diff --git a/pg_lake_copy/tests/pytests/test_parquet_copy.py b/pg_lake_copy/tests/pytests/test_parquet_copy.py
index f5521535e..85e895dd0 100644
--- a/pg_lake_copy/tests/pytests/test_parquet_copy.py
+++ b/pg_lake_copy/tests/pytests/test_parquet_copy.py
@@ -834,6 +834,76 @@ def test_md_array(pg_conn, duckdb_conn, tmp_path):
     assert result[0]["val"] == 2
 
 
+def test_copy_to_multidim_array_errors(pg_conn, tmp_path):
+    """
+    Regression test for https://github.com/Snowflake-Labs/pg_lake/issues/407.
+
+    COPY <table> TO <lake-file> must raise a clear pg_lake error when a column
+    contains a multidimensional array value.  Previously the value was
+    serialised into the intermediate temp CSV and handed to DuckDB, which
+    either returned a cryptic Conversion Error or crashed the shared
+    pgduck_server process (issue #408).
+
+    The check lives in CopyOneRowTo (csv_writer.c) and fires before the CSV
+    is written, so the engine is never involved.
+    """
+    parquet_path = tmp_path / "test_multidim_err.parquet"
+
+    run_command(
+        """
+        CREATE TABLE test_multidim_err (id bigint, v int[]);
+        INSERT INTO test_multidim_err VALUES (1, ARRAY[[1,2],[3,4]]);
+    """,
+        pg_conn,
+    )
+
+    error = run_command(
+        f"COPY test_multidim_err TO '{parquet_path}' WITH (format 'parquet')",
+        pg_conn,
+        raise_error=False,
+    )
+
+    assert error is not None, "Expected an error for multidimensional array in COPY TO"
+    assert (
+        "multidimensional arrays are not supported" in error.lower()
+    ), f"Unexpected error message: {error}"
+
+    pg_conn.rollback()
+
+
+def test_copy_to_1d_array_succeeds(pg_conn, duckdb_conn, tmp_path):
+    """
+    Regression guard: 1-D array columns must still round-trip correctly through
+    COPY TO after the multidim check is added.  A 1-D value has ARR_NDIM == 1
+    and must not be rejected.
+    """
+    parquet_path = tmp_path / "test_1d_array.parquet"
+
+    run_command(
+        f"""
+        CREATE TABLE test_1d_array (id bigint, tags text[]);
+        INSERT INTO test_1d_array VALUES
+            (1, ARRAY['a', 'b', 'c']),
+            (2, NULL),
+            (3, ARRAY['x']);
+        COPY test_1d_array TO '{parquet_path}' WITH (format 'parquet');
+    """,
+        pg_conn,
+    )
+
+    duckdb_conn.execute(
+        "SELECT id, tags FROM read_parquet($1) ORDER BY id", [str(parquet_path)]
+    )
+    rows = duckdb_conn.fetchall()
+
+    assert len(rows) == 3
+    assert rows[0] == (1, ["a", "b", "c"])
+    assert rows[1] == (2, None)
+    assert rows[2] == (3, ["x"])
+
+    pg_conn.rollback()
+
+
 def test_copy_virtual_column(pg_conn, tmp_path):
     # virtual columns were introduced in PostgreSQL 18
     if get_pg_version_num(pg_conn) < 180000:
diff --git a/pg_lake_engine/src/csv/csv_writer.c b/pg_lake_engine/src/csv/csv_writer.c
index 3b91870fe..f0945560b 100644
--- a/pg_lake_engine/src/csv/csv_writer.c
+++ b/pg_lake_engine/src/csv/csv_writer.c
@@ -43,6 +43,7 @@
 #include "nodes/execnodes.h"
 #include "nodes/makefuncs.h"
 #include "port/pg_bswap.h"
+#include "utils/array.h"
 #include "utils/builtins.h"
 #include "utils/lsyscache.h"
 #include "utils/memutils.h"
@@ -770,6 +771,36 @@ CopyOneRowTo(CopyToState cstate, TupleTableSlot *slot)
 				 */
 				Form_pg_attribute attr = TupleDescAttr(slot->tts_tupleDescriptor, attnum - 1);
 
+				/*
+				 * Reject multidimensional arrays before serialization.
+				 * PostgreSQL cannot distinguish int[] from int[][] at the
+				 * type level, so a value with ndim > 1 would be serialised as
+				 * "[[1,2],[3,4]]" and DuckDB cannot cast that string back to
+				 * a flat LIST(T).  For Iceberg tables this is handled
+				 * upstream by IcebergErrorOrClampDatum; for plain COPY TO
+				 * there is no such guard, so we raise here.  Check before
+				 * serialisation so we do not pay the cost of PGDuckSerialize
+				 * on a value we will reject.
+				 */
+				if (get_element_type(attr->atttypid) != InvalidOid &&
+					cstate->targetFormat != DATA_FORMAT_ICEBERG)
+				{
+					ArrayType  *arr = DatumGetArrayTypeP(value);
+
+					if (ARR_NDIM(arr) > 1)
+						ereport(ERROR,
+								(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
+								 errmsg("multidimensional arrays are not supported"
+										" in COPY TO"),
+								 errdetail("Column \"%s\" contains a"
+										   " %d-dimensional array value.",
+										   NameStr(attr->attname),
+										   ARR_NDIM(arr)),
+								 errhint("Flatten the array to one dimension before"
+										 " exporting, or write to an Iceberg table"
+										 " with out_of_range_values = 'clamp'.")));
+				}
+
 				if (ShouldUseDuckSerialization(cstate->targetFormat, MakePGType(attr->atttypid, attr->atttypmod)))
 				{
 					/*
diff --git a/pg_lake_engine/src/pgduck/write_data.c b/pg_lake_engine/src/pgduck/write_data.c
index 3f91dc1f6..b00003eae 100644
--- a/pg_lake_engine/src/pgduck/write_data.c
+++ b/pg_lake_engine/src/pgduck/write_data.c
@@ -93,8 +93,11 @@ ConvertCSVFileTo(char *csvFilePath, TupleDesc csvTupleDesc, int maxLineSize,
 	bool		queryHasRowIds = false;
 
 	/*
-	 * CSV data is already clamped by WriteInsertRecord and converted to
-	 * struct for Iceberg
+	 * When reached from the Iceberg FDW INSERT path, the CSV data has already
+	 * been clamped by WriteInsertRecord (via ClampAndCheckConstraints →
+	 * IcebergErrorOrClampSlotInPlace).  When reached from the plain COPY TO
+	 * path (ProcessPgLakeCopyTo), multidimensional array values are rejected
+	 * earlier in CopyOneRowTo, so they never appear in the CSV.
 	 */
 	return WriteQueryResultTo(command.data,
 							  destinationPath,