gsd-2020-26271
Vulnerability from gsd
Modified
2023-12-13 01:22
Details
In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
Aliases
Aliases



{
  "GSD": {
    "alias": "CVE-2020-26271",
    "description": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
    "id": "GSD-2020-26271",
    "references": [
      "https://www.suse.com/security/cve/CVE-2020-26271.html",
      "https://security.archlinux.org/CVE-2020-26271"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2020-26271"
      ],
      "details": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
      "id": "GSD-2020-26271",
      "modified": "2023-12-13T01:22:08.957931Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
    "cve.org": {
      "CVE_data_meta": {
        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2020-26271",
        "STATE": "PUBLIC",
        "TITLE": "Heap out of bounds access in MakeEdge in TensorFlow"
      },
      "affects": {
        "vendor": {
          "vendor_data": [
            {
              "product": {
                "product_data": [
                  {
                    "product_name": "tensorflow",
                    "version": {
                      "version_data": [
                        {
                          "version_value": "\u003c 1.15.5"
                        },
                        {
                          "version_value": "\u003e= 2.0.0, \u003c 2.0.4"
                        },
                        {
                          "version_value": "\u003e= 2.1.0, \u003c 2.1.3"
                        },
                        {
                          "version_value": "\u003e= 2.2.0, \u003c 2.2.2"
                        },
                        {
                          "version_value": "\u003e= 2.3.0, \u003c 2.3.2"
                        }
                      ]
                    }
                  }
                ]
              },
              "vendor_name": "tensorflow"
            }
          ]
        }
      },
      "data_format": "MITRE",
      "data_type": "CVE",
      "data_version": "4.0",
      "description": {
        "description_data": [
          {
            "lang": "eng",
            "value": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."
          }
        ]
      },
      "impact": {
        "cvss": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "LOW",
          "baseScore": 4.4,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "NONE",
          "integrityImpact": "LOW",
          "privilegesRequired": "LOW",
          "scope": "UNCHANGED",
          "userInteraction": "NONE",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:L/A:L",
          "version": "3.1"
        }
      },
      "problemtype": {
        "problemtype_data": [
          {
            "description": [
              {
                "lang": "eng",
                "value": "CWE-125 Out-of-bounds Read"
              }
            ]
          }
        ]
      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-q263-fvxm-m5mw",
        "discovery": "UNKNOWN"
      }
    },
    "gitlab.com": {
      "advisories": [
        {
          "affected_range": "(,1.15.5),[2.0.0,2.0.4),[2.1.0,2.1.3),[2.2.0,2.2.2),[2.3.0,2.3.2)",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:N/A:N",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2020-12-14",
          "description": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The `MakeEdge` function creates an edge between one output tensor of the src node (given by `output_index`) and the input slot of the dst node (given by `input_index`). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding `DataType` values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out-of-bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library.",
          "fixed_versions": [],
          "identifier": "CVE-2020-26271",
          "identifiers": [
            "CVE-2020-26271",
            "GHSA-q263-fvxm-m5mw"
          ],
          "not_impacted": "",
          "package_slug": "maven/org.tensorflow/parentpom",
          "pubdate": "2020-12-10",
          "solution": "Unfortunately, there is no solution available yet.",
          "title": "Use of Uninitialized Resource",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26271"
          ],
          "uuid": "97ac0f67-db83-4fb6-aed5-5adbcf87af54"
        },
        {
          "affected_range": "\u003c1.15.5||\u003e=2.0.0,\u003c2.0.4||\u003e=2.1.0,\u003c2.1.3||\u003e=2.2.0,\u003c2.2.2||\u003e=2.3.0,\u003c2.3.2",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:N/A:N",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2021-01-07",
          "description": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node . This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
          "fixed_versions": [
            "1.15.5",
            "2.0.4",
            "2.1.3",
            "2.2.2",
            "2.3.2"
          ],
          "identifier": "CVE-2020-26271",
          "identifiers": [
            "GHSA-q263-fvxm-m5mw",
            "CVE-2020-26271"
          ],
          "not_impacted": "All versions starting from 1.15.5 before 2.0.0, all versions starting from 2.0.4 before 2.1.0, all versions starting from 2.1.3 before 2.2.0, all versions starting from 2.2.2 before 2.3.0, all versions starting from 2.3.2",
          "package_slug": "pypi/tensorflow-cpu",
          "pubdate": "2020-12-10",
          "solution": "Upgrade to versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or above.",
          "title": "Use of Uninitialized Resource",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw",
            "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b",
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26271",
            "https://github.com/advisories/GHSA-q263-fvxm-m5mw"
          ],
          "uuid": "70abc4c8-f40c-449d-a19d-4bd566d97d2a"
        },
        {
          "affected_range": "\u003c1.15.5||\u003e=2.0.0,\u003c2.0.4||\u003e=2.1.0,\u003c2.1.3||\u003e=2.2.0,\u003c2.2.2||\u003e=2.3.0,\u003c2.3.2",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:N/A:N",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2021-01-07",
          "description": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node . This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.",
          "fixed_versions": [
            "1.15.5",
            "2.0.4",
            "2.1.3",
            "2.2.2",
            "2.3.2"
          ],
          "identifier": "CVE-2020-26271",
          "identifiers": [
            "GHSA-q263-fvxm-m5mw",
            "CVE-2020-26271"
          ],
          "not_impacted": "All versions starting from 1.15.5 before 2.0.0, all versions starting from 2.0.4 before 2.1.0, all versions starting from 2.1.3 before 2.2.0, all versions starting from 2.2.2 before 2.3.0, all versions starting from 2.3.2",
          "package_slug": "pypi/tensorflow-gpu",
          "pubdate": "2020-12-10",
          "solution": "Upgrade to versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2 or above.",
          "title": "Use of Uninitialized Resource",
          "urls": [
            "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw",
            "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b",
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26271",
            "https://github.com/advisories/GHSA-q263-fvxm-m5mw"
          ],
          "uuid": "0ef33a6c-2bcb-4fdd-8aaa-16cc127306ad"
        },
        {
          "affected_range": "\u003c1.15.5||\u003e=2.0.0,\u003c2.0.4||\u003e=2.1.0,\u003c2.1.3||\u003e=2.2.0,\u003c2.2.2||\u003e=2.3.0,\u003c2.3.2",
          "affected_versions": "All versions before 1.15.5, all versions starting from 2.0.0 before 2.0.4, all versions starting from 2.1.0 before 2.1.3, all versions starting from 2.2.0 before 2.2.2, all versions starting from 2.3.0 before 2.3.2",
          "cvss_v2": "AV:L/AC:L/Au:N/C:P/I:N/A:N",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
          "cwe_ids": [
            "CWE-1035",
            "CWE-125",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2020-12-14",
          "description": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The `MakeEdge` function creates an edge between one output tensor of the src node (given by `output_index`) and the input slot of the dst node (given by `input_index`). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding `DataType` values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out-of-bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library.",
          "fixed_versions": [
            "2.4.0"
          ],
          "identifier": "CVE-2020-26271",
          "identifiers": [
            "CVE-2020-26271",
            "GHSA-q263-fvxm-m5mw"
          ],
          "not_impacted": "All versions starting from 1.15.5 before 2.0.0, all versions starting from 2.0.4 before 2.1.0, all versions starting from 2.1.3 before 2.2.0, all versions starting from 2.2.2 before 2.3.0, all versions starting from 2.3.2",
          "package_slug": "pypi/tensorflow",
          "pubdate": "2020-12-10",
          "solution": "Upgrade to version 2.4.0 or above.",
          "title": "Use of Uninitialized Resource",
          "urls": [
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26271"
          ],
          "uuid": "18fdf16a-f906-4982-a4a2-52ccf316d901"
        }
      ]
    },
    "nvd.nist.gov": {
      "configurations": {
        "CVE_data_version": "4.0",
        "nodes": [
          {
            "children": [],
            "cpe_match": [
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "1.15.5",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.0.4",
                "versionStartIncluding": "2.0.0",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.1.3",
                "versionStartIncluding": "2.1.0",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.2.2",
                "versionStartIncluding": "2.2.0",
                "vulnerable": true
              },
              {
                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
                "cpe_name": [],
                "versionEndExcluding": "2.3.2",
                "versionStartIncluding": "2.3.0",
                "vulnerable": true
              }
            ],
            "operator": "OR"
          }
        ]
      },
      "cve": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2020-26271"
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "en",
              "value": "In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function creates an edge between one output tensor of the src node (given by output_index) and the input slot of the dst node (given by input_index). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding DataType values and comparing these for equality. However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays. In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0."
            }
          ]
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "en",
                  "value": "CWE-125"
                },
                {
                  "lang": "en",
                  "value": "CWE-908"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw",
              "refsource": "CONFIRM",
              "tags": [
                "Exploit",
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-q263-fvxm-m5mw"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b",
              "refsource": "MISC",
              "tags": [
                "Patch",
                "Third Party Advisory"
              ],
              "url": "https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b"
            }
          ]
        }
      },
      "impact": {
        "baseMetricV2": {
          "acInsufInfo": false,
          "cvssV2": {
            "accessComplexity": "LOW",
            "accessVector": "LOCAL",
            "authentication": "NONE",
            "availabilityImpact": "NONE",
            "baseScore": 2.1,
            "confidentialityImpact": "PARTIAL",
            "integrityImpact": "NONE",
            "vectorString": "AV:L/AC:L/Au:N/C:P/I:N/A:N",
            "version": "2.0"
          },
          "exploitabilityScore": 3.9,
          "impactScore": 2.9,
          "obtainAllPrivilege": false,
          "obtainOtherPrivilege": false,
          "obtainUserPrivilege": false,
          "severity": "LOW",
          "userInteractionRequired": false
        },
        "baseMetricV3": {
          "cvssV3": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "NONE",
            "baseScore": 3.3,
            "baseSeverity": "LOW",
            "confidentialityImpact": "LOW",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N",
            "version": "3.1"
          },
          "exploitabilityScore": 1.8,
          "impactScore": 1.4
        }
      },
      "lastModifiedDate": "2020-12-14T18:35Z",
      "publishedDate": "2020-12-10T22:15Z"
    }
  }
}


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