diff --git a/mlir/lib/Dialect/Vector/IR/VectorOps.cpp b/mlir/lib/Dialect/Vector/IR/VectorOps.cpp
index bee5c1fd6ed58..74222cb56d412 100644
--- a/mlir/lib/Dialect/Vector/IR/VectorOps.cpp
+++ b/mlir/lib/Dialect/Vector/IR/VectorOps.cpp
@@ -151,13 +151,39 @@ static bool isSupportedCombiningKind(CombiningKind combiningKind,
   return false;
 }
 
-AffineMap mlir::vector::getTransferMinorIdentityMap(ShapedType shapedType,
-                                                    VectorType vectorType) {
-  int64_t elementVectorRank = 0;
+/// Returns the number of dimensions of the `shapedType` that participate in the
+/// vector transfer, effectively the rank of the vector dimensions within the
+/// `shapedType`. This is calculated by taking the rank of the `vectorType`
+/// being transferred and subtracting the rank of the `shapedType`'s element
+/// type if it's also a vector.
+///
+/// This is used to determine the number of minor dimensions for identity maps
+/// in vector transfers.
+///
+/// For example, given a transfer operation involving `shapedType` and
+/// `vectorType`:
+///
+///   - shapedType = tensor<10x20xf32>, vectorType = vector<2x4xf32>
+///     - shapedType.getElementType() = f32 (rank 0)
+///     - vectorType.getRank() = 2
+///     - Result = 2 - 0 = 2
+///
+///   - shapedType = tensor<10xvector<20xf32>>, vectorType = vector<20xf32>
+///     - shapedType.getElementType() = vector<20xf32> (rank 1)
+///     - vectorType.getRank() = 1
+///     - Result = 1 - 1 = 0
+static unsigned getRealVectorRank(ShapedType shapedType,
+                                  VectorType vectorType) {
+  unsigned elementVectorRank = 0;
   VectorType elementVectorType =
       llvm::dyn_cast<VectorType>(shapedType.getElementType());
   if (elementVectorType)
     elementVectorRank += elementVectorType.getRank();
+  return vectorType.getRank() - elementVectorRank;
+}
+
+AffineMap mlir::vector::getTransferMinorIdentityMap(ShapedType shapedType,
+                                                    VectorType vectorType) {
   // 0-d transfers are to/from tensor<t>/memref<t> and vector<1xt>.
   // TODO: replace once we have 0-d vectors.
   if (shapedType.getRank() == 0 &&
@@ -166,7 +192,7 @@ AffineMap mlir::vector::getTransferMinorIdentityMap(ShapedType shapedType,
         /*numDims=*/0, /*numSymbols=*/0,
         getAffineConstantExpr(0, shapedType.getContext()));
   return AffineMap::getMinorIdentityMap(
-      shapedType.getRank(), vectorType.getRank() - elementVectorRank,
+      shapedType.getRank(), getRealVectorRank(shapedType, vectorType),
       shapedType.getContext());
 }
 
@@ -4261,6 +4287,10 @@ ParseResult TransferReadOp::parse(OpAsmParser &parser, OperationState &result) {
   Attribute permMapAttr = result.attributes.get(permMapAttrName);
   AffineMap permMap;
   if (!permMapAttr) {
+    if (shapedType.getRank() < getRealVectorRank(shapedType, vectorType))
+      return parser.emitError(typesLoc,
+                              "expected a custom permutation_map when "
+                              "rank(source) != rank(destination)");
     permMap = getTransferMinorIdentityMap(shapedType, vectorType);
     result.attributes.set(permMapAttrName, AffineMapAttr::get(permMap));
   } else {
@@ -4676,6 +4706,10 @@ ParseResult TransferWriteOp::parse(OpAsmParser &parser,
   auto permMapAttr = result.attributes.get(permMapAttrName);
   AffineMap permMap;
   if (!permMapAttr) {
+    if (shapedType.getRank() < getRealVectorRank(shapedType, vectorType))
+      return parser.emitError(typesLoc,
+                              "expected a custom permutation_map when "
+                              "rank(source) != rank(destination)");
     permMap = getTransferMinorIdentityMap(shapedType, vectorType);
     result.attributes.set(permMapAttrName, AffineMapAttr::get(permMap));
   } else {
diff --git a/mlir/test/Dialect/Vector/invalid.mlir b/mlir/test/Dialect/Vector/invalid.mlir
index dbf829e014b8d..63f8667ce6b9e 100644
--- a/mlir/test/Dialect/Vector/invalid.mlir
+++ b/mlir/test/Dialect/Vector/invalid.mlir
@@ -525,6 +525,15 @@ func.func @test_vector.transfer_read(%arg0: memref<?x?xvector<2x3xf32>>) {
 
 // -----
 
+func.func @test_vector.transfer_read(%arg1: memref<?xindex>) -> vector<3x4xindex> {
+  %c3 = arith.constant 3 : index
+  // expected-error@+1 {{expected a custom permutation_map when rank(source) != rank(destination)}}
+  %0 = vector.transfer_read %arg1[%c3, %c3], %c3 : memref<?xindex>, vector<3x4xindex>
+  return %0 : vector<3x4xindex>
+}
+
+// -----
+
 func.func @test_vector.transfer_write(%arg0: memref<?x?xf32>) {
   %c3 = arith.constant 3 : index
   %cst = arith.constant 3.0 : f32
@@ -646,6 +655,14 @@ func.func @test_vector.transfer_write(%arg0: memref<?xf32>, %arg1: vector<7xf32>
 
 // -----
 
+func.func @test_vector.transfer_write(%vec_to_write: vector<3x4xindex>, %output_memref: memref<?xindex>) {
+  %c3 = arith.constant 3 : index
+  // expected-error@+1 {{expected a custom permutation_map when rank(source) != rank(destination)}}
+  vector.transfer_write %vec_to_write, %output_memref[%c3, %c3] : vector<3x4xindex>, memref<?xindex>
+}
+
+// -----
+
 func.func @insert_strided_slice(%a: vector<4x4xf32>, %b: vector<4x8x16xf32>) {
   // expected-error@+1 {{expected offsets of same size as destination vector rank}}
   %1 = vector.insert_strided_slice %a, %b {offsets = [100], strides = [1, 1]} : vector<4x4xf32> into vector<4x8x16xf32>