pysec - pysec-2021-828

PYSEC-2021-828

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 code for the Cudnn* operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the input, input_h and input_c parameters are not validated, but code assumes they have certain values. 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-gpu	pkg:pypi/tensorflow-gpu

Aliases

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu",
        "purl": "pkg:pypi/tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "af5fcebb37c8b5d71c237f4e59c6477015c78ce6"
            }
          ],
          "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": [
        "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",
        "2.5.0",
        "2.5.1",
        "2.6.0",
        "2.7.0rc0",
        "2.7.0rc1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41221",
    "GHSA-cqv6-3phm-hcwx"
  ],
  "details": "TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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-2021-828",
  "modified": "2021-12-09T06:35:44.302427Z",
  "published": "2021-11-05T23:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6"
    }
  ]
}

CVE-2021-41221 (GCVE-0-2021-41221)

Vulnerability from cvelistv5 – Published: 2021-11-05 22:15 – Updated: 2024-08-04 03:08

Summary

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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 ?

7.8 (High)


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

{
  "containers": {
    "adp": [
      {
        "providerMetadata": {
          "dateUpdated": "2024-08-04T03:08:31.404Z",
          "orgId": "af854a3a-2127-422b-91ae-364da2661108",
          "shortName": "CVE"
        },
        "references": [
          {
            "tags": [
              "x_refsource_CONFIRM",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx"
          },
          {
            "tags": [
              "x_refsource_MISC",
              "x_transferred"
            ],
            "url": "https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6"
          }
        ],
        "title": "CVE Program Container"
      }
    ],
    "cna": {
      "affected": [
        {
          "product": "tensorflow",
          "vendor": "tensorflow",
          "versions": [
            {
              "status": "affected",
              "version": "\u003e= 2.6.0, \u003c 2.6.1"
            },
            {
              "status": "affected",
              "version": "\u003e= 2.5.0, \u003c 2.5.2"
            },
            {
              "status": "affected",
              "version": "\u003c 2.4.4"
            }
          ]
        }
      ],
      "descriptions": [
        {
          "lang": "en",
          "value": "TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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."
        }
      ],
      "metrics": [
        {
          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 7.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        }
      ],
      "problemTypes": [
        {
          "descriptions": [
            {
              "cweId": "CWE-120",
              "description": "CWE-120: Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)",
              "lang": "en",
              "type": "CWE"
            }
          ]
        }
      ],
      "providerMetadata": {
        "dateUpdated": "2021-11-05T22:15:11",
        "orgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
        "shortName": "GitHub_M"
      },
      "references": [
        {
          "tags": [
            "x_refsource_CONFIRM"
          ],
          "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx"
        },
        {
          "tags": [
            "x_refsource_MISC"
          ],
          "url": "https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6"
        }
      ],
      "source": {
        "advisory": "GHSA-cqv6-3phm-hcwx",
        "discovery": "UNKNOWN"
      },
      "title": "Access to invalid memory during shape inference in `Cudnn*` ops",
      "x_legacyV4Record": {
        "CVE_data_meta": {
          "ASSIGNER": "security-advisories@github.com",
          "ID": "CVE-2021-41221",
          "STATE": "PUBLIC",
          "TITLE": "Access to invalid memory during shape inference in `Cudnn*` ops"
        },
        "affects": {
          "vendor": {
            "vendor_data": [
              {
                "product": {
                  "product_data": [
                    {
                      "product_name": "tensorflow",
                      "version": {
                        "version_data": [
                          {
                            "version_value": "\u003e= 2.6.0, \u003c 2.6.1"
                          },
                          {
                            "version_value": "\u003e= 2.5.0, \u003c 2.5.2"
                          },
                          {
                            "version_value": "\u003c 2.4.4"
                          }
                        ]
                      }
                    }
                  ]
                },
                "vendor_name": "tensorflow"
              }
            ]
          }
        },
        "data_format": "MITRE",
        "data_type": "CVE",
        "data_version": "4.0",
        "description": {
          "description_data": [
            {
              "lang": "eng",
              "value": "TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow. This occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values. 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."
            }
          ]
        },
        "impact": {
          "cvss": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 7.8,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "HIGH",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
            "vectorString": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H",
            "version": "3.1"
          }
        },
        "problemtype": {
          "problemtype_data": [
            {
              "description": [
                {
                  "lang": "eng",
                  "value": "CWE-120: Buffer Copy without Checking Size of Input (\u0027Classic Buffer Overflow\u0027)"
                }
              ]
            }
          ]
        },
        "references": {
          "reference_data": [
            {
              "name": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx",
              "refsource": "CONFIRM",
              "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx"
            },
            {
              "name": "https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6",
              "refsource": "MISC",
              "url": "https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6"
            }
          ]
        },
        "source": {
          "advisory": "GHSA-cqv6-3phm-hcwx",
          "discovery": "UNKNOWN"
        }
      }
    }
  },
  "cveMetadata": {
    "assignerOrgId": "a0819718-46f1-4df5-94e2-005712e83aaa",
    "assignerShortName": "GitHub_M",
    "cveId": "CVE-2021-41221",
    "datePublished": "2021-11-05T22:15:11",
    "dateReserved": "2021-09-15T00:00:00",
    "dateUpdated": "2024-08-04T03:08:31.404Z",
    "state": "PUBLISHED"
  },
  "dataType": "CVE_RECORD",
  "dataVersion": "5.1"
}

GHSA-CQV6-3PHM-HCWX

Vulnerability from github – Published: 2021-11-10 18:50 – Updated: 2024-11-07 22:10

Summary

Access to invalid memory during shape inference in `Cudnn*` ops

Details

Impact

The shape inference code for the Cudnn* operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow:

import tensorflow as tf

@tf.function
def func():
  return tf.raw_ops.CudnnRNNV3(
    input=[0.1, 0.1],
    input_h=[0.5],
    input_c=[0.1, 0.1, 0.1], 
    params=[0.5, 0.5],
    sequence_lengths=[-1, 0, 1])

func()

This occurs because the ranks of the input, input_h and input_c parameters are not validated, but code assumes they have certain values:

auto input_shape = c->input(0);
auto input_h_shape = c->input(1);
auto seq_length = c->Dim(input_shape, 0);
auto batch_size = c->Dim(input_shape, 1);  // assumes rank >= 2
auto num_units = c->Dim(input_h_shape, 2); // assumes rank >= 3

Patches

We have patched the issue in GitHub commit af5fcebb37c8b5d71c237f4e59c6477015c78ce6.

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 ?

7.8 (High)


                  
                    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/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-2021-41221"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-120",
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-11-08T22:02:26Z",
    "nvd_published_at": "2021-11-05T23:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nThe [shape inference code](https://github.com/tensorflow/tensorflow/blob/9ff27787893f76d6971dcd1552eb5270d254f31b/tensorflow/core/ops/cudnn_rnn_ops.cc) for the `Cudnn*` operations in TensorFlow can be tricked into accessing invalid memory, via a heap buffer overflow:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef func():\n  return tf.raw_ops.CudnnRNNV3(\n    input=[0.1, 0.1],\n    input_h=[0.5],\n    input_c=[0.1, 0.1, 0.1], \n    params=[0.5, 0.5],\n    sequence_lengths=[-1, 0, 1])\n  \nfunc() \n```\n  \nThis occurs because the ranks of the `input`, `input_h` and `input_c` parameters are not validated, but code assumes they have certain values:\n\n```cc\nauto input_shape = c-\u003einput(0);\nauto input_h_shape = c-\u003einput(1);\nauto seq_length = c-\u003eDim(input_shape, 0);\nauto batch_size = c-\u003eDim(input_shape, 1);  // assumes rank \u003e= 2\nauto num_units = c-\u003eDim(input_h_shape, 2); // assumes rank \u003e= 3\n``` \n\n### Patches\nWe have patched the issue in GitHub commit [af5fcebb37c8b5d71c237f4e59c6477015c78ce6](https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6).\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-cqv6-3phm-hcwx",
  "modified": "2024-11-07T22:10:37Z",
  "published": "2021-11-10T18:50:17Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cqv6-3phm-hcwx"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41221"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/af5fcebb37c8b5d71c237f4e59c6477015c78ce6"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-630.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-828.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-413.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:H/I:H/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Access to invalid memory during shape inference in `Cudnn*` ops"
}

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-2021-828

CVE-2021-41221 (GCVE-0-2021-41221)

GHSA-CQV6-3PHM-HCWX

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature