github - ghsa-3hxh-8cp2-g4hg

ghsa-3hxh-8cp2-g4hg

Vulnerability from github

Published

2021-08-25 14:39

Modified

2024-11-13 21:25

Severity ?

6.6 (Medium) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H
6.9 (Medium) - CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:H/SC:N/SI:N/SA:N

Summary

Use after free and segfault in shape inference functions

Details

Impact

When running shape functions, some functions (such as MutableHashTableShape) produce extra output information in the form of a ShapeAndType struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault.

ShapeRefiner is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types.

Patches

We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1.

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.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Show details on source website

JSON

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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.3.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.5.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.3.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.1"
            }
          ],
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        }
      ],
      "versions": [
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    },
    {
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      },
      "ranges": [
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    },
    {
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      },
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            {
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        }
      ]
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
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            {
              "fixed": "2.5.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.5.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-37690"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-416"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-08-24T18:16:10Z",
    "nvd_published_at": "2021-08-13T00:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nWhen running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault.\n\n`ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types.\n\n### Patches\nWe have patched the issue in GitHub commit [ee119d4a498979525046fba1c3dd3f13a039fbb1](https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1).                                                                                                          \n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.",
  "id": "GHSA-3hxh-8cp2-g4hg",
  "modified": "2024-11-13T21:25:03Z",
  "published": "2021-08-25T14:39:22Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37690"
    },
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      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-603.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-801.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-312.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Use after free and segfault in shape inference functions"
}

pysec-2021-801

Vulnerability from pysec

Published

2021-08-13 00:15

Modified

2021-12-09 06:35

Details

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as MutableHashTableShape) produce extra output information in the form of a ShapeAndType struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. ShapeRefiner is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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.

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu",
        "purl": "pkg:pypi/tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "ee119d4a498979525046fba1c3dd3f13a039fbb1"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.4"
            },
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.4.0",
        "2.4.1",
        "2.4.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-37690",
    "GHSA-3hxh-8cp2-g4hg"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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.",
  "id": "PYSEC-2021-801",
  "modified": "2021-12-09T06:35:40.227651Z",
  "published": "2021-08-13T00:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1"
    }
  ]
}

pysec-2021-312

Vulnerability from pysec

Published

2021-08-13 00:15

Modified

2021-08-27 03:22

Details

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "ee119d4a498979525046fba1c3dd3f13a039fbb1"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.4"
            },
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.4.0",
        "2.4.1",
        "2.4.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-37690",
    "GHSA-3hxh-8cp2-g4hg"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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.",
  "id": "PYSEC-2021-312",
  "modified": "2021-08-27T03:22:47.685921Z",
  "published": "2021-08-13T00:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1"
    }
  ]
}

pysec-2021-603

Vulnerability from pysec

Published

2021-08-13 00:15

Modified

2021-12-09 06:35

Details

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "ee119d4a498979525046fba1c3dd3f13a039fbb1"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.4"
            },
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            },
            {
              "fixed": "2.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.3.0",
        "2.3.1",
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        "2.4.0",
        "2.4.1",
        "2.4.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-37690",
    "GHSA-3hxh-8cp2-g4hg"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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.",
  "id": "PYSEC-2021-603",
  "modified": "2021-12-09T06:35:06.680335Z",
  "published": "2021-08-13T00:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1"
    }
  ]
}

cve-2021-37690

Vulnerability from cvelistv5

Published

2021-08-12 23:10

Modified

2024-08-04 01:23

Severity ?

6.6 (Medium) - CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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.

References

▼	URL	Tags
	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1	x_refsource_MISC

Impacted products

Vendor

Product

Version

▼

tensorflow

Version: >= 2.5.0, < 2.5.1
Version: >= 2.4.0, < 2.4.3
Version: < 2.3.4

Show details on NVD website

JSON

To clipboard

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        "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 when running shape functions, some functions (such as `MutableHashTableShape`) produce extra output information in the form of a `ShapeAndType` struct. The shapes embedded in this struct are owned by an inference context that is cleaned up almost immediately; if the upstream code attempts to access this shape information, it can trigger a segfault. `ShapeRefiner` is mitigating this for normal output shapes by cloning them (and thus putting the newly created shape under ownership of an inference context that will not die), but we were not doing the same for shapes and types. This commit fixes that by doing similar logic on output shapes and types. We have patched the issue in GitHub commit ee119d4a498979525046fba1c3dd3f13a039fbb1. 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": 6.6,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "LOW",
            "integrityImpact": "LOW",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:H",
            "version": "3.1"
          }
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "CWE-416: Use After Free"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg",
              "refsource": "CONFIRM",
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3hxh-8cp2-g4hg"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/ee119d4a498979525046fba1c3dd3f13a039fbb1"
            }
          ]
        },
        "source": {
          "advisory": "GHSA-3hxh-8cp2-g4hg",
          "discovery": "UNKNOWN"
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2021-37690",
    "datePublished": "2021-08-12T23:10:16",
    "dateReserved": "2021-07-29T00:00:00",
    "dateUpdated": "2024-08-04T01:23:01.511Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

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.

Action not permitted

ghsa-3hxh-8cp2-g4hg

Vulnerability from github

Impact

Patches

For more information

pysec-2021-801

Vulnerability from pysec

pysec-2021-312

Vulnerability from pysec

pysec-2021-603

Vulnerability from pysec

cve-2021-37690

Vulnerability from cvelistv5

Tags

Sightings

Nomenclature