[tflite] Ensure input tensors don't have `nullptr` buffers.

A crafted TFLite model can force a node to have as input a tensor backed by a `nullptr` buffer. That is, by carefully changing the buffer index in the flatbuffer serialization, we can force the TFLite interpreter to consider a read-only tensor to be a read-write one and assume that there is an operator that has this tensor as output, writing to it and allocating memory before the tensor is used as input. If this does not happen, we get memory corruption.

PiperOrigin-RevId: 332524692
Change-Id: I57ef175152a29020af9ab041dc959e5631dce40f

tensorflow/lite/core/subgraph.cc

@@ -18,6 +18,7 @@ limitations under the License.
 #include <algorithm>
 
 #include "tensorflow/lite/arena_planner.h"
+#include "third_party/tensorflow/lite/builtin_ops.h"
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/context_util.h"
 #include "tensorflow/lite/core/api/tensor_utils.h"
@@ -934,6 +935,19 @@ TfLiteStatus Subgraph::Invoke() {
           tensor->data_is_stale) {
         TF_LITE_ENSURE_STATUS(EnsureTensorDataIsReadable(tensor_index));
       }
+      if (tensor->data.raw == nullptr && tensor->bytes > 0) {
+        if (registration.builtin_code == kTfLiteBuiltinReshape && i == 1) {
+          // In general, having a tensor here with no buffer will be an error.
+          // However, for the reshape operator, the second input tensor is only
+          // used for the shape, not for the data. Thus, null buffer is ok.
+          continue;
+        } else {
+          // In all other cases, we need to return an error as otherwise we will
+          // trigger a null pointer dereference (likely).
+          ReportError("Input tensor %d lacks data", tensor_index);
+          return kTfLiteError;
+        }
+      }
     }
 
     if (check_cancelled_func_ != nullptr &&