PYSEC-2026-3358

Vulnerability from pysec - Published: 2026-07-09 16:49 - Updated: 2026-07-13 16:06
VLAI
Details

Impact

The implementation of tf.raw_ops.QuantizedConv2D does not fully validate the input arguments:

import tensorflow as tf

input = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)
filter = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)

# bad args
min_input = tf.constant([], shape=[0], dtype=tf.float32)
max_input = tf.constant(0, shape=[], dtype=tf.float32)
min_filter = tf.constant(0, shape=[], dtype=tf.float32)
max_filter = tf.constant(0, shape=[], dtype=tf.float32)

tf.raw_ops.QuantizedConv2D(
  input=input,
  filter=filter,
  min_input=min_input,
  max_input=max_input,
  min_filter=min_filter,
  max_filter=max_filter, 
  strides=[1, 1, 1, 1],
  padding="SAME")

In this case, references get bound to nullptr for each argument that is empty (in the example, all arguments in the bad args section).

Patches

We have patched the issue in GitHub commit 0f0b080ecde4d3dfec158d6f60da34d5e31693c4.

The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.

Severity
5.5 (Medium)
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Impacted products
Name purl
tensorflow-cpu pkg:pypi/tensorflow-cpu
Aliases
To clipboard 

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "tensorflow-cpu",
        "purl": "pkg:pypi/tensorflow-cpu"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "2.6.4"
            },
            {
              "introduced": "2.7.0"
            },
            {
              "fixed": "2.7.2"
            },
            {
              "introduced": "2.8.0"
            },
            {
              "fixed": "2.8.1"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ],
      "versions": [
        "1.15.0",
        "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",
        "2.5.3",
        "2.6.0",
        "2.6.1",
        "2.6.2",
        "2.6.3",
        "2.7.0",
        "2.7.1",
        "2.8.0"
      ]
    }
  ],
  "aliases": [
    "CVE-2022-29201",
    "GHSA-pqhm-4wvf-2jg8"
  ],
  "details": "### Impact\nThe implementation of [`tf.raw_ops.QuantizedConv2D`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantized_conv_ops.cc) does not fully validate the input arguments:\n\n```python\nimport tensorflow as tf\n\ninput = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)\nfilter = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8)\n\n# bad args\nmin_input = tf.constant([], shape=[0], dtype=tf.float32)\nmax_input = tf.constant(0, shape=[], dtype=tf.float32)\nmin_filter = tf.constant(0, shape=[], dtype=tf.float32)\nmax_filter = tf.constant(0, shape=[], dtype=tf.float32)\n\ntf.raw_ops.QuantizedConv2D(\n  input=input,\n  filter=filter,\n  min_input=min_input,\n  max_input=max_input,\n  min_filter=min_filter,\n  max_filter=max_filter, \n  strides=[1, 1, 1, 1],\n  padding=\"SAME\")\n```\n\nIn this case, references get bound to `nullptr` for each argument that is empty (in the example, all arguments in the `bad args` section).\n\n### Patches\nWe have patched the issue in GitHub commit [0f0b080ecde4d3dfec158d6f60da34d5e31693c4](https://github.com/tensorflow/tensorflow/commit/0f0b080ecde4d3dfec158d6f60da34d5e31693c4).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Neophytos Christou from Secure Systems Lab at Brown University.\n",
  "id": "PYSEC-2026-3358",
  "modified": "2026-07-13T16:06:35.061894Z",
  "published": "2026-07-09T16:49:49.132365Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pqhm-4wvf-2jg8"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2022-29201"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/commit/0f0b080ecde4d3dfec158d6f60da34d5e31693c4"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/tensorflow/tensorflow"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantized_conv_ops.cc"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1"
    },
    {
      "type": "WEB",
      "url": "https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/tensorflow-cpu"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-pqhm-4wvf-2jg8"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H",
      "type": "CVSS_V3"
    }
  ],
  "summary": "Missing validation results in undefined behavior in `QuantizedConv2D`"
}



Log in or create an account to share your comment.




Tags
Taxonomy of the tags.





Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

Author Source Type Date Other

Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
  • Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.