pysec - pysec-2022-61

pysec-2022-61

Vulnerability from pysec

Published

2022-02-03 14:15

Modified

2022-03-09 00:17

Details

Tensorflow is an Open Source Machine Learning Framework. The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

Impacted products

Name	purl
tensorflow-cpu	pkg:pypi/tensorflow-cpu

Aliases

JSON

To clipboard

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        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
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  "id": "PYSEC-2022-61",
  "modified": "2022-03-09T00:17:31.433747Z",
  "published": "2022-02-03T14:15:00Z",
  "references": [
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      "type": "ADVISORY",
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    }
  ]
}

CVE-2022-21737 (GCVE-0-2022-21737)

Vulnerability from cvelistv5

Published

2022-02-03 13:43

Modified

2025-05-05 16:31

Severity ?

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

CWE

Summary

Tensorflow is an Open Source Machine Learning Framework. The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

References

►

URL

Tags

	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f2vv-v9cg-qhh7	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9	x_refsource_MISC
	https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/bincount_op.cc	x_refsource_MISC

Impacted products

	Vendor	Product	Version
	n/a	n/a	Version: n/a

Show details on NVD website

JSON

To clipboard

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ghsa-f2vv-v9cg-qhh7

Vulnerability from github

Published

2022-02-09 23:43

Modified

2024-11-13 22:32

Severity ?

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

Summary

Assertion failure based denial of service in Tensorflow

Details

Impact

The implementation of *Bincount operations allows malicious users to cause denial of service by passing in arguments which would trigger a CHECK-fail:

```python import tensorflow as tf

tf.raw_ops.DenseBincount( input=[[0], [1], [2]], size=[1], weights=[3,2,1], binary_output=False) ```

There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in CHECK failures later when the output tensors get allocated.

Patches

We have patched the issue in GitHub commit 7019ce4f68925fd01cdafde26f8d8c938f47e6f9.

The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.

Show details on source website

JSON

To clipboard

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
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          "events": [
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      ],
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        "2.7.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-21737"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-617",
      "CWE-754"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2022-02-03T19:59:49Z",
    "nvd_published_at": "2022-02-03T14:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact \nThe [implementation of `*Bincount` operations](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/bincount_op.cc) allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.DenseBincount(\n  input=[[0], [1], [2]],\n  size=[1],\n  weights=[3,2,1],\n  binary_output=False)\n```\n\nThere are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated.\n\n### Patches\nWe have patched the issue in GitHub commit [7019ce4f68925fd01cdafde26f8d8c938f47e6f9](https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9).\n\nThe fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.",
  "id": "GHSA-f2vv-v9cg-qhh7",
  "modified": "2024-11-13T22:32:39Z",
  "published": "2022-02-09T23:43:48Z",
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      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f2vv-v9cg-qhh7"
    },
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      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21737"
    },
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      "url": "https://github.com/tensorflow/tensorflow/commit/7019ce4f68925fd01cdafde26f8d8c938f47e6f9"
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      "type": "CVSS_V4"
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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-2022-61

Vulnerability from pysec

CVE-2022-21737 (GCVE-0-2022-21737)

Vulnerability from cvelistv5

ghsa-f2vv-v9cg-qhh7

Vulnerability from github

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature