CVE-2021-29532: Out-of-bounds Read (CWE-125)
value: TensorFlow is an end-to-end open source platform for machine learning. An attacker can force accesses outside the bounds of heap allocated arrays by passing in invalid tensor values to `tf.raw_ops.RaggedCross`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efea03b38fb8d3b81762237dc85e579cc5fc6e87/tensorflow/core/kernels/ragged_cross_op.cc#L456-L487) lacks validation for the user supplied arguments. Each of the above branches call a helper function after accessing array elements via a `*_list[next_*]` pattern, followed by incrementing the `next_*` index. However, as there is no validation that the `next_*` values are in the valid range for the corresponding `*_list` arrays, this results in heap OOB reads. 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.
CWE description: The product reads data past the end, or before the beginning, of the intended buffer.
CVSS v3 base score: 7.1
Published: 2021-05-14T20:15Z
Repository: https://github.com/tensorflow/tensorflow
Language: C++
Files changed: tensorflow/core/kernels/ragged_cross_op.cc
Commit date: 2021-04-21 16:26:41 -0700
Commit message: Fix out of bounds read in `ragged_cross_op.cc`.

PiperOrigin-RevId: 369757702
Change-Id: Ie6e5d2c21513a8d56bf41fcf35960caf76e890f9

Diff: diff --git a/tensorflow/core/kernels/ragged_cross_op.cc b/tensorflow/core/kernels/ragged_cross_op.cc
index ea65c0ee2b5b2..5dfe93f416659 100644
--- a/tensorflow/core/kernels/ragged_cross_op.cc
+++ b/tensorflow/core/kernels/ragged_cross_op.cc
@@ -19,10 +19,11 @@ limitations under the License.
 
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/register_types.h"
 #include "tensorflow/core/framework/tensor.h"
 #include "tensorflow/core/framework/tensor_shape.h"
+#include "tensorflow/core/platform/errors.h"
 #include "tensorflow/core/platform/fingerprint.h"
 #include "tensorflow/core/util/util.h"
 #include "tensorflow/core/util/work_sharder.h"
 
 namespace tensorflow {
@@ -464,20 +465,49 @@ class RaggedCrossOp : public OpKernel {
     int next_ragged = 0;
     int next_sparse = 0;
     int next_dense = 0;
     for (char c : input_order_) {
       if (c == 'R') {
+        if (next_ragged >= ragged_values_list.size())
+          return errors::InvalidArgument(
+              "input_order \"", input_order_,
+              "\" specifies reading a ragged tensor value at index ",
+              next_ragged, " from a list of ", ragged_values_list.size(),
+              " values.");
+        if (next_ragged >= ragged_splits_list.size())
+          return errors::InvalidArgument(
+              "input_order \"", input_order_,
+              "\" specifies reading a ragged tensor split at index ",
+              next_ragged, " from a list of ", ragged_splits_list.size(),
+              " splits.");
         TF_RETURN_IF_ERROR(BuildRaggedFeatureReader(
             ragged_values_list[next_ragged], ragged_splits_list[next_ragged],
             features));
         next_ragged++;
       } else if (c == 'S') {
+        if (next_sparse >= sparse_values_list.size())
+          return errors::InvalidArgument(
+              "input_order \"", input_order_,
+              "\" specifies reading a sparse tensor value at index ",
+              next_sparse, " from a list of ", sparse_values_list.size(),
+              " values.");
+        if (next_sparse >= sparse_indices_list.size())
+          return errors::InvalidArgument(
+              "input_order \"", input_order_,
+              "\" specifies reading a sparse tensor index at index ",
+              next_sparse, " from a list of ", sparse_indices_list.size(),
+              " indices.");
         TF_RETURN_IF_ERROR(BuildSparseFeatureReader(
             sparse_indices_list[next_sparse], sparse_values_list[next_sparse],
             batch_size, features));
         next_sparse++;
       } else if (c == 'D') {
+        if (next_dense >= dense_list.size())
+          return errors::InvalidArgument(
+              "input_order \"", input_order_,
+              "\" specifies reading a dense tensor at index ", next_dense,
+              " from a list of ", dense_list.size(), " tensors.");
         TF_RETURN_IF_ERROR(
             BuildDenseFeatureReader(dense_list[next_dense++], features));
       } else {
         return errors::InvalidArgument("Unexpected input_order value.");
       }

Fixed code: #include "tensorflow/core/platform/errors.h"
        if (next_ragged >= ragged_values_list.size())
          return errors::InvalidArgument(
              "input_order \"", input_order_,
              "\" specifies reading a ragged tensor value at index ",
              next_ragged, " from a list of ", ragged_values_list.size(),
              " values.");
        if (next_ragged >= ragged_splits_list.size())
          return errors::InvalidArgument(
              "input_order \"", input_order_,
              "\" specifies reading a ragged tensor split at index ",
              next_ragged, " from a list of ", ragged_splits_list.size(),
              " splits.");
        if (next_sparse >= sparse_values_list.size())
          return errors::InvalidArgument(
              "input_order \"", input_order_,
              "\" specifies reading a sparse tensor value at index ",
              next_sparse, " from a list of ", sparse_values_list.size(),
              " values.");
        if (next_sparse >= sparse_indices_list.size())
          return errors::InvalidArgument(
              "input_order \"", input_order_,
              "\" specifies reading a sparse tensor index at index ",
              next_sparse, " from a list of ", sparse_indices_list.size(),
              " indices.");
        if (next_dense >= dense_list.size())
          return errors::InvalidArgument(
              "input_order \"", input_order_,
              "\" specifies reading a dense tensor at index ", next_dense,
              " from a list of ", dense_list.size(), " tensors.");