diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 222790cfbef6c..f2e646978b3c9 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -1279,6 +1279,7 @@ Groupby/resample/rolling
 - Bug in :meth:`Series.resample` raising error when resampling non-nanosecond resolutions out of bounds for nanosecond precision (:issue:`57427`)
 - Bug in :meth:`Series.rolling.var` and :meth:`Series.rolling.std` computing incorrect results due to numerical instability. (:issue:`47721`, :issue:`52407`, :issue:`54518`, :issue:`55343`)
 - Bug in :meth:`DataFrame.groupby` methods when operating on NumPy-nullable data failing when the NA mask was not C-contiguous (:issue:`61031`)
+- Bug in :meth:`DataFrame.groupby` when grouping by a Series and that Series was modified after calling :meth:`DataFrame.groupby` but prior to the groupby operation (:issue:`63219`)
 
 Reshaping
 ^^^^^^^^^
diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index 98d9fbe1f87c5..eacde2e9661a8 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -460,6 +460,8 @@ def __init__(
         dropna: bool = True,
         uniques: ArrayLike | None = None,
     ) -> None:
+        if isinstance(grouper, Series):
+            grouper = grouper.copy(deep=False)
         self.level = level
         self._orig_grouper = grouper
         grouping_vector = _convert_grouper(index, grouper)
diff --git a/pandas/tests/copy_view/test_methods.py b/pandas/tests/copy_view/test_methods.py
index 49ce689e5f517..dc0bc7e476a02 100644
--- a/pandas/tests/copy_view/test_methods.py
+++ b/pandas/tests/copy_view/test_methods.py
@@ -226,6 +226,19 @@ def test_groupby_column_index_in_references():
     tm.assert_frame_equal(result, expected)
 
 
+def test_groupby_modify_series():
+    # https://github.com/pandas-dev/pandas/issues/63219
+    # Modifying a Series after using it to groupby should not impact
+    # the groupby operation.
+    ser = Series([1, 2, 1])
+    df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
+    gb = df.groupby(ser)
+    ser.iloc[0] = 100
+    result = gb.sum()
+    expected = DataFrame({"a": [4, 2], "b": [10, 5]}, index=[1, 2])
+    tm.assert_frame_equal(result, expected)
+
+
 def test_rename_columns():
     # Case: renaming columns returns a new dataframe
     # + afterwards modifying the result