante puede desencadenar un comportamiento indefinido vinculando una referencia a un puntero null o puede acceder a datos fuera de l\u00edmites de las matrices asignadas a la pila.\u0026#xa0;La [implementaci\u00f3n] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantization_range_per_channel_op.cc) no comprueba las dimensiones del tensor \"input\".\u0026#xa0;Un problema similar ocurre en \"MklRequantizePerChannelOp\".\u0026#xa0;La [implementaci\u00f3n] (https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/mkl/mkl_requantize_per_channel_op.cc) no lleva a cabo una comprobaci\u00f3n completa para todos los argumentos de entrada.\u0026#xa0;Hemos solucionado el problema en el commit de GitHub 9e62869465573cb2d9b5053f1fa02a81fce21d69 y en el commit de Github 203214568f5bc237603dbab6e1fd389f1572f5c9.\u0026#xa0;La correcci\u00f3n ser\u00e1 incluida en TensorFlow versi\u00f3n 2.6.0.\u0026#xa0;Tambi\u00e9n seleccionaremos este commit en TensorFlow versi\u00f3n 2.5.1, TensorFlow versi\u00f3n 2.4.3 y TensorFlow versi\u00f3n 2.3.4, ya que estos tambi\u00e9n est\u00e1n afectados y a\u00fan se encuentran en el rango admitido."
          }
        ],
        "id": "CVE-2021-37665",
        "lastModified": "2024-11-21T06:15:38.997",
        "metrics": {
          "cvssMetricV2": [
            {
              "acInsufInfo": false,
              "baseSeverity": "MEDIUM",
              "cvssData": {
                "accessComplexity": "LOW",
                "accessVector": "LOCAL",
                "authentication": "NONE",
                "availabilityImpact": "PARTIAL",
                "baseScore": 4.6,
                "confidentialityImpact": "PARTIAL",
                "integrityImpact": "PARTIAL",
                "vectorString": "AV:L/AC:L/Au:N/C:P/I:P/A:P",
                "version": "2.0"
              },
              "exploitabilityScore": 3.9,
              "impactScore": 6.4,
              "obtainAllPrivilege": false,
              "obtainOtherPrivilege": false,
              "obtainUserPrivilege": false,
              "source": "nvd@nist.gov",
              "type": "Primary",
              "userInteractionRequired": false
            }
          ],
          "cvssMetricV31": [
            {
              "cvssData": {
                "attackComplexity": "LOW",
                "attackVector": "LOCAL",
                "availabilityImpact": "HIGH",
                "baseScore": 7.8,
                "baseSeverity": "HIGH",
                "confidentialityImpact": "HIGH",
                "integrityImpact": "HIGH",
                "privilegesRequired": "LOW",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
                "version": "3.1"
              },
              "exploitabilityScore": 1.8,
              "impactScore": 5.9,
              "source": "security-advisories@github.com",
              "type": "Secondary"
            },
            {
              "cvssData": {
                "attackComplexity": "LOW",
                "attackVector": "LOCAL",
                "availabilityImpact": "HIGH",
                "baseScore": 7.8,
                "baseSeverity": "HIGH",
                "confidentialityImpact": "HIGH",
                "integrityImpact": "HIGH",
                "privilegesRequired": "LOW",
                "scope": "UNCHANGED",
                "userInteraction": "NONE",
                "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
                "version": "3.1"
              },
              "exploitabilityScore": 1.8,
              "impactScore": 5.9,
              "source": "nvd@nist.gov",
              "type": "Primary"
            }
          ]
        },
        "published": "2021-08-12T23:15:07.333",
        "references": [
          {
            "source": "security-advisories@github.com",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
          },
          {
            "source": "security-advisories@github.com",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
          },
          {
            "source": "security-advisories@github.com",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/203214568f5bc237603dbab6e1fd389f1572f5c9"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Patch",
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/9e62869465573cb2d9b5053f1fa02a81fce21d69"
          },
          {
            "source": "af854a3a-2127-422b-91ae-364da2661108",
            "tags": [
              "Third Party Advisory"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v82p-hv3v-p6qp"
          }
        ],
        "sourceIdentifier": "security-advisories@github.com",
        "vulnStatus": "Modified",
        "weaknesses": [
          {
            "description": [
              {
                "lang": "en",
                "value": "CWE-20"
              }
            ],
            "source": "security-advisories@github.com",
            "type": "Primary"
          }
        ]
      }
    },
    "redhat_vex": {
      "current_release_date": "2026-03-27T13:44:58+00:00",
      "cve": "CVE-2021-37665",
      "id": "CVE-2021-37665",
      "initial_release_date": "2021-01-01T00:00:00+00:00",
      "product_status:known_not_affected": "1",
      "source": "Red Hat CSAF VEX",
      "status": "final",
      "title": "Incomplete validation in MKL requantization in TensorFlow",
      "url": "https://security.access.redhat.com/data/csaf/v2/vex/2021/cve-2021-37665.json",
      "version": "3"
    },
    "suse_vex": {
      "aggregate_severity": "important",
      "current_release_date": "2025-03-15T08:47:06Z",
      "cve": "CVE-2021-37665",
      "id": "CVE-2021-37665",
      "initial_release_date": "2023-02-15T03:39:22Z",
      "product_status:recommended": "56",
      "source": "SUSE CSAF VEX",
      "status": "interim",
      "title": "SUSE CVE CVE-2021-37665",
      "url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2021-37665.json",
      "version": "6"
    }
  }
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.





Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.