CVE-2022-36027 – tensorflow-gpu
Package
Manager: pip
Name: tensorflow-gpu
Vulnerable Version: >=0 <2.7.2 || >=2.8.0 <2.8.1 || >=2.9.0 <2.9.1
Severity
Level: Medium
CVSS v3.1: CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
CVSS v4.0: CVSS:4.0/AV:N/AC:H/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N
EPSS: 0.00501 pctl0.65002
Details
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. ```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).
Metadata
Created: 2022-09-16T21:06:31Z
Modified: 2022-09-19T19:00:53Z
Source: https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2022/09/GHSA-79h2-q768-fpxr/GHSA-79h2-q768-fpxr.json
CWE IDs: ["CWE-20"]
Alternative ID: GHSA-79h2-q768-fpxr
Finding: F184
Auto approve: 1