CVE-2021-29516
Calling tf.raw_ops.RaggedTensorToVariant
with arguments specifying an invalid ragged tensor results in a null pointer dereference:
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1])
import tensorflow as tf
input_tensor = tf.constant([], shape=[2, 2, 2, 2, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 2, 6, 2], dtype=tf.float32)
tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 39, 34, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 1, 1])
The implementation of RaggedTensorToVariant
operations
does not validate that the ragged tensor argument is non-empty:
int ragged_rank = batched_ragged.ragged_rank();
auto batched_splits_top_vec = batched_ragged.splits(0).vec<SPLIT_TYPE>();
Since batched_ragged
contains no elements, batched_ragged.splits
is a null vector, thus batched_ragged.splits(0)
will result in dereferencing nullptr
.
We have patched the issue in GitHub commit b055b9c474cd376259dde8779908f9eeaf097d93.
The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
This vulnerability has been reported by Yakun Zhang and Ying Wang of Baidu X-Team.