pysec - pysec-2021-689

pysec-2021-689

Vulnerability from pysec

Published

2021-05-14 20:15

Modified

2021-12-09 06:35

Details

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a CHECK-failure coming from the implementation of tf.raw_ops.RFFT. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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-gpu",
        "purl": "pkg:pypi/tensorflow-gpu"
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      "ranges": [
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          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
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          "events": [
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              "introduced": "0"
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            {
              "fixed": "2.2.0rc0"
            },
            {
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            {
              "fixed": "2.3.0rc0"
            },
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.4"
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            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.3"
            }
          ],
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      "versions": [
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        "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",
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        "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",
        "2.4.0",
        "2.4.1",
        "2.4.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29563",
    "GHSA-ph87-fvjr-v33w"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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-2021-689",
  "modified": "2021-12-09T06:35:25.642142Z",
  "published": "2021-05-14T20:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1"
    }
  ]
}

cve-2021-29563

Vulnerability from cvelistv5

Published

2021-05-14 19:17

Modified

2024-08-03 22:11

Severity ?

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

Summary

TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`. Eigen code operating on an empty matrix can trigger on an assertion and will cause program termination. 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-ph87-fvjr-v33w	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1	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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ghsa-ph87-fvjr-v33w

Vulnerability from github

Published

2021-05-21 14:25

Modified

2024-11-01 16:55

Severity ?

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

Summary

CHECK-fail in `tf.raw_ops.RFFT`

Details

Impact

An attacker can cause a denial of service by exploiting a CHECK-failure coming from the implementation of tf.raw_ops.RFFT:

```python import tensorflow as tf

inputs = tf.constant([1], shape=[1], dtype=tf.float32) fft_length = tf.constant([0], shape=[1], dtype=tf.int32)

tf.raw_ops.RFFT(input=inputs, fft_length=fft_length) ```

The above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.

Patches

We have patched the issue in GitHub commit 31bd5026304677faa8a0b77602c6154171b9aec1.

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"
            },
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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          "events": [
            {
              "introduced": "2.3.0"
            },
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              "fixed": "2.3.3"
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          ],
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        }
      ]
    },
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
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        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
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          ],
          "type": "ECOSYSTEM"
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    },
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        "name": "tensorflow-cpu"
      },
      "ranges": [
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    },
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        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
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        "name": "tensorflow-cpu"
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            },
            {
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          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
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        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
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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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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
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          "events": [
            {
              "introduced": "0"
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    },
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
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    },
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        "name": "tensorflow-gpu"
      },
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    },
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        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
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        {
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            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29563"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T19:46:06Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can cause a denial of service by exploiting a `CHECK`-failure coming from the implementation of `tf.raw_ops.RFFT`:\n    \n```python\nimport tensorflow as tf\n\ninputs = tf.constant([1], shape=[1], dtype=tf.float32)\nfft_length = tf.constant([0], shape=[1], dtype=tf.int32)\n\ntf.raw_ops.RFFT(input=inputs, fft_length=fft_length)\n```\n\nThe above example causes Eigen code to operate on an empty matrix. This triggers on an assertion and causes program termination.\n    \n### Patches\nWe have patched the issue in GitHub commit [31bd5026304677faa8a0b77602c6154171b9aec1](https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1).\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-ph87-fvjr-v33w",
  "modified": "2024-11-01T16:55:05Z",
  "published": "2021-05-21T14:25:05Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-ph87-fvjr-v33w"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29563"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/31bd5026304677faa8a0b77602c6154171b9aec1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-491.yaml"
    },
    {
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      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-689.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-200.yaml"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:P/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "CHECK-fail in `tf.raw_ops.RFFT`"
}

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-2021-689

Vulnerability from pysec

cve-2021-29563

Vulnerability from cvelistv5

ghsa-ph87-fvjr-v33w

Vulnerability from github

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature