pysec - pysec-2021-492

pysec-2021-492

Vulnerability from pysec

Published

2021-05-14 20:15

Modified

2021-12-09 06:34

Details

TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of tf.raw_ops.EditDistance. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters. 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-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
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        "2.1.2",
        "2.1.3",
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        "2.2.1",
        "2.2.2",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.4.0",
        "2.4.1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29564",
    "GHSA-75f6-78jr-4656"
  ],
  "details": "TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters. 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-2021-492",
  "modified": "2021-12-09T06:34:53.290029Z",
  "published": "2021-05-14T20:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-75f6-78jr-4656"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3"
    }
  ]
}

cve-2021-29564

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 trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters. 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-75f6-78jr-4656	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3	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-75f6-78jr-4656

Vulnerability from github

Published

2021-05-21 14:25

Modified

2024-11-01 16:54

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

Null pointer dereference in `EditDistance`

Details

Impact

An attacker can trigger a null pointer dereference in the implementation of tf.raw_ops.EditDistance:

```python import tensorflow as tf

hypothesis_indices = tf.constant([247, 247, 247], shape=[1, 3], dtype=tf.int64) hypothesis_values = tf.constant([-9.9999], shape=[1], dtype=tf.float32) hypothesis_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64) truth_indices = tf.constant([], shape=[0, 3], dtype=tf.int64) truth_values = tf.constant([], shape=[0], dtype=tf.float32) truth_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)

tf.raw_ops.EditDistance( hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values, hypothesis_shape=hypothesis_shape, truth_indices=truth_indices, truth_values=truth_values, truth_shape=truth_shape, normalize=True) ```

This is because the implementation has incomplete validation of the input parameters.

In the above scenario, an attacker causes an allocation of an empty tensor for the output:

cc OP_REQUIRES_OK(ctx, ctx->allocate_output("output", output_shape, &output)); auto output_t = output->flat<float>(); output_t.setZero();

Because output_shape has 0 elements, the result of output->flat<T>() has an empty buffer, so calling setZero would result in a null dereference.

Patches

We have patched the issue in GitHub commit f4c364a5d6880557f6f5b6eb5cee2c407f0186b3.

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"
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          "type": "ECOSYSTEM"
        }
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    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
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      "ranges": [
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          "type": "ECOSYSTEM"
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        "name": "tensorflow"
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        "name": "tensorflow"
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        "name": "tensorflow-gpu"
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              "introduced": "2.3.0"
            },
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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"
            },
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              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
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  "aliases": [
    "CVE-2021-29564"
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  "database_specific": {
    "cwe_ids": [
      "CWE-476"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T19:43:25Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can trigger a null pointer dereference in the implementation of `tf.raw_ops.EditDistance`: \n    \n```python\nimport tensorflow as tf\n\nhypothesis_indices = tf.constant([247, 247, 247], shape=[1, 3], dtype=tf.int64)\nhypothesis_values = tf.constant([-9.9999], shape=[1], dtype=tf.float32)\nhypothesis_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)\ntruth_indices = tf.constant([], shape=[0, 3], dtype=tf.int64)\ntruth_values = tf.constant([], shape=[0], dtype=tf.float32)\ntruth_shape = tf.constant([0, 0, 0], shape=[3], dtype=tf.int64)\n\ntf.raw_ops.EditDistance(\n    hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values,\n    hypothesis_shape=hypothesis_shape, truth_indices=truth_indices,\n    truth_values=truth_values, truth_shape=truth_shape, normalize=True)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/79865b542f9ffdc9caeb255631f7c56f1d4b6517/tensorflow/core/kernels/edit_distance_op.cc#L103-L159) has incomplete validation of the input parameters.\n\nIn the above scenario, an attacker causes an allocation of an empty tensor for the output:\n\n```cc\nOP_REQUIRES_OK(ctx, ctx-\u003eallocate_output(\"output\", output_shape, \u0026output));\nauto output_t = output-\u003eflat\u003cfloat\u003e();\noutput_t.setZero();\n```\n\nBecause `output_shape` has 0 elements, the result of `output-\u003eflat\u003cT\u003e()` has an empty buffer, so calling `setZero` would result in a null dereference.\n\n### Patches\nWe have patched the issue in GitHub commit [f4c364a5d6880557f6f5b6eb5cee2c407f0186b3](https://github.com/tensorflow/tensorflow/commit/f4c364a5d6880557f6f5b6eb5cee2c407f0186b3).\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-75f6-78jr-4656",
  "modified": "2024-11-01T16:54:25Z",
  "published": "2021-05-21T14:25:08Z",
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    },
    {
      "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": "Null pointer dereference in `EditDistance`"
}

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-2021-492

Vulnerability from pysec

cve-2021-29564

Vulnerability from cvelistv5

ghsa-75f6-78jr-4656

Vulnerability from github

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature