pysec - pysec-2022-146

pysec-2022-146

Vulnerability from pysec

Published

2022-02-04 23:15

Modified

2022-03-09 00:18

Details

Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures. TensorShape constructor throws a CHECK-fail if shape is partial or has a number of elements that would overflow the size of an int. The PartialTensorShape constructor instead does not cause a CHECK-abort if the shape is partial, which is exactly what this function needs to be able to return -1. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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": "c2426bba00a01de6913738df8fa78e0215fcce02"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            },
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.10.0",
        "1.10.1",
        "1.11.0",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.1",
        "1.13.2",
        "1.14.0",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "1.15.4",
        "1.15.5",
        "1.2.0",
        "1.2.1",
        "1.3.0",
        "1.4.0",
        "1.4.1",
        "1.5.0",
        "1.5.1",
        "1.6.0",
        "1.7.0",
        "1.7.1",
        "1.8.0",
        "1.9.0",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.3.4",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.4.4",
        "2.5.0",
        "2.5.1",
        "2.5.2",
        "2.6.0",
        "2.6.1",
        "2.6.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-23582",
    "GHSA-4j82-5ccr-4r8v"
  ],
  "details": "Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that `TensorByteSize` would trigger `CHECK` failures. `TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.",
  "id": "PYSEC-2022-146",
  "modified": "2022-03-09T00:18:28.710235Z",
  "published": "2022-02-04T23:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4j82-5ccr-4r8v"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50"
    }
  ]
}

ghsa-4j82-5ccr-4r8v

Vulnerability from github

Published

2022-02-10 00:34

Modified

2024-11-07 22:27

Severity ?

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

Summary

`CHECK`-failures in `TensorByteSize` in Tensorflow

Details

Impact

A malicious user can cause a denial of service by altering a SavedModel such that TensorByteSize would trigger CHECK failures.

cc int64_t TensorByteSize(const TensorProto& t) { // num_elements returns -1 if shape is not fully defined. int64_t num_elems = TensorShape(t.tensor_shape()).num_elements(); return num_elems < 0 ? -1 : num_elems * DataTypeSize(t.dtype()); } TensorShape constructor throws a CHECK-fail if shape is partial or has a number of elements that would overflow the size of an int. The PartialTensorShape constructor instead does not cause a CHECK-abort if the shape is partial, which is exactly what this function needs to be able to return -1.

Patches

We have patched the issue in GitHub commit c2426bba00a01de6913738df8fa78e0215fcce02.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
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          "events": [
            {
              "introduced": "2.6.0"
            },
            {
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            }
          ],
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        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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      "ranges": [
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            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
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            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
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        }
      ]
    },
    {
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-23582"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-04T19:53:00Z",
    "nvd_published_at": "2022-02-04T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nA malicious user can cause a denial of service by altering a `SavedModel` such that [`TensorByteSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50) would trigger `CHECK` failures.\n\n```cc\nint64_t TensorByteSize(const TensorProto\u0026 t) {\n  // num_elements returns -1 if shape is not fully defined.\n  int64_t num_elems = TensorShape(t.tensor_shape()).num_elements();\n  return num_elems \u003c 0 ? -1 : num_elems * DataTypeSize(t.dtype());\n}\n```\n`TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`.\n\n### Patches\nWe have patched the issue in GitHub commit [c2426bba00a01de6913738df8fa78e0215fcce02](https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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-4j82-5ccr-4r8v",
  "modified": "2024-11-07T22:27:53Z",
  "published": "2022-02-10T00:34:01Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4j82-5ccr-4r8v"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23582"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-91.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-146.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "`CHECK`-failures in `TensorByteSize` in Tensorflow"
}

cve-2022-23582

Vulnerability from cvelistv5

Published

2022-02-04 22:32

Modified

2024-08-03 03:43

Severity ?

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

Summary

Tensorflow is an Open Source Machine Learning Framework. A malicious user can cause a denial of service by altering a `SavedModel` such that `TensorByteSize` would trigger `CHECK` failures. `TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

References

▼	URL	Tags
	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4j82-5ccr-4r8v	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50	x_refsource_MISC

Impacted products

Vendor

Product

Version

▼

tensorflow

Version: >= 2.7.0, < 2.7.1
Version: >= 2.6.0, < 2.6.3
Version: < 2.5.3

Show details on NVD website

JSON

To clipboard

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}

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

pysec-2022-146

Vulnerability from pysec

ghsa-4j82-5ccr-4r8v

Vulnerability from github

Impact

Patches

For more information

cve-2022-23582

Vulnerability from cvelistv5

Tags

Sightings

Nomenclature