Vulnerability-Lookup

PYSEC-2021-625

Vulnerability from pysec - Published: 2021-11-05 23:15 - Updated: 2021-12-09 06:35

Details

TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for Transpose is vulnerable to a heap buffer overflow. This occurs whenever perm contains negative elements. The shape inference function does not validate that the indices in perm are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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": [
            {
              "introduced": "0"
            },
            {
              "fixed": "c79ba87153ee343401dbe9d1954d7f79e521eb14"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            },
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            },
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            },
            {
              "introduced": "2.7.0rc0"
            },
            {
              "fixed": "2.7.0"
            }
          ],
          "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",
        "2.5.0",
        "2.5.1",
        "2.6.0",
        "2.7.0rc0",
        "2.7.0rc1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41216",
    "GHSA-3ff2-r28g-w7h9"
  ],
  "details": "TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.",
  "id": "PYSEC-2021-625",
  "modified": "2021-12-09T06:35:09.827396Z",
  "published": "2021-11-05T23:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3ff2-r28g-w7h9"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14"
    }
  ]
}

GHSA-3FF2-R28G-W7H9

Vulnerability from github – Published: 2021-11-10 18:57 – Updated: 2024-11-07 22:16

Summary

Heap buffer overflow in `Transpose`

Details

Impact

The shape inference function for Transpose is vulnerable to a heap buffer overflow:

import tensorflow as tf
@tf.function
def test():
  y = tf.raw_ops.Transpose(x=[1,2,3,4],perm=[-10])
  return y

test()

This occurs whenever perm contains negative elements. The shape inference function does not validate that the indices in perm are all valid:

for (int32_t i = 0; i < rank; ++i) {
  int64_t in_idx = data[i];
  if (in_idx >= rank) {
    return errors::InvalidArgument("perm dim ", in_idx,
                                   " is out of range of input rank ", rank);
  }
  dims[i] = c->Dim(input, in_idx);
}

where Dim(tensor, index) accepts either a positive index less than the rank of the tensor or the special value -1 for unknown dimensions.

Patches

We have patched the issue in GitHub commit c79ba87153ee343401dbe9d1954d7f79e521eb14.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 ?

5.5 (Medium)


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

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.5.0"
            },
            {
              "fixed": "2.5.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.4.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41216"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-120",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-11-08T22:21:10Z",
    "nvd_published_at": "2021-11-05T23:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe [shape inference function for `Transpose`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/array_ops.cc#L121-L185) is vulnerable to a heap buffer overflow:\n\n```python\nimport tensorflow as tf\n@tf.function\ndef test():\n  y = tf.raw_ops.Transpose(x=[1,2,3,4],perm=[-10])\n  return y\n\ntest()\n```\n\nThis occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid:\n        \n```cc\nfor (int32_t i = 0; i \u003c rank; ++i) {\n  int64_t in_idx = data[i];\n  if (in_idx \u003e= rank) {\n    return errors::InvalidArgument(\"perm dim \", in_idx,\n                                   \" is out of range of input rank \", rank);\n  }\n  dims[i] = c-\u003eDim(input, in_idx);\n}\n```\n\nwhere `Dim(tensor, index)` accepts either a positive index less than the rank of the tensor or the special value `-1` for unknown dimensions.\n\n### Patches\nWe have patched the issue in GitHub commit [c79ba87153ee343401dbe9d1954d7f79e521eb14](https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14).\n\nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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-3ff2-r28g-w7h9",
  "modified": "2024-11-07T22:16:21Z",
  "published": "2021-11-10T18:57:19Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3ff2-r28g-w7h9"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41216"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-625.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-823.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-408.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/array_ops.cc#L121-L185"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Heap buffer overflow in `Transpose`"
}

CVE-2021-41216 (GCVE-0-2021-41216)

Vulnerability from cvelistv5 – Published: 2021-11-05 22:10 – Updated: 2024-08-04 03:08

Title

Heap buffer overflow in `Transpose`

Summary

TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

Severity ?

5.5 (Medium)


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

CWE

CWE-120 - Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')

Assigner

GitHub_M

References

URL

Tags

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

Impacted products

	Vendor	Product	Version
	tensorflow	tensorflow	Affected: >= 2.6.0, < 2.6.1 Affected: >= 2.5.0, < 2.5.2 Affected: < 2.4.4

Show details on NVD website

JSON

To clipboard

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Sightings

Author	Source	Type	Date	Other

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-2021-625

GHSA-3FF2-R28G-W7H9

Impact

Patches

For more information

Attribution

CVE-2021-41216 (GCVE-0-2021-41216)

Tags

Sightings

Nomenclature