diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 549d49aaa1853..e3fc3a24cfe00 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -318,6 +318,7 @@ Bug fixes
 ~~~~~~~~~
 - Fixed bug in :class:`SparseDtype` for equal comparison with na fill value. (:issue:`54770`)
 - Fixed bug in :meth:`.DataFrameGroupBy.median` where nat values gave an incorrect result. (:issue:`57926`)
+- Fixed bug in :meth:`DataFrame.cumsum` which was raising ``IndexError`` if dtype is ``timedelta64[ns]`` (:issue:`57956`)
 - Fixed bug in :meth:`DataFrame.join` inconsistently setting result index name (:issue:`55815`)
 - Fixed bug in :meth:`DataFrame.to_string` that raised ``StopIteration`` with nested DataFrames. (:issue:`16098`)
 - Fixed bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
diff --git a/pandas/core/array_algos/datetimelike_accumulations.py b/pandas/core/array_algos/datetimelike_accumulations.py
index 55942f2c9350d..c3a7c2e4fefb2 100644
--- a/pandas/core/array_algos/datetimelike_accumulations.py
+++ b/pandas/core/array_algos/datetimelike_accumulations.py
@@ -49,7 +49,8 @@ def _cum_func(
     if not skipna:
         mask = np.maximum.accumulate(mask)
 
-    result = func(y)
+    # GH 57956
+    result = func(y, axis=0)
     result[mask] = iNaT
 
     if values.dtype.kind in "mM":
diff --git a/pandas/tests/series/test_cumulative.py b/pandas/tests/series/test_cumulative.py
index 68d7fd8b90df2..9b7b08127a550 100644
--- a/pandas/tests/series/test_cumulative.py
+++ b/pandas/tests/series/test_cumulative.py
@@ -91,6 +91,25 @@ def test_cummin_cummax_datetimelike(self, ts, method, skipna, exp_tdi):
         result = getattr(ser, method)(skipna=skipna)
         tm.assert_series_equal(expected, result)
 
+    def test_cumsum_datetimelike(self):
+        # GH#57956
+        df = pd.DataFrame(
+            [
+                [pd.Timedelta(0), pd.Timedelta(days=1)],
+                [pd.Timedelta(days=2), pd.NaT],
+                [pd.Timedelta(hours=-6), pd.Timedelta(hours=12)],
+            ]
+        )
+        result = df.cumsum()
+        expected = pd.DataFrame(
+            [
+                [pd.Timedelta(0), pd.Timedelta(days=1)],
+                [pd.Timedelta(days=2), pd.NaT],
+                [pd.Timedelta(days=1, hours=18), pd.Timedelta(days=1, hours=12)],
+            ]
+        )
+        tm.assert_frame_equal(result, expected)
+
     @pytest.mark.parametrize(
         "func, exp",
         [