Headline
CVE-2022-36018: [security] Fix failed shape check in RaggedTensorToVariant. · tensorflow/tensorflow@88f93df
TensorFlow is an open source platform for machine learning. If RaggedTensorToVariant is given a rt_nested_splits list that contains tensors of ranks other than one, it results in a CHECK fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 88f93dfe691563baa4ae1e80ccde2d5c7a143821. 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.
@@ -1468,6 +1468,21 @@ def testUnbatchVariantInDataset(self):
for i in range(3):
self.assertAllEqual(sess.run(rt[i]), out)
def testToVariantInvalidParams(self):
self.assertRaisesRegex((ValueError, errors.InvalidArgumentError),
r’be rank 1 but is rank 0’,
gen_ragged_conversion_ops.ragged_tensor_to_variant,
rt_nested_splits=[0, 1, 2],
rt_dense_values=[0, 1, 2],
batched_input=True)
self.assertRaisesRegex((ValueError, errors.InvalidArgumentError),
r’be rank 1 but is rank 2’,
gen_ragged_conversion_ops.ragged_tensor_to_variant,
rt_nested_splits=[[[0]], [[1]], [[2]]],
rt_dense_values=[0, 1, 2],
batched_input=True)
def testFromVariantInvalidParams(self):
rt = ragged_factory_ops.constant([[0], [1], [2], [3]])
batched_variant = rt._to_variant(batched_input=True)
Related news
### Impact If `RaggedTensorToVariant` is given a `rt_nested_splits` list that contains tensors of ranks other than one, it results in a `CHECK` fail that can be used to trigger a denial of service attack. ```python import tensorflow as tf batched_input = True rt_nested_splits = tf.constant([0,32,64], shape=[3], dtype=tf.int64) rt_dense_values = tf.constant([0,32,64], shape=[3], dtype=tf.int64) tf.raw_ops.RaggedTensorToVariant(rt_nested_splits=rt_nested_splits, rt_dense_values=rt_dense_values, batched_input=batched_input) ``` ### Patches We have patched the issue in GitHub commit [88f93dfe691563baa4ae1e80ccde2d5c7a143821](https://github.com/tensorflow/tensorflow/commit/88f93dfe691563baa4ae1e80ccde2d5c7a143821). 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. ### For more information Please consult [our security guide](https://githu...