GHSA-PVRC-HG3F-58R6

Vulnerability from github – Published: 2021-05-21 14:25 – Updated: 2024-11-01 17:03
VLAI?
Summary
Heap OOB access in `Dilation2DBackpropInput`
Details

Impact

An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to tf.raw_ops.Dilation2DBackpropInput:

import tensorflow as tf

input_tensor = tf.constant([1.1] * 81, shape=[3, 3, 3, 3], dtype=tf.float32)
filter = tf.constant([], shape=[0, 0, 3], dtype=tf.float32)
out_backprop = tf.constant([1.1] * 1062, shape=[3, 2, 59, 3], dtype=tf.float32)

tf.raw_ops.Dilation2DBackpropInput(
  input=input_tensor, filter=filter, out_backprop=out_backprop, 
  strides=[1, 40, 1, 1], rates=[1, 56, 56, 1], padding='VALID')

This is because the implementation does not validate before writing to the output array.

in_backprop(b, h_in_max, w_in_max, d) += out_backprop(b, h_out, w_out, d);

The values for h_out and w_out are guaranteed to be in range for out_backprop (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating h_in_max/w_in_max and in_backprop.

Patches

We have patched the issue in GitHub commit 3f6fe4dfef6f57e768260b48166c27d148f3015f.

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.

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
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{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
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            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
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        }
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
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            {
              "introduced": "2.3.0"
            },
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              "fixed": "2.3.3"
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          "type": "ECOSYSTEM"
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        "name": "tensorflow"
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
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          "events": [
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              "fixed": "2.2.3"
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      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
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              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
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          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
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          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.1.4"
            }
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          "type": "ECOSYSTEM"
        }
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    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.2.0"
            },
            {
              "fixed": "2.2.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "2.3.0"
            },
            {
              "fixed": "2.3.3"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    },
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-gpu"
      },
      "ranges": [
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            {
              "introduced": "2.4.0"
            },
            {
              "fixed": "2.4.2"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2021-29566"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-787"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T19:22:37Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nAn attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`:\n\n```python\nimport tensorflow as tf\n    \ninput_tensor = tf.constant([1.1] * 81, shape=[3, 3, 3, 3], dtype=tf.float32)\nfilter = tf.constant([], shape=[0, 0, 3], dtype=tf.float32)\nout_backprop = tf.constant([1.1] * 1062, shape=[3, 2, 59, 3], dtype=tf.float32)\n\ntf.raw_ops.Dilation2DBackpropInput(\n  input=input_tensor, filter=filter, out_backprop=out_backprop, \n  strides=[1, 40, 1, 1], rates=[1, 56, 56, 1], padding=\u0027VALID\u0027)\n```\n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array.\n  \n```cc               \nin_backprop(b, h_in_max, w_in_max, d) += out_backprop(b, h_out, w_out, d);\n```                 \n    \nThe values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`.\n\n### Patches\nWe have patched the issue in GitHub commit [3f6fe4dfef6f57e768260b48166c27d148f3015f](https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f).\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-pvrc-hg3f-58r6",
  "modified": "2024-11-01T17:03:51Z",
  "published": "2021-05-21T14:25:13Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pvrc-hg3f-58r6"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29566"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-494.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-692.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-203.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": "Heap OOB access in `Dilation2DBackpropInput`"
}


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