diff --git a/onnxruntime/core/providers/cpu/nn/Unpool.cc b/onnxruntime/core/providers/cpu/nn/Unpool.cc
index 391326dbb2..e108f67712 100644
--- a/onnxruntime/core/providers/cpu/nn/Unpool.cc
+++ b/onnxruntime/core/providers/cpu/nn/Unpool.cc
@@ -26,6 +26,7 @@ ONNX_CPU_OPERATOR_KERNEL(
 Status MaxUnpool::Compute(OpKernelContext* context) const {
   // Get pooled values tensor
   const Tensor* X = context->Input<Tensor>(0);
+  if (X == nullptr) return Status(common::ONNXRUNTIME, common::FAIL, "input count mismatch");
   const TensorShape& X_shape = X->Shape();
   const float* X_data = X->template Data<float>();
 
@@ -62,12 +63,13 @@ Status MaxUnpool::Compute(OpKernelContext* context) const {
   bool padsInferred = false;
 
   if (num_inputs_ == 3) {
-    auto& tensor_shape = *context->Input<Tensor>(2);
-    ORT_RETURN_IF_NOT(tensor_shape.Shape().GetDims().size() == 1, "Shape must be 1 dimensional as it's tensor data is a shape");
+    auto tensor_shape = context->Input<Tensor>(2);
+    if (tensor_shape == nullptr) return Status(common::ONNXRUNTIME, common::FAIL, "input count mismatch");
+    ORT_RETURN_IF_NOT(tensor_shape->Shape().GetDims().size() == 1, "Shape must be 1 dimensional as it's tensor data is a shape");
 
     // Turn the shape tensor data into an actual shape
-    const int64_t* p_shape = tensor_shape.template Data<int64_t>();
-    std::vector<int64_t> shape{p_shape, p_shape + tensor_shape.Shape().Size()};
+    const int64_t* p_shape = tensor_shape->template Data<int64_t>();
+    std::vector<int64_t> shape{p_shape, p_shape + tensor_shape->Shape().Size()};
     givenOutputShape = shape;
 
     inferredPads.resize(inferredOutputShape.size() * 2, 0);
diff --git a/onnxruntime/core/providers/cuda/tensor/identity_op.h b/onnxruntime/core/providers/cuda/tensor/identity_op.h
index f66a11faf7..d83fd541b3 100644
--- a/onnxruntime/core/providers/cuda/tensor/identity_op.h
+++ b/onnxruntime/core/providers/cuda/tensor/identity_op.h
@@ -17,6 +17,7 @@ class IdentityOp final : public CudaKernel {
 
   Status ComputeInternal(OpKernelContext* context) const override {
     const Tensor* X = context->Input<Tensor>(0);
+    if (X == nullptr) return Status(common::ONNXRUNTIME, common::FAIL, "input count mismatch");
     const TensorShape& shape = X->Shape();
     Tensor* Y = context->Output(0, shape);
     auto X_type = X->DataType();
diff --git a/onnxruntime/core/providers/cuda/tensor/transpose.cc b/onnxruntime/core/providers/cuda/tensor/transpose.cc
index 670e4f2843..d443336deb 100644
--- a/onnxruntime/core/providers/cuda/tensor/transpose.cc
+++ b/onnxruntime/core/providers/cuda/tensor/transpose.cc
@@ -21,7 +21,9 @@ namespace cuda {
 
 template <typename T>
 Status Transpose<T>::ComputeInternal(OpKernelContext* ctx) const {
-  const Tensor& X = *ctx->Input<Tensor>(0);
+  const Tensor* X_ptr = ctx->Input<Tensor>(0);
+  if (X_ptr == nullptr) return Status(common::ONNXRUNTIME, common::FAIL, "input count mismatch");
+  const Tensor& X = *X_ptr;
   const TensorShape& input_shape = X.Shape();
   const std::vector<int64_t>& input_dims = input_shape.GetDims();
   size_t rank = input_dims.size();
diff --git a/onnxruntime/core/providers/mkldnn/math/sum.cc b/onnxruntime/core/providers/mkldnn/math/sum.cc
index d08bc62ea7..5b7794ab62 100644
--- a/onnxruntime/core/providers/mkldnn/math/sum.cc
+++ b/onnxruntime/core/providers/mkldnn/math/sum.cc
@@ -192,6 +192,7 @@ Status Sum<T>::Compute(OpKernelContext* context) const {
   std::vector<mkldnn::memory::dims> src_dims;
 
   const Tensor* X1 = context->Input<Tensor>(0);
+  if (X1 == nullptr) return Status(common::ONNXRUNTIME, common::FAIL, "input count mismatch");
   Tensor* Y = context->Output(0, X1->Shape());
   int dimensions = static_cast<int>(X1->Shape().NumDimensions());
 
@@ -204,6 +205,7 @@ Status Sum<T>::Compute(OpKernelContext* context) const {
 
   for (int i = 0; i < num_inputs; i++) {
     const Tensor* X = context->Input<Tensor>(i);
+    if (X == nullptr) return Status(common::ONNXRUNTIME, common::FAIL, "input count mismatch");
     mkldnn::memory::dims src_dims_mkl(
       X->Shape().GetDims().begin(), X->Shape().GetDims().end());
     src_dims.push_back(src_dims_mkl);