From 02cc160e29d20631de3859c6653184e3f876b9d7 Mon Sep 17 00:00:00 2001
From: Mihai Maruseac <mihaimaruseac@google.com>
Date: Tue, 3 Aug 2021 15:51:47 -0700
Subject: [PATCH] Prevent nullptr deref in SparseTensorSliceDataset

The arguments must determine a valid sparse tensor. This means that when indices are empty then the values must be empty too (and the reverse).

Also added test, by modifying existing test with empty sparse tensor to now run with an invalid sparse tensor input.

PiperOrigin-RevId: 388562757
Change-Id: Id8b54cd7c2316025b4f9a77292c8fb5344d17609
---
 .../data/sparse_tensor_slice_dataset_op.cc    | 11 ++++++++++
 .../from_sparse_tensor_slices_test.py         | 20 +++++++++++++++++++
 2 files changed, 31 insertions(+)

diff --git a/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc b/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc
index 00b71d41a7ca1..58bb4b0b6d806 100644
--- a/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc
+++ b/tensorflow/core/kernels/data/sparse_tensor_slice_dataset_op.cc
@@ -241,6 +241,17 @@ class SparseTensorSliceDatasetOp : public DatasetOpKernel {
                 errors::InvalidArgument(
                     "Input indices should be a matrix but received shape ",
                     indices->shape().DebugString()));
+
+    const auto num_indices = indices->NumElements();
+    const auto num_values = values->NumElements();
+    if (num_indices == 0 || num_values == 0) {
+      OP_REQUIRES(ctx, num_indices == num_values,
+                  errors::InvalidArgument(
+                      "If indices or values are empty, the other one must also "
+                      "be. Got indices of shape ",
+                      indices->shape().DebugString(), " and values of shape ",
+                      values->shape().DebugString()));
+    }
     OP_REQUIRES(ctx, TensorShapeUtils::IsVector(values->shape()),
                 errors::InvalidArgument(
                     "Input values should be a vector but received shape ",
diff --git a/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py b/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py
index 25ecbf20680b3..8f93530010cae 100644
--- a/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py
+++ b/tensorflow/python/data/kernel_tests/from_sparse_tensor_slices_test.py
@@ -118,6 +118,26 @@ def testEmptySparseTensorSlices(self):
       with self.assertRaises(errors.OutOfRangeError):
         sess.run(get_next)
 
+  @combinations.generate(combinations.combine(tf_api_version=1, mode=["graph"]))
+  def testEmptySparseTensorSlicesInvalid(self):
+    """Test a dataset based on invalid `tf.sparse.SparseTensor`."""
+    st = array_ops.sparse_placeholder(dtypes.float64)
+    iterator = dataset_ops.make_initializable_iterator(
+        dataset_ops.Dataset.from_sparse_tensor_slices(st))
+    init_op = iterator.initializer
+
+    with self.cached_session() as sess:
+      # Test with an empty sparse tensor but with non empty values.
+      empty_indices = np.empty((0, 4), dtype=np.int64)
+      non_empty_values = [1, 2, 3, 4]
+      empty_dense_shape = [0, 4, 37, 9]
+      sparse_feed = sparse_tensor.SparseTensorValue(empty_indices,
+                                                    non_empty_values,
+                                                    empty_dense_shape)
+      # Here, we expect the test to fail when running the feed.
+      with self.assertRaises(errors.InvalidArgumentError):
+        sess.run(init_op, feed_dict={st: sparse_feed})
+
   @combinations.generate(combinations.combine(tf_api_version=2, mode=["eager"]))
   def testFromSparseTensorSlicesError(self):
     with self.assertRaises(AttributeError):