pysec - pysec-2021-246

pysec-2021-246

Vulnerability from pysec

Published

2021-05-14 20:15

Modified

2021-08-27 03:22

Details

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "41727ff06111117bdf86b37db198217fd7a143cc"
            },
            {
              "fixed": "6fd02f44810754ae7481838b6a67c5df7f909ca3"
            }
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          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
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            {
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            },
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              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
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            {
              "introduced": "2.4.0"
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            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
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      "versions": [
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        "0.12.0rc1",
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        "1.10.0rc1",
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        "1.11.0rc1",
        "1.11.0rc2",
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        "1.12.0rc0",
        "1.12.0rc1",
        "1.12.0rc2",
        "1.12.2",
        "1.12.3",
        "1.13.0rc0",
        "1.13.0rc1",
        "1.13.0rc2",
        "1.13.1",
        "1.13.2",
        "1.14.0",
        "1.14.0rc0",
        "1.14.0rc1",
        "1.15.0",
        "1.15.0rc0",
        "1.15.0rc1",
        "1.15.0rc2",
        "1.15.0rc3",
        "1.15.2",
        "1.15.3",
        "1.15.4",
        "1.15.5",
        "1.2.0",
        "1.2.0rc0",
        "1.2.0rc1",
        "1.2.0rc2",
        "1.2.1",
        "1.3.0",
        "1.3.0rc0",
        "1.3.0rc1",
        "1.3.0rc2",
        "1.4.0",
        "1.4.0rc0",
        "1.4.0rc1",
        "1.4.1",
        "1.5.0",
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        "1.5.1",
        "1.6.0",
        "1.6.0rc0",
        "1.6.0rc1",
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        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.4.0",
        "2.4.1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29609",
    "GHSA-cjc7-49v2-jp64"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.",
  "id": "PYSEC-2021-246",
  "modified": "2021-08-27T03:22:40.807777Z",
  "published": "2021-05-14T20:15:00Z",
  "references": [
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3"
    }
  ]
}

ghsa-cjc7-49v2-jp64

Vulnerability from github

Published

2021-05-21 14:28

Modified

2024-11-13 16:19

Severity ?

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

Summary

Incomplete validation in `SparseAdd`

Details

Impact

Incomplete validation in SparseAdd results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:

```python import tensorflow as tf

a_indices = tf.zeros([10, 97], dtype=tf.int64) a_values = tf.zeros([10], dtype=tf.int64) a_shape = tf.zeros([0], dtype=tf.int64)

b_indices = tf.zeros([0, 0], dtype=tf.int64) b_values = tf.zeros([0], dtype=tf.int64) b_shape = tf.zeros([0], dtype=tf.int64)

thresh = 0

tf.raw_ops.SparseAdd(a_indices=a_indices, a_values=a_values, a_shape=a_shape, b_indices=b_indices, b_values=b_values, b_shape=b_shape, thresh=thresh) ```

The implementation has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of *_indices matches the size of corresponding *_shape. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.

Patches

We have patched the issue in GitHub commit 6fd02f44810754ae7481838b6a67c5df7f909ca3 followed by GitHub commit 41727ff06111117bdf86b37db198217fd7a143cc.

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Yakun Zhang and Ying Wang of Baidu X-Team.

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
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      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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      "ranges": [
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              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
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          ],
          "type": "ECOSYSTEM"
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      ]
    },
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
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              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
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    },
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        "name": "tensorflow-cpu"
      },
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        "name": "tensorflow-cpu"
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        "name": "tensorflow-cpu"
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        "name": "tensorflow-gpu"
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
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      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
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              "fixed": "2.4.2"
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          ],
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        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29609"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-665",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-17T22:09:32Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nIncomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data:\n\n```python\nimport tensorflow as tf\n\na_indices = tf.zeros([10, 97], dtype=tf.int64)\na_values = tf.zeros([10], dtype=tf.int64)\na_shape = tf.zeros([0], dtype=tf.int64)\n\nb_indices = tf.zeros([0, 0], dtype=tf.int64)\nb_values = tf.zeros([0], dtype=tf.int64)\nb_shape = tf.zeros([0], dtype=tf.int64)\n  \nthresh = 0\n\ntf.raw_ops.SparseAdd(a_indices=a_indices,\n                    a_values=a_values,\n                    a_shape=a_shape,\n                    b_indices=b_indices,\n                    b_values=b_values,\n                    b_shape=b_shape,\n                    thresh=thresh)\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation.\n\n### Patches\nWe have patched the issue in GitHub commit [6fd02f44810754ae7481838b6a67c5df7f909ca3](https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3) followed by GitHub commit  [41727ff06111117bdf86b37db198217fd7a143cc](https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc).\n\nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Yakun Zhang and Ying Wang of Baidu X-Team.",
  "id": "GHSA-cjc7-49v2-jp64",
  "modified": "2024-11-13T16:19:57Z",
  "published": "2021-05-21T14:28:29Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29609"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-537.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-735.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-246.yaml"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:L/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Incomplete validation in `SparseAdd`"
}

cve-2021-29609

Vulnerability from cvelistv5

Published

2021-05-14 19:20

Modified

2024-08-03 22:11

Severity ?

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

Summary

TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

References

▼	URL	Tags
	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3	x_refsource_MISC

Impacted products

Vendor

Product

Version

▼

tensorflow

Version: < 2.1.4
Version: >= 2.2.0, < 2.2.3
Version: >= 2.3.0, < 2.3.3
Version: >= 2.4.0, < 2.4.2

Show details on NVD website

JSON

To clipboard

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        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3"
        }
      ],
      "source": {
        "advisory": "GHSA-cjc7-49v2-jp64",
        "discovery": "UNKNOWN"
      },
      "title": "Incomplete validation in `SparseAdd`",
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2021-29609",
          "STATE": "PUBLIC",
          "TITLE": "Incomplete validation in `SparseAdd`"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "tensorflow",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "\u003c 2.1.4"
                          },
                          {
                            "version_value": "\u003e= 2.2.0, \u003c 2.2.3"
                          },
                          {
                            "version_value": "\u003e= 2.3.0, \u003c 2.3.3"
                          },
                          {
                            "version_value": "\u003e= 2.4.0, \u003c 2.4.2"
                          }
                        ]
                      }
                    }
                  ]
                },
                "vendor_name": "tensorflow"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "TensorFlow is an end-to-end open source platform for machine learning. Incomplete validation in `SparseAdd` results in allowing attackers to exploit undefined behavior (dereferencing null pointers) as well as write outside of bounds of heap allocated data. The implementation(https://github.com/tensorflow/tensorflow/blob/656e7673b14acd7835dc778867f84916c6d1cac2/tensorflow/core/kernels/sparse_add_op.cc) has a large set of validation for the two sparse tensor inputs (6 tensors in total), but does not validate that the tensors are not empty or that the second dimension of `*_indices` matches the size of corresponding `*_shape`. This allows attackers to send tensor triples that represent invalid sparse tensors to abuse code assumptions that are not protected by validation. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range."
            }
          ]
        },
        "impact": {
          "cvss": {
            "attackComplexity": "HIGH",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 5.3,
            "baseSeverity": "MEDIUM",
            "confidentialityImpact": "NONE",
            "integrityImpact": "LOW",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:L/A:H",
            "version": "3.1"
          }
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "CWE-665: Improper Initialization"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64",
              "refsource": "CONFIRM",
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cjc7-49v2-jp64"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/41727ff06111117bdf86b37db198217fd7a143cc"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/6fd02f44810754ae7481838b6a67c5df7f909ca3"
            }
          ]
        },
        "source": {
          "advisory": "GHSA-cjc7-49v2-jp64",
          "discovery": "UNKNOWN"
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2021-29609",
    "datePublished": "2021-05-14T19:20:52",
    "dateReserved": "2021-03-30T00:00:00",
    "dateUpdated": "2024-08-03T22:11:06.266Z",
    "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

pysec-2021-246

Vulnerability from pysec

ghsa-cjc7-49v2-jp64

Vulnerability from github

Impact

Patches

For more information

Attribution

cve-2021-29609

Vulnerability from cvelistv5

Tags

Sightings

Nomenclature