diff --git a/mlir/lib/Dialect/Vector/Transforms/VectorUnroll.cpp b/mlir/lib/Dialect/Vector/Transforms/VectorUnroll.cpp
index 693f4f955994d..734a8590eedb7 100644
--- a/mlir/lib/Dialect/Vector/Transforms/VectorUnroll.cpp
+++ b/mlir/lib/Dialect/Vector/Transforms/VectorUnroll.cpp
@@ -169,7 +169,7 @@ struct UnrollTransferReadPattern
     auto sourceVectorType = readOp.getVectorType();
     SmallVector<int64_t> strides(targetShape->size(), 1);
     Location loc = readOp.getLoc();
-    ArrayRef<int64_t> originalSize = readOp.getVectorType().getShape();
+    ArrayRef<int64_t> originalSize = sourceVectorType.getShape();
 
     // Prepare the result vector;
     Value result = rewriter.create<arith::ConstantOp>(
@@ -224,6 +224,14 @@ struct UnrollTransferWritePattern
     SmallVector<int64_t> strides(targetShape->size(), 1);
     Location loc = writeOp.getLoc();
     ArrayRef<int64_t> originalSize = sourceVectorType.getShape();
+    // Bail-out if rank(source) != rank(target). The main limitation here is the
+    // fact that `ExtractStridedSlice` requires the rank for the input and
+    // output to match. If needed, we can relax this later.
+    if (originalSize.size() != targetShape->size())
+      return rewriter.notifyMatchFailure(
+          writeOp,
+          "expected source input vector rank to match target shape rank");
+
     SmallVector<Value> originalIndices(writeOp.getIndices().begin(),
                                        writeOp.getIndices().end());
     SmallVector<int64_t> loopOrder =
diff --git a/mlir/test/Dialect/Vector/vector-transfer-unroll.mlir b/mlir/test/Dialect/Vector/vector-transfer-unroll.mlir
index 5dd65ea132d08..44601a4a47dda 100644
--- a/mlir/test/Dialect/Vector/vector-transfer-unroll.mlir
+++ b/mlir/test/Dialect/Vector/vector-transfer-unroll.mlir
@@ -68,6 +68,24 @@ func.func @transfer_write_unroll(%mem : memref<4x4xf32>, %vec : vector<4x4xf32>)
 
 // -----
 
+// Ensure that cases with mismatched target and source shape ranks
+// do not lead to a crash.
+// Note: The vector unrolling target shape in `test-vector-transfer-unrolling-patterns`
+// is currently hard-coded to [2, 2].
+
+// CHECK-LABEL: func @negative_transfer_write
+//   CHECK-NOT:   vector.extract_strided_slice
+//       CHECK:   vector.transfer_write
+//       CHECK:   return
+func.func @negative_transfer_write(%vec: vector<6x34x62xi8>) {
+  %c0 = arith.constant 0 : index
+  %alloc = memref.alloc() : memref<6x34x62xi8>
+  vector.transfer_write %vec, %alloc[%c0, %c0, %c0]: vector<6x34x62xi8>, memref<6x34x62xi8>
+  return
+}
+
+// -----
+
 // CHECK-LABEL: func @transfer_readwrite_unroll
 // CHECK-DAG:     %[[C2:.*]] = arith.constant 2 : index
 // CHECK-DAG:     %[[C0:.*]] = arith.constant 0 : index