diff --git a/tests/test_cat_selection_input_immutability.py b/tests/test_cat_selection_input_immutability.py
new file mode 100644
index 000000000..8e1c7e00b
--- /dev/null
+++ b/tests/test_cat_selection_input_immutability.py
@@ -0,0 +1,58 @@
+"""Regression contracts for CAT public-input immutability."""
+
+from __future__ import annotations
+
+import numpy as np
+
+from fast_mlsirm.test_design import item_information, select_cat_item
+from fast_mlsirm.types import MLSIRMParams
+
+
+def _bank() -> tuple[MLSIRMParams, np.ndarray]:
+    """Return a small one-dimensional calibrated bank and factor map."""
+    discrimination = np.array([0.8, 1.1, 1.4, 1.7], dtype=np.float64)
+    bank = MLSIRMParams(
+        theta=np.array([[0.0]], dtype=np.float64),
+        alpha=np.log(discrimination),
+        b=np.array([-1.0, -0.2, 0.4, 1.2], dtype=np.float64),
+        xi=np.zeros((1, 1), dtype=np.float64),
+        zeta=np.zeros((4, 1), dtype=np.float64),
+        tau=-30.0,
+    )
+    return bank, np.zeros(4, dtype=np.int64)
+
+
+def test_item_information_does_not_mutate_theta_or_factor_map() -> None:
+    """Rust marshalling for item information leaves caller arrays unchanged."""
+    bank, factor_id = _bank()
+    theta = np.array([-0.5], dtype=np.float64)
+    theta_before = theta.copy()
+    factor_before = factor_id.copy()
+
+    item_information(bank, factor_id, theta=theta, model="MIRT")
+
+    assert np.array_equal(theta, theta_before)
+    assert np.array_equal(factor_id, factor_before)
+
+
+def test_cat_selection_does_not_mutate_public_arrays() -> None:
+    """Rust selection marshalling preserves theta, factor, and administered inputs."""
+    bank, factor_id = _bank()
+    theta = np.array([0.25], dtype=np.float64)
+    administered = np.array([2, 0], dtype=np.int64)
+    theta_before = theta.copy()
+    factor_before = factor_id.copy()
+    administered_before = administered.copy()
+
+    selected = select_cat_item(
+        bank,
+        factor_id,
+        theta=theta,
+        administered=administered,
+        model="MIRT",
+    )
+
+    assert selected in {1, 3}
+    assert np.array_equal(theta, theta_before)
+    assert np.array_equal(factor_id, factor_before)
+    assert np.array_equal(administered, administered_before)