pysec - pysec-2021-570

PYSEC-2021-570

Vulnerability from pysec - Published: 2021-08-12 21:15 - Updated: 2021-12-09 06:35

Details

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixDiagV*. The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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.

Impacted products

Name	purl
tensorflow-cpu	pkg:pypi/tensorflow-cpu

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
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              "introduced": "0"
            },
            {
              "fixed": "f2a673bd34f0d64b8e40a551ac78989d16daad09"
            }
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          "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-2021-37657",
    "GHSA-5xwc-mrhx-5g3m"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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-2021-570",
  "modified": "2021-12-09T06:35:03.842863Z",
  "published": "2021-08-12T21:15:00Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m"
    }
  ]
}

GHSA-5XWC-MRHX-5G3M

Vulnerability from github – Published: 2021-08-25 14:42 – Updated: 2024-11-13 20:52

Summary

Reference binding to nullptr in `MatrixDiagV*` ops

Details

Impact

An attacker can cause undefined behavior via binding a reference to null pointer in all operations of type tf.raw_ops.MatrixDiagV*:

import tensorflow as tf

tf.raw_ops.MatrixDiagV3(
  diagonal=[1,0],
  k=[],
  num_rows=[1,2,3],
  num_cols=[4,5],
  padding_value=[],
  align='RIGHT_RIGHT')

The implementation has incomplete validation that the value of k is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:

  auto& diag_index = context->input(1);
  ...
  lower_diag_index = diag_index.flat<int32>()(0);

Patches

We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09.

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.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.

Severity ?

7.1 (High)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H

6.9 (Medium)


                  
                    CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N

Show details on source website

JSON

To clipboard

{
  "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"
        }
      ]
    },
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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      "ranges": [
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          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.5.0"
      ]
    },
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        "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"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.5.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.3.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.5.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-37657"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-824"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-08-24T13:10:06Z",
    "nvd_published_at": "2021-08-12T21:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nAn attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.MatrixDiagV3(\n  diagonal=[1,0],\n  k=[],\n  num_rows=[1,2,3],\n  num_cols=[4,5],\n  padding_value=[],\n  align=\u0027RIGHT_RIGHT\u0027)\n``` \n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong:\n\n```cc\n  auto\u0026 diag_index = context-\u003einput(1);\n  ...\n  lower_diag_index = diag_index.flat\u003cint32\u003e()(0);\n```\n\n### Patches\nWe have patched the issue in GitHub commit [f2a673bd34f0d64b8e40a551ac78989d16daad09](https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09).\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.\n\n### Attribution\nThis vulnerability has been reported by members of the Aivul Team from Qihoo 360.",
  "id": "GHSA-5xwc-mrhx-5g3m",
  "modified": "2024-11-13T20:52:27Z",
  "published": "2021-08-25T14:42:52Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-5xwc-mrhx-5g3m"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-37657"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/f2a673bd34f0d64b8e40a551ac78989d16daad09"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-570.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-768.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-279.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:N/I:H/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Reference binding to nullptr in `MatrixDiagV*` ops"
}

CVE-2021-37657 (GCVE-0-2021-37657)

Vulnerability from cvelistv5 – Published: 2021-08-12 20:50 – Updated: 2024-08-04 01:23

Summary

TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can cause undefined behavior via binding a reference to null pointer in all operations of type `tf.raw_ops.MatrixDiagV*`. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/linalg/matrix_diag_op.cc) has incomplete validation that the value of `k` is a valid tensor. We have check that this value is either a scalar or a vector, but there is no check for the number of elements. If this is an empty tensor, then code that accesses the first element of the tensor is wrong. We have patched the issue in GitHub commit f2a673bd34f0d64b8e40a551ac78989d16daad09. 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.

Severity ?

7.1 (High)


                        
                          CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H

CWE

CWE-824 - Access of Uninitialized Pointer

Assigner

GitHub_M

References

URL

Tags

	https://github.com/tensorflow/tensorflow/security…	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/f…	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	tensorflow	tensorflow	Affected: >= 2.5.0, < 2.5.1 Affected: >= 2.4.0, < 2.4.3 Affected: < 2.3.4

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 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.
Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
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.

Detection rules are retrieved from Rulezet.

Action not permitted

PYSEC-2021-570

GHSA-5XWC-MRHX-5G3M

Impact

Patches

For more information

Attribution

CVE-2021-37657 (GCVE-0-2021-37657)

Tags

Sightings

Nomenclature