pysec - pysec-2021-620

pysec-2021-620

Vulnerability from pysec

Published

2021-11-05 21:15

Modified

2021-12-09 06:35

Details

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array. This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start of a heap buffer. The code allows axis to be an optional argument (s would contain an error::NOT_FOUND error code). Otherwise, it assumes that axis is a valid index into the dimensions of the input tensor. If axis is less than -1 then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

Aliases

JSON

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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "a0d64445116c43cf46a5666bd4eee28e7a82f244"
            }
          ],
          "repo": "https://github.com/tensorflow/tensorflow",
          "type": "GIT"
        },
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            },
            {
              "introduced": "2.7.0rc0"
            },
            {
              "fixed": "2.7.0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.6.0",
        "2.7.0rc0",
        "2.7.0rc1"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41211",
    "GHSA-cvgx-3v3q-m36c"
  ],
  "details": "TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.",
  "id": "PYSEC-2021-620",
  "modified": "2021-12-09T06:35:09.057312Z",
  "published": "2021-11-05T21:15:00Z",
  "references": [
    {
      "type": "ADVISORY",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c"
    },
    {
      "type": "FIX",
      "url": "https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244"
    }
  ]
}

cve-2021-41211

Vulnerability from cvelistv5

Published

2021-11-05 20:15

Modified

2024-08-04 03:08

Severity ?

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

Summary

TensorFlow is an open source platform for machine learning. In affected versions the shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array. This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer. The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

References

▼	URL	Tags
	https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c	x_refsource_CONFIRM
	https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244	x_refsource_MISC

Impacted products

Vendor

Product

Version

▼

tensorflow

Version: >= 2.6.0, < 2.6.1

Show details on NVD website

JSON

To clipboard

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        }
      ],
      "metrics": [
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          "cvssV3_1": {
            "attackComplexity": "LOW",
            "attackVector": "LOCAL",
            "availabilityImpact": "HIGH",
            "baseScore": 7.1,
            "baseSeverity": "HIGH",
            "confidentialityImpact": "HIGH",
            "integrityImpact": "NONE",
            "privilegesRequired": "LOW",
            "scope": "UNCHANGED",
            "userInteraction": "NONE",
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ghsa-cvgx-3v3q-m36c

Vulnerability from github

Published

2021-11-10 19:01

Modified

2024-11-07 22:18

Severity ?

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

Summary

Heap OOB in shape inference for `QuantizeV2`

Details

Impact

The shape inference code for QuantizeV2 can trigger a read outside of bounds of heap allocated array:

```python import tensorflow as tf

@tf.function def test(): data=tf.raw_ops.QuantizeV2( input=[1.0,1.0], min_range=[1.0,10.0], max_range=[1.0,10.0], T=tf.qint32, mode='MIN_COMBINED', round_mode='HALF_TO_EVEN', narrow_range=False, axis=-100, ensure_minimum_range=10) return data

test() ```

This occurs whenever axis is a negative value less than -1. In this case, we are accessing data before the start of a heap buffer:

cc int axis = -1; Status s = c->GetAttr("axis", &axis); if (!s.ok() && s.code() != error::NOT_FOUND) { return s; } ... if (axis != -1) { ... TF_RETURN_IF_ERROR( c->Merge(c->Dim(minmax, 0), c->Dim(input, axis), &depth)); }

The code allows axis to be an optional argument (s would contain an error::NOT_FOUND error code). Otherwise, it assumes that axis is a valid index into the dimensions of the input tensor. If axis is less than -1 then this results in a heap OOB read.

Patches

We have patched the issue in GitHub commit a0d64445116c43cf46a5666bd4eee28e7a82f244.

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.

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.

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"
        }
      ],
      "versions": [
        "2.6.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.6.0"
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.6.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2021-41211"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-11-08T22:32:45Z",
    "nvd_published_at": "2021-11-05T21:15:00Z",
    "severity": "HIGH"
  },
  "details": "### Impact\nThe [shape inference code for `QuantizeV2`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/framework/common_shape_fns.cc#L2509-L2530) can trigger a read outside of bounds of heap allocated array:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef test():\n  data=tf.raw_ops.QuantizeV2(\n    input=[1.0,1.0],\n    min_range=[1.0,10.0],\n    max_range=[1.0,10.0],\n    T=tf.qint32,\n    mode=\u0027MIN_COMBINED\u0027,\n    round_mode=\u0027HALF_TO_EVEN\u0027,\n    narrow_range=False,\n    axis=-100,\n    ensure_minimum_range=10)\n  return data\n\ntest()\n```\n\nThis occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer:\n    \n```cc\nint axis = -1;\nStatus s = c-\u003eGetAttr(\"axis\", \u0026axis);\nif (!s.ok() \u0026\u0026 s.code() != error::NOT_FOUND) {\n  return s;\n}   \n... \nif (axis != -1) {\n  ...\n  TF_RETURN_IF_ERROR(\n      c-\u003eMerge(c-\u003eDim(minmax, 0), c-\u003eDim(input, axis), \u0026depth));\n}\n```\n\nThe code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read.\n    \n### Patches\nWe have patched the issue in GitHub commit [a0d64445116c43cf46a5666bd4eee28e7a82f244](https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244).\n    \nThe fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected.\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-cvgx-3v3q-m36c",
  "modified": "2024-11-07T22:18:59Z",
  "published": "2021-11-10T19:01:03Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cvgx-3v3q-m36c"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-41211"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/a0d64445116c43cf46a5666bd4eee28e7a82f244"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-620.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-818.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-403.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:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Heap OOB in shape inference for `QuantizeV2`"
}

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-2021-620

Vulnerability from pysec

cve-2021-41211

Vulnerability from cvelistv5

ghsa-cvgx-3v3q-m36c

Vulnerability from github

Impact

Patches

For more information

Attribution

Tags

Sightings

Nomenclature