TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
Impact
When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process.
import tensorflow as tf
class QuantConv2DTransposed(tf.keras.layers.Layer):
def build(self, input_shape):
self.kernel = self.add_weight("kernel", [3, 3, input_shape[-1], 24])
def call(self, inputs):
filters = tf.quantization.fake_quant_with_min_max_vars_per_channel(
self.kernel, -3.0 * tf.ones([24]), 3.0 * tf.ones([24]), narrow_range=True
)
filters = tf.transpose(filters, (0, 1, 3, 2))
return tf.nn.conv2d_transpose(inputs, filters, [*inputs.shape[:-1], 24], 1)
inp = tf.keras.Input(shape=(6, 8, 48), batch_size=1)
x = tf.quantization.fake_quant_with_min_max_vars(inp, -3.0, 3.0, narrow_range=True)
x = QuantConv2DTransposed()(x)
x = tf.quantization.fake_quant_with_min_max_vars(x, -3.0, 3.0, narrow_range=True)
model = tf.keras.Model(inp, x)
model.save("/tmp/testing")
converter = tf.lite.TFLiteConverter.from_saved_model("/tmp/testing")
converter.optimizations = [tf.lite.Optimize.DEFAULT]
# terminated by signal SIGSEGV (Address boundary error)
tflite_model = converter.convert()
Patches
We have patched the issue in GitHub commit aa0b852a4588cea4d36b74feb05d93055540b450.
The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.
For more information
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Attribution
This vulnerability has been reported by Lukas Geiger via Github issue.
Affected software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 | 2.7.2, 2.8.1, 2.9.1 |
| Python (PyPI) | tensorflow-cpu | < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 | 2.7.2, 2.8.1, 2.9.1 |
| Python (PyPI) | tensorflow-gpu | < 2.7.2, >= 2.8.0, < 2.8.1, >= 2.9.0, < 2.9.1 | 2.7.2, 2.8.1, 2.9.1 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-79h2-q768-fpxr
- https://nvd.nist.gov/vuln/detail/CVE-2022-36027
- https://github.com/tensorflow/tensorflow/issues/53767
- https://github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/releases/tag/v2.10.0
- https://pypi.org/project/tensorflow
- https://github.com/advisories/GHSA-79h2-q768-fpxr
- https://pypi.org/project/tensorflow-cpu
- https://pypi.org/project/tensorflow-gpu
- CVSS vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H- Weakness (CWE)
CWE-20- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 16.09.2022
- Updated
- 11.10.2026 14:18
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2026-3128 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-3291 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-79h2-q768-fpxr - CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2026-965 - PyPA Advisory Database; CC BY 4.0
Vulnerability history: tensorflow-cpu
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
- 430
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 111
- Medium 208
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions this entry
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