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BUG: sanity check __array_interface__ number of dimensions #28449

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Merged
merged 1 commit into from
Mar 7, 2025
Merged

BUG: sanity check __array_interface__ number of dimensions #28449

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8 changes: 7 additions & 1 deletion numpy/_core/src/multiarray/ctors.c
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Original file line number Diff line number Diff line change
Expand Up @@ -2153,7 +2153,7 @@ PyArray_FromInterface(PyObject *origin)
PyArray_Descr *dtype = NULL;
char *data = NULL;
Py_buffer view;
int i, n;
Py_ssize_t i, n;
npy_intp dims[NPY_MAXDIMS], strides[NPY_MAXDIMS];
int dataflags = NPY_ARRAY_BEHAVED;

Expand Down Expand Up @@ -2269,6 +2269,12 @@ 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);
Expand Down
21 changes: 21 additions & 0 deletions numpy/_core/tests/test_multiarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10358,3 +10358,24 @@ def test_to_device(self):
r"The stream argument in to_device\(\) is not supported"
):
arr.to_device("cpu", stream=1)

def test_array_interface_excess_dimensions_raises():
"""Regression test for gh-27949: ensure too many dims raises ValueError instead of segfault."""

# 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)
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