ghsa-545v-42p7-98fq
Vulnerability from github
Published
2021-05-21 14:25
Modified
2024-11-01 17:06
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
Heap out of bounds read in `MaxPoolGradWithArgmax`
Details

Impact

The implementation of tf.raw_ops.MaxPoolGradWithArgmax can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:

```python import tensorflow as tf

input = tf.constant([10.0, 10.0, 10.0], shape=[1, 1, 3, 1], dtype=tf.float32) grad = tf.constant([10.0, 10.0, 10.0, 10.0], shape=[1, 1, 1, 4], dtype=tf.float32) argmax = tf.constant([1], shape=[1], dtype=tf.int64) ksize = [1, 1, 1, 1] strides = [1, 1, 1, 1]

tf.raw_ops.MaxPoolGradWithArgmax( input=input, grad=grad, argmax=argmax, ksize=ksize, strides=strides, padding='SAME', include_batch_in_index=False) ```

The implementation uses the same value to index in two different arrays but there is no guarantee that the sizes are identical.

Patches

We have patched the issue in GitHub commit dcd7867de0fea4b72a2b34bd41eb74548dc23886.

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 Ying Wang and Yakun Zhang of Baidu X-Team.

Show details on source website

To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow"
      },
      "ranges": [
        {
          "events": [
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  ],
  "aliases": [
    "CVE-2021-29570"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-125"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2021-05-18T18:54:55Z",
    "nvd_published_at": "2021-05-14T20:15:00Z",
    "severity": "LOW"
  },
  "details": "### Impact\nThe implementation of `tf.raw_ops.MaxPoolGradWithArgmax` can cause reads outside of bounds of heap allocated data if attacker supplies specially crafted inputs:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant([10.0, 10.0, 10.0], shape=[1, 1, 3, 1], dtype=tf.float32)\ngrad = tf.constant([10.0, 10.0, 10.0, 10.0], shape=[1, 1, 1, 4], dtype=tf.float32)\nargmax = tf.constant([1], shape=[1], dtype=tf.int64)\nksize = [1, 1, 1, 1]\nstrides = [1, 1, 1, 1]\n  \ntf.raw_ops.MaxPoolGradWithArgmax(\n  input=input, grad=grad, argmax=argmax, ksize=ksize, strides=strides,\n  padding=\u0027SAME\u0027, include_batch_in_index=False)\n```\n\nThe [implementation](https://github.com/tensorflow/tensorflow/blob/ef0c008ee84bad91ec6725ddc42091e19a30cf0e/tensorflow/core/kernels/maxpooling_op.cc#L1016-L1017) uses the same value to index in two different arrays but there is no guarantee that the sizes are identical. \n\n### Patches\nWe have patched the issue in GitHub commit [dcd7867de0fea4b72a2b34bd41eb74548dc23886](https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886).\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 Ying Wang and Yakun Zhang of Baidu X-Team.",
  "id": "GHSA-545v-42p7-98fq",
  "modified": "2024-11-01T17:06:23Z",
  "published": "2021-05-21T14:25:25Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-545v-42p7-98fq"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2021-29570"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/dcd7867de0fea4b72a2b34bd41eb74548dc23886"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-498.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-696.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-207.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 out of bounds read in `MaxPoolGradWithArgmax`"
}


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