PYSEC-2026-3158

Vulnerability from pysec - Published: 2026-07-09 16:49 - Updated: 2026-07-13 16:07
VLAI
Details

Impact

The implementation of ThreadPoolHandle can be used to trigger a denial of service attack by allocating too much memory:

import tensorflow as tf
y = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name='tf')

This is because the num_threads argument is only checked to not be negative, but there is no upper bound on its value.

Patches

We have patched the issue in GitHub commit e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e.

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 Yu Tian of Qihoo 360 AIVul Team.

Severity
4.3 (Medium)
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L
5.3 (Medium)
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
Impacted products
Name purl
tensorflow pkg:pypi/tensorflow
Aliases
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow",
        "purl": "pkg:pypi/tensorflow"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.5.3"
            },
            {
              "introduced": "2.6.0"
            },
            {
              "fixed": "2.6.3"
            },
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "2.7.0",
        "0.12.0",
        "0.12.1",
        "1.0.0",
        "1.0.1",
        "1.1.0",
        "1.10.0",
        "1.10.1",
        "1.11.0",
        "1.12.0",
        "1.12.2",
        "1.12.3",
        "1.13.1",
        "1.13.2",
        "1.14.0",
        "1.15.0",
        "1.15.2",
        "1.15.3",
        "1.15.4",
        "1.15.5",
        "1.2.0",
        "1.2.1",
        "1.3.0",
        "1.4.0",
        "1.4.1",
        "1.5.0",
        "1.5.1",
        "1.6.0",
        "1.7.0",
        "1.7.1",
        "1.8.0",
        "1.9.0",
        "2.0.0",
        "2.0.1",
        "2.0.2",
        "2.0.3",
        "2.0.4",
        "2.1.0",
        "2.1.1",
        "2.1.2",
        "2.1.3",
        "2.1.4",
        "2.2.0",
        "2.2.1",
        "2.2.2",
        "2.2.3",
        "2.3.0",
        "2.3.1",
        "2.3.2",
        "2.3.3",
        "2.3.4",
        "2.4.0",
        "2.4.1",
        "2.4.2",
        "2.4.3",
        "2.4.4",
        "2.5.0",
        "2.5.1",
        "2.5.2",
        "2.6.0",
        "2.6.1",
        "2.6.2"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-21732",
    "GHSA-c582-c96p-r5cq"
  ],
  "details": "### Impact \nThe [implementation of `ThreadPoolHandle`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135) can be used to trigger a denial of service attack by allocating too much memory:\n\n```python\nimport tensorflow as tf\ny = tf.raw_ops.ThreadPoolHandle(num_threads=0x60000000,display_name=\u0027tf\u0027)\n```\n\nThis is because the `num_threads` argument is only checked to not be negative, but there is no upper bound on its value.\n    \n### Patches\nWe have patched the issue in GitHub commit [e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e](https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e).\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 Yu Tian of Qihoo 360 AIVul Team.",
  "id": "PYSEC-2026-3158",
  "modified": "2026-07-13T16:07:02.991177Z",
  "published": "2026-07-09T16:49:43.776600Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-c582-c96p-r5cq"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-21732"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/e3749a6d5d1e8d11806d4a2e9cc3123d1a90b75e"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-56.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-111.yaml"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/data/experimental/threadpool_dataset_op.cc#L79-L135"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/tensorflow"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-c582-c96p-r5cq"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:L",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Memory exhaustion in Tensorflow"
}



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