pysec - pysec-2021-389

pysec-2021-389

Vulnerability from pysec

Published

2021-11-05 20:15

Modified

2021-11-13 06:52

Details

TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. 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.

Aliases

JSON

To clipboard

{
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        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
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        "2.4.0rc4",
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        "2.4.2",
        "2.4.3",
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        "2.5.1",
        "2.6.0",
        "2.7.0rc0",
        "2.7.0rc1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41196",
    "GHSA-m539-j985-hcr8"
  ],
  "details": "TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. 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-2021-389",
  "modified": "2021-11-13T06:52:41.665281Z",
  "published": "2021-11-05T20:15:00Z",
  "references": [
    {
      "type": "REPORT",
      "url": "https://github.com/tensorflow/tensorflow/issues/51936"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b"
    }
  ]
}

ghsa-m539-j985-hcr8

Vulnerability from github

Published

2021-11-10 19:36

Modified

2024-11-13 21:46

Severity ?

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

Summary

Crash in `max_pool3d` when size argument is 0 or negative

Details

Impact

The Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative:

```python import tensorflow as tf

pool_size = [2, 2, 0] layer = tf.keras.layers.MaxPooling3D(strides=1, pool_size=pool_size) input_tensor = tf.random.uniform([3, 4, 10, 11, 12], dtype=tf.float32) res = layer(input_tensor) ```

This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive.

Patches

We have patched the issue in GitHub commit 12b1ff82b3f26ff8de17e58703231d5a02ef1b8b (merging #51975).

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 externally via a GitHub issue.

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
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              "fixed": "2.6.1"
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        "name": "tensorflow"
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        "name": "tensorflow"
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        "name": "tensorflow-cpu"
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        "name": "tensorflow-cpu"
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      "ranges": [
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            },
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              "fixed": "2.4.4"
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          ],
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        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41196"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-191"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-11-08T22:56:11Z",
    "nvd_published_at": "2021-11-05T20:15:00Z",
    "severity": "MODERATE"
  },
  "details": "### Impact\nThe Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative: \n\n```python\nimport tensorflow as tf\n\npool_size = [2, 2, 0]\nlayer = tf.keras.layers.MaxPooling3D(strides=1, pool_size=pool_size)\ninput_tensor = tf.random.uniform([3, 4, 10, 11, 12], dtype=tf.float32)\nres = layer(input_tensor)\n```\n\nThis is due to the TensorFlow\u0027s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive.\n\n### Patches\nWe have patched the issue in GitHub commit [12b1ff82b3f26ff8de17e58703231d5a02ef1b8b](https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b) (merging [#51975](https://github.com/tensorflow/tensorflow/pull/51975)).\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 externally via a [GitHub issue](https://github.com/tensorflow/tensorflow/issues/51936).\n",
  "id": "GHSA-m539-j985-hcr8",
  "modified": "2024-11-13T21:46:28Z",
  "published": "2021-11-10T19:36:21Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41196"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/issues/51936"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b"
    },
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      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-804.yaml"
    },
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      "type": "WEB",
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    },
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      "type": "PACKAGE",
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  "schema_version": "1.4.0",
  "severity": [
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      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Crash in `max_pool3d` when size argument is 0 or negative"
}

cve-2021-41196

Vulnerability from cvelistv5

Published

2021-11-05 19:55

Modified

2024-08-04 03:08

Severity ?

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

Summary

References

▼	URL	Tags
	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/issues/51936	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b	x_refsource_MISC

Impacted products

Vendor

Product

Version

▼

tensorflow

Version: >= 2.6.0, < 2.6.1
Version: >= 2.5.0, < 2.5.2
Version: < 2.4.4

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 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-2021-389

Vulnerability from pysec

ghsa-m539-j985-hcr8

Vulnerability from github

Impact

Patches

For more information

Attribution

cve-2021-41196

Vulnerability from cvelistv5

Tags

Sightings

Nomenclature