TensorFlow Denial of Service vulnerability
Medium6.5CVE-2023-25661 · Published Mar 27, 2023 · updated Jul 13, 2026
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.11.1 | 2.11.1 |
Details and references
### 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. ```python 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](https://github.com/tensorflow/tensorflow/commit/948fe6369a5711d4b4568ea9bbf6015c6dfb77e2) - GitHub commit [85db5d07db54b853484bfd358c3894d948c36baf](https://github.com/keras-team/keras/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](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.
- CVSS 3.1
- CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-20
- Also known as
- BIT-tensorflow-2023-25661, CVE-2023-25661, PYSEC-2026-1952, PYSEC-2026-3182
More TensorFlow advisories
All TensorFlow| Date | Advisory | Severity | Fixed in |
|---|---|---|---|
| Mar 242023 | TensorFlow vulnerable to Out-of-Bounds Read in DynamicStitch CVE-2023-25659High7.5fixed in 2.11.1 | High7.5 | 2.11.1 |
| Mar 242023 | TensorFlow vulnerable to seg fault in `tf.raw_ops.Print` CVE-2023-25660High7.5fixed in 2.11.1 | High7.5 | 2.11.1 |
| Mar 242023 | TensorFlow vulnerable to integer overflow in EditDistance CVE-2023-25662High7.5fixed in 2.11.1 | High7.5 | 2.11.1 |
| Mar 242023 | TensorFlow has Null Pointer Error in TensorArrayConcatV2 CVE-2023-25663High7.5fixed in 2.11.1 | High7.5 | 2.11.1 |
| Mar 242023 | TensorFlow has Heap-buffer-overflow in AvgPoolGrad CVE-2023-25664High7.5fixed in 2.11.1 | High7.5 | 2.11.1 |
| Mar 242023 | TensorFlow has Null Pointer Error in SparseSparseMaximum CVE-2023-25665High7.5fixed in 2.11.1 | High7.5 | 2.11.1 |