CVSS3
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality Impact
NONE
Integrity Impact
NONE
Availability Impact
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS
Percentile
41.9%
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()
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.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Lukas Geiger via Github issue.
github.com/tensorflow/tensorflow
github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450
github.com/tensorflow/tensorflow/issues/53767
github.com/tensorflow/tensorflow/releases/tag/v2.10.0
github.com/tensorflow/tensorflow/security/advisories/GHSA-79h2-q768-fpxr
nvd.nist.gov/vuln/detail/CVE-2022-36027