diff --git a/python/docs/source/migration_guide/pyspark_upgrade.rst b/python/docs/source/migration_guide/pyspark_upgrade.rst
index c6cf69dadc93..d588e73ef919 100644
--- a/python/docs/source/migration_guide/pyspark_upgrade.rst
+++ b/python/docs/source/migration_guide/pyspark_upgrade.rst
@@ -25,7 +25,7 @@ Upgrading from PySpark 4.0 to 4.1
 * In Spark 4.1, Python 3.9 support was dropped in PySpark.
 * In Spark 4.1, the minimum supported version for PyArrow has been raised from 11.0.0 to 15.0.0 in PySpark.
 * In Spark 4.1, the minimum supported version for Pandas has been raised from 2.0.0 to 2.2.0 in PySpark.
-* In Spark 4.1, ``DataFrame['name']`` on Spark Connect Python Client no longer eagerly validate the column name. To restore the legacy behavior, set ``PYSPARK_VALIDATE_COLUMN_NAME_LEGACY`` environment variable to ``1``.
+* In Spark 4.1, ``DataFrame['name']`` and ``DataFrame.name`` on Spark Connect Python Client no longer eagerly validate the column name. To restore the legacy behavior, set ``PYSPARK_VALIDATE_COLUMN_NAME_LEGACY`` environment variable to ``1``.
 * In Spark 4.1, Arrow-optimized Python UDF supports UDT input / output instead of falling back to the regular UDF. To restore the legacy behavior, set ``spark.sql.execution.pythonUDF.arrow.legacy.fallbackOnUDT`` to ``true``.
 * In Spark 4.1, unnecessary conversion to pandas instances is removed when ``spark.sql.execution.pythonUDF.arrow.enabled`` is enabled. As a result, the type coercion changes when the produced output has a schema different from the specified schema. To restore the previous behavior, enable ``spark.sql.legacy.execution.pythonUDF.pandas.conversion.enabled``.
 * In Spark 4.1, unnecessary conversion to pandas instances is removed when ``spark.sql.execution.pythonUDTF.arrow.enabled`` is enabled. As a result, the type coercion changes when the produced output has a schema different from the specified schema. To restore the previous behavior, enable ``spark.sql.legacy.execution.pythonUDTF.pandas.conversion.enabled``.
diff --git a/python/pyspark/sql/connect/dataframe.py b/python/pyspark/sql/connect/dataframe.py
index 65dea5cf1a57..c4f54f77de60 100644
--- a/python/pyspark/sql/connect/dataframe.py
+++ b/python/pyspark/sql/connect/dataframe.py
@@ -1737,7 +1737,9 @@ def __getattr__(self, name: str) -> "Column":
                 errorClass="JVM_ATTRIBUTE_NOT_SUPPORTED", messageParameters={"attr_name": name}
             )
 
-        if name not in self.columns:
+        if os.environ.get("PYSPARK_VALIDATE_COLUMN_NAME_LEGACY") == "1" and not any(
+            field.name == name for field in self._schema
+        ):
             raise PySparkAttributeError(
                 errorClass="ATTRIBUTE_NOT_SUPPORTED", messageParameters={"attr_name": name}
             )