numpy
diff --git a/‎numpy/_core/src/multiarray/ctors.c
Copy file name to clipboardExpand all lines: numpy/_core/src/multiarray/ctors.c
+6Lines changed: 6 additions & 0 deletions b/‎numpy/_core/src/multiarray/ctors.c
Copy file name to clipboardExpand all lines: numpy/_core/src/multiarray/ctors.c
+6Lines changed: 6 additions & 0 deletions
diff --git a/‎numpy/_core/tests/test_multiarray.py
Copy file name to clipboardExpand all lines: numpy/_core/tests/test_multiarray.py
+23Lines changed: 23 additions & 0 deletions b/‎numpy/_core/tests/test_multiarray.py
Copy file name to clipboardExpand all lines: numpy/_core/tests/test_multiarray.py
+23Lines changed: 23 additions & 0 deletions
@@ -2250,6 +2250,12 @@ PyArray_FromInterface(PyObject *origin)
     /* Get dimensions from shape tuple */
     else {
         n = PyTuple_GET_SIZE(attr);
+        if (n > NPY_MAXDIMS) {
+            PyErr_Format( PyExc_ValueError,
+                          "number of dimensions must be within [0, %d], got %d",
+                          NPY_MAXDIMS, n );
+            goto fail;
+        }
         for (i = 0; i < n; i++) {
             PyObject *tmp = PyTuple_GET_ITEM(attr, i);
             dims[i] = PyArray_PyIntAsIntp(tmp);
 
@@ -10420,3 +10420,26 @@ def test_to_device(self):
             r"The stream argument in to_device\(\) is not supported"
         ):
             arr.to_device("cpu", stream=1)
+
+def test_asanyarray_excess_dimensions_raises():
+    """Regression test for gh-27949: ensure too many dims raises ValueError instead of segfault."""
+    import numpy as np
+    import pytest
+
+    # Dummy object to hold a custom __array_interface__
+    class DummyArray:
+        def __init__(self, interface):
+            # Attach the array interface dict to mimic an array
+            self.__array_interface__ = interface
+
+    # Create a base array (scalar) and copy its interface
+    base = np.array(42)  # base can be any scalar or array
+    interface = dict(base.__array_interface__)
+
+    # Modify the shape to exceed NumPy's dimension limit (NPY_MAXDIMS, typically 64)
+    interface['shape'] = tuple([1] * 136)  # match the original bug report 
+
+    dummy = DummyArray(interface)
+    # Now, using np.asanyarray on this dummy should trigger a ValueError (not segfault)
+    with pytest.raises(ValueError, match="dimensions must be within"):
+        np.asanyarray(dummy)