pysec - pysec-2022-84

pysec-2022-84

Vulnerability from pysec

Published

2022-02-04 23:15

Modified

2022-03-09 00:17

Details

Tensorflow is an Open Source Machine Learning Framework. The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. 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-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "fcd18ce3101f245b083b30655c27b239dc72221e"
            }
          ],
          "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": [
        "1.15.0",
        "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-2022-23575",
    "GHSA-c94w-c95p-phf8"
  ],
  "details": "Tensorflow is an Open Source Machine Learning Framework. The implementation of `OpLevelCostEstimator::CalculateTensorSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. 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-2022-84",
  "modified": "2022-03-09T00:17:34.290009Z",
  "published": "2022-02-04T23:15:00Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8"
    }
  ]
}

cve-2022-23575

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. The implementation of `OpLevelCostEstimator::CalculateTensorSize` is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements. 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-c94w-c95p-phf8	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558	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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            "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558"
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}

ghsa-c94w-c95p-phf8

Vulnerability from github

Published

2022-02-10 00:32

Modified

2024-11-13 22:48

Severity ?

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

Summary

Integer overflow in Tensorflow

Details

Impact

The implementation of OpLevelCostEstimator::CalculateTensorSize is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements: cc int64_t OpLevelCostEstimator::CalculateTensorSize( const OpInfo::TensorProperties& tensor, bool* found_unknown_shapes) { int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes); int size = DataTypeSize(BaseType(tensor.dtype())); VLOG(2) << "Count: " << count << " DataTypeSize: " << size; return count * size; } Here, count and size can be large enough to cause count * size to overflow.

Patches

We have patched the issue in GitHub commit fcd18ce3101f245b083b30655c27b239dc72221e.

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": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            }
          ],
          "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"
      ]
    },
    {
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
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        {
          "events": [
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              "introduced": "0"
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            {
              "fixed": "2.5.3"
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      ]
    },
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        "name": "tensorflow-gpu"
      },
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        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
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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-2022-23575"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-190"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-04T20:19:53Z",
    "nvd_published_at": "2022-02-04T23:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nThe [implementation of `OpLevelCostEstimator::CalculateTensorSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558) is vulnerable to an integer overflow if an attacker can create an operation which would involve a tensor with large enough number of elements:\n```cc\nint64_t OpLevelCostEstimator::CalculateTensorSize(\n    const OpInfo::TensorProperties\u0026 tensor, bool* found_unknown_shapes) {\n  int64_t count = CalculateTensorElementCount(tensor, found_unknown_shapes);\n  int size = DataTypeSize(BaseType(tensor.dtype()));\n  VLOG(2) \u003c\u003c \"Count: \" \u003c\u003c count \u003c\u003c \" DataTypeSize: \" \u003c\u003c size;\n  return count * size;\n}\n```\nHere, `count` and `size` can be large enough to cause `count * size` to overflow.\n\n### Patches\nWe have patched the issue in GitHub commit [fcd18ce3101f245b083b30655c27b239dc72221e](https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e).\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-c94w-c95p-phf8",
  "modified": "2024-11-13T22:48:17Z",
  "published": "2022-02-10T00:32:59Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c94w-c95p-phf8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-23575"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/fcd18ce3101f245b083b30655c27b239dc72221e"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-84.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-139.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/grappler/costs/op_level_cost_estimator.cc#L1552-L1558"
    }
  ],
  "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"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Integer overflow in Tensorflow"
}

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-2022-84

Vulnerability from pysec

cve-2022-23575

Vulnerability from cvelistv5

ghsa-c94w-c95p-phf8

Vulnerability from github

Impact

Patches

For more information

Tags

Sightings

Nomenclature