diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index f709bec842c86..27e7abe333d6f 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -395,7 +395,7 @@ Interval
 
 Indexing
 ^^^^^^^^
--
+- Bug in :meth:`DataFrame.__getitem__` returning modified columns when called with ``slice`` in Python 3.12 (:issue:`57500`)
 -
 
 Missing
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 0b386efb5a867..cd4812c3f78ae 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -3855,8 +3855,10 @@ def __getitem__(self, key):
         key = lib.item_from_zerodim(key)
         key = com.apply_if_callable(key, self)
 
-        if is_hashable(key) and not is_iterator(key):
+        if is_hashable(key) and not is_iterator(key) and not isinstance(key, slice):
             # is_iterator to exclude generator e.g. test_getitem_listlike
+            # As of Python 3.12, slice is hashable which breaks MultiIndex (GH#57500)
+
             # shortcut if the key is in columns
             is_mi = isinstance(self.columns, MultiIndex)
             # GH#45316 Return view if key is not duplicated
diff --git a/pandas/tests/frame/indexing/test_indexing.py b/pandas/tests/frame/indexing/test_indexing.py
index 49e5c4aff5afe..5a6fe07aa007b 100644
--- a/pandas/tests/frame/indexing/test_indexing.py
+++ b/pandas/tests/frame/indexing/test_indexing.py
@@ -524,6 +524,16 @@ def test_loc_setitem_boolean_mask_allfalse(self):
         result.loc[result.b.isna(), "a"] = result.a.copy()
         tm.assert_frame_equal(result, df)
 
+    def test_getitem_slice_empty(self):
+        df = DataFrame([[1]], columns=MultiIndex.from_product([["A"], ["a"]]))
+        result = df[:]
+
+        expected = DataFrame([[1]], columns=MultiIndex.from_product([["A"], ["a"]]))
+
+        tm.assert_frame_equal(result, expected)
+        # Ensure df[:] returns a view of df, not the same object
+        assert result is not df
+
     def test_getitem_fancy_slice_integers_step(self):
         df = DataFrame(np.random.default_rng(2).standard_normal((10, 5)))