TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
Medium5.9CVE-2022-36027 · Published Sep 16, 2022 · updated Jul 13, 2026
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.7.2 | 2.7.2 |
| >= 2.8.0, < 2.8.1 | 2.8.1 | |
| >= 2.9.0, < 2.9.1 | 2.9.1 |
Details and references
### Impact When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. ```python 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](https://github.com/tensorflow/tensorflow/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 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. ### Attribution This vulnerability has been reported by Lukas Geiger via [Github issue](https://github.com/tensorflow/tensorflow/issues/53767).
- CVSS 3.1
- CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-20
- Also known as
- BIT-tensorflow-2022-36027, CVE-2022-36027, PYSEC-2026-3128, PYSEC-2026-3291, PYSEC-2026-965
- github.com/tensorflow/tensorflow/security/advisories/GHSA-79h2-q768-fpxr
- nvd.nist.gov/vuln/detail/CVE-2022-36027
- github.com/tensorflow/tensorflow/issues/53767
- github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/releases/tag/v2.10.0
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