GSD-2020-26266

Vulnerability from gsd - Updated: 2023-12-13 01:22
Details
In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. 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
CVE-2020-26266
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{
  "GSD": {
    "alias": "CVE-2020-26266",
    "description": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. 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-2020-26266",
    "references": [
      "https://www.suse.com/security/cve/CVE-2020-26266.html",
      "https://security.archlinux.org/CVE-2020-26266"
    ]
  },
  "gsd": {
    "metadata": {
      "exploitCode": "unknown",
      "remediation": "unknown",
      "reportConfidence": "confirmed",
      "type": "vulnerability"
    },
    "osvSchema": {
      "aliases": [
        "CVE-2020-26266"
      ],
      "details": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. 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-2020-26266",
      "modified": "2023-12-13T01:22:08.782818Z",
      "schema_version": "1.4.0"
    }
  },
  "namespaces": {
    "cve.org": {
      "CVE_data_meta": {
        "ASSIGNER": "security-advisories@github.com",
        "ID": "CVE-2020-26266",
        "STATE": "PUBLIC",
        "TITLE": "Uninitialized memory access in Eigen types 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": {
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          {
            "lang": "eng",
            "value": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. 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-908: Use of Uninitialized Resource"
              }
            ]
          }
        ]
      },
      "references": {
        "reference_data": [
          {
            "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qhxx-j73r-qpm2",
            "refsource": "CONFIRM",
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qhxx-j73r-qpm2"
          },
          {
            "name": "https://github.com/tensorflow/tensorflow/commit/ace0c15a22f7f054abcc1f53eabbcb0a1239a9e2",
            "refsource": "MISC",
            "url": "https://github.com/tensorflow/tensorflow/commit/ace0c15a22f7f054abcc1f53eabbcb0a1239a9e2"
          }
        ]
      },
      "source": {
        "advisory": "GHSA-qhxx-j73r-qpm2",
        "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:P/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
          "cwe_ids": [
            "CWE-1035",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2020-12-14",
          "description": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen.",
          "fixed_versions": [],
          "identifier": "CVE-2020-26266",
          "identifiers": [
            "CVE-2020-26266",
            "GHSA-qhxx-j73r-qpm2"
          ],
          "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-2020-26266"
          ],
          "uuid": "c4f09fdd-d252-46ce-9576-bb6576d583f1"
        },
        {
          "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:P/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
          "cwe_ids": [
            "CWE-1035",
            "CWE-78",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2021-01-07",
          "description": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. 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-2020-26266",
          "identifiers": [
            "GHSA-qhxx-j73r-qpm2",
            "CVE-2020-26266"
          ],
          "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-qhxx-j73r-qpm2",
            "https://github.com/tensorflow/tensorflow/commit/ace0c15a22f7f054abcc1f53eabbcb0a1239a9e2",
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26266",
            "https://github.com/advisories/GHSA-qhxx-j73r-qpm2"
          ],
          "uuid": "eef2146c-36cb-41d7-bdab-07b64c658efd"
        },
        {
          "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:P/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
          "cwe_ids": [
            "CWE-1035",
            "CWE-78",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2021-01-07",
          "description": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen. 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-2020-26266",
          "identifiers": [
            "GHSA-qhxx-j73r-qpm2",
            "CVE-2020-26266"
          ],
          "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-qhxx-j73r-qpm2",
            "https://github.com/tensorflow/tensorflow/commit/ace0c15a22f7f054abcc1f53eabbcb0a1239a9e2",
            "https://nvd.nist.gov/vuln/detail/CVE-2020-26266",
            "https://github.com/advisories/GHSA-qhxx-j73r-qpm2"
          ],
          "uuid": "e5eea5dc-6a2a-44ed-8580-e0e3ddf6f35a"
        },
        {
          "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:P/A:P",
          "cvss_v3": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L",
          "cwe_ids": [
            "CWE-1035",
            "CWE-908",
            "CWE-937"
          ],
          "date": "2020-12-14",
          "description": "In affected versions of TensorFlow under certain cases a saved model can trigger use of uninitialized values during code execution. This is caused by having tensor buffers be filled with the default value of the type but forgetting to default initialize the quantized floating point types in Eigen.",
          "fixed_versions": [
            "2.4.0"
          ],
          "identifier": "CVE-2020-26266",
          "identifiers": [
            "CVE-2020-26266",
            "GHSA-qhxx-j73r-qpm2"
          ],
          "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-2020-26266"
          ],
          "uuid": "9fbfdaf1-1d5f-47f1-bee7-352fae943f9a"
        }
      ]
    },
    "nvd.nist.gov": {
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        "nodes": [
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                "cpe23Uri": "cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:*",
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                "versionEndExcluding": "1.15.5",
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      "impact": {
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          "acInsufInfo": false,
          "cvssV2": {
            "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"
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          "exploitabilityScore": 3.9,
          "impactScore": 6.4,
          "obtainAllPrivilege": false,
          "obtainOtherPrivilege": false,
          "obtainUserPrivilege": false,
          "severity": "MEDIUM",
          "userInteractionRequired": false
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        "baseMetricV3": {
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            "confidentialityImpact": "LOW",
            "integrityImpact": "LOW",
            "privilegesRequired": "LOW",
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            "version": "3.1"
          },
          "exploitabilityScore": 1.8,
          "impactScore": 3.4
        }
      },
      "lastModifiedDate": "2020-12-14T17:54Z",
      "publishedDate": "2020-12-10T23:15Z"
    }
  }
}


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  • 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.
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  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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  • 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.



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