CVE-2022-36027
published 2022-09-16CVE-2022-36027: TensorFlow is an open source platform for machine learning. When converting transposed convolutions using per-channel weight quantization the converter…
PriorityP337high7.5CVSS 3.1
AVNACLPRNUINSUCNINAH
EPSS
0.62%
45.6th percentile
TensorFlow is an open source platform for machine learning. When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. 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. There are no known workarounds for this issue.
Affected
11 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | < 2.7.2 | 2.7.2 | |
| tensorflow | — | — | |
| tensorflow | >= 2.8.0 < 2.8.1 | 2.8.1 | |
| tensorflow | >= 2.9.0 < 2.9.1 | 2.9.1 | |
| intel | optimization_for_tensorflow | >= 0 < 2.7.2 | 2.7.2 |
| intel | optimization_for_tensorflow | >= 2.8.0 < 2.8.1 | 2.8.1 |
| intel | optimization_for_tensorflow | >= 2.9.0 < 2.9.1 | 2.9.1 |
| tensorflow | tensorflow | < 2.7.2 | 2.7.2 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.5HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
vendor_debian5.9LOW
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OSV
TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
osv·2022-09-16
CVE-2022-36027 [MEDIUM] TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
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_m
GHSA
TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
ghsa·2022-09-16
CVE-2022-36027 [MEDIUM] CWE-20 TensorFlow segfault TFLite converter on per-channel quantized transposed convolutions
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_m
Debian
CVE-2022-36027: tensorflow - TensorFlow is an open source platform for machine learning. When converting tran...
vendor_debian·2022·CVSS 5.9
CVE-2022-36027 [MEDIUM] CVE-2022-36027: tensorflow - TensorFlow is an open source platform for machine learning. When converting tran...
TensorFlow is an open source platform for machine learning. When converting transposed convolutions using per-channel weight quantization the converter segfaults and crashes the Python process. 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. There are no known workarounds for this issue.
Scope: local
forky: resolved
sid: resolved
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450https://github.com/tensorflow/tensorflow/issues/53767https://github.com/tensorflow/tensorflow/security/advisories/GHSA-79h2-q768-fpxrhttps://github.com/tensorflow/tensorflow/commit/aa0b852a4588cea4d36b74feb05d93055540b450https://github.com/tensorflow/tensorflow/issues/53767https://github.com/tensorflow/tensorflow/security/advisories/GHSA-79h2-q768-fpxr
2022-09-16
Published