Safe eval

docs/source/utils.rst

@@ -80,3 +80,8 @@ Ordering
 --------
 .. automodule:: monai.utils.ordering
   :members:
+
+Safe Evaluation
+---------------
+.. automodule:: monai.utils.safeeval
+  :members:

monai/bundle/scripts.py

@@ -25,6 +25,7 @@
 from textwrap import dedent
 from typing import Any
 
+import numpy as np
 import torch
 from torch.cuda import is_available
 
@@ -51,6 +52,7 @@
     min_version,
     optional_import,
     pprint_edges,
+    safe_eval,
 )
 
 validate, _ = optional_import("jsonschema", name="validate")
@@ -158,10 +160,12 @@ def _get_fake_spatial_shape(shape: Sequence[str | int], p: int = 1, n: int = 1,
             if i == "*":
                 ret.append(any)
             else:
-                for c in _get_var_names(i):
-                    if c not in ["p", "n"]:
-                        raise ValueError(f"only support variables 'p' and 'n' so far, but got: {c}.")
-                ret.append(eval(i, {"p": p, "n": n}))
+                bad_names = set(c for c in _get_var_names(i) if c not in {"p", "n"})
+                if bad_names:
+                    raise ValueError(f"Only variables `p` and `n` currently supported. Invalid names: {bad_names}")
+
+                # evaluate using Numpy types to prevent slow Python DoS attacks
+                ret.append(int(safe_eval(i, {"p": np.int32(p), "n": np.int32(n)}, rewrite_np=True)))
         else:
             raise ValueError(f"spatial shape items must be int or string, but got: {type(i)} {i}.")
     return tuple(ret)

monai/utils/__init__.py

@@ -137,6 +137,7 @@
     torch_profiler_time_cpu_gpu,
     torch_profiler_time_end_to_end,
 )
+from .safeeval import SAFE_TYPES, safe_eval
 from .state_cacher import StateCacher
 from .tf32 import detect_default_tf32, has_ampere_or_later
 from .type_conversion import (

monai/utils/ordering.py

@@ -148,7 +148,7 @@ def _order_template(self, template: np.ndarray) -> np.ndarray:
         else:
             rows, columns, depths = (template.shape[0], template.shape[1], template.shape[2])
 
-        sequence = eval(f"self.{self.ordering_type}_idx")(rows, columns, depths)
+        sequence = getattr(self, f"{self.ordering_type}_idx")(rows, columns, depths)
 
         ordering = np.array([template[tuple(e)] for e in sequence])
 

monai/utils/safeeval.py

@@ -0,0 +1,106 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import ast
+from collections.abc import Mapping, Sequence
+from typing import Any
+
+import numpy as np
+
+__all__ = ["SAFE_TYPES", "safe_eval"]
+
+# default set of safe AST node types
+SAFE_TYPES: Sequence[type] = (
+    ast.Expression,
+    ast.Name,
+    ast.Load,
+    ast.Constant,
+    ast.BinOp,
+    ast.UnaryOp,
+    ast.Add,
+    ast.Sub,
+    ast.Mult,
+    ast.Div,
+    ast.FloorDiv,
+    ast.Pow,
+    ast.Mod,
+    ast.USub,
+    ast.UAdd,
+)
+
+
+class _RewriteConstNp(ast.NodeTransformer):
+    """Replaces int and float constants in the tree with those wrapped in Numpy types."""
+
+    def __init__(self, int_type_str: str, float_type_str: str):
+        self.int_type_str = int_type_str
+        self.float_type_str = float_type_str
+
+    def visit_Constant(self, node):
+        if isinstance(node.value, (int, float)):
+            type_str = self.int_type_str if isinstance(node.value, int) else self.float_type_str
+            return ast.parse(f"{type_str}({node.value})")
+
+        return node
+
+
+def safe_eval(
+    expr: str,
+    globals_vars: Mapping[str, Any] | None = None,
+    locals_vars: Mapping[str, object] | None = None,
+    allowed_types: Sequence[type] = SAFE_TYPES,
+    rewrite_np: bool = False,
+    int_type_str: str = "np.int32",
+    float_type_str: str = "np.float32",
+) -> Any:
+    """
+    Evaluate the Python expression `expr` using `eval`, but only if it is a safe expression in that its parsed AST
+    contains nodes whose types are given in `allowed_types`. This ensures unsafe node types are excluded, if these
+    are present in the AST a ValueError is raised. The default set of such types in `SAFE_TYPES` ensures only
+    expressions with constants and names can be evaluated, so excludes attribute access, indexing, and calls. Code
+    injection is infeasible through such expressions, so this is a safe and secure way of evaluating simple expressions.
+
+    If `rewrite_np` is True, int and float constants in the given expression will be wrapped with Numpy types as given
+    by `int_type_str` and `float_type_str`. These are expected to be constructor names prefixed with `np.` as Numpy
+    will be present in the expression global variables under that name. The values can be changed to other types if
+    needed, such as "int64". One advantage of doing this is to avoid denial-of-service attacks by attempting to evaluate
+    an expressoini which is incredibly slow under native Python but fast (though potentially erroneous) under Numpy.
+
+    Args:
+        expr: expression to evaluate, this will be stripped before parsing to avoid indentation complaints
+        globals_vars: global variable mapping, this will be treated as read-only for this function, unlike `eval`
+        locals_vars: local variable mapping
+        allowed_types: sequence of allowed AST types which can be found in `expr` when parsed
+        rewrite_np: if True, wrap int or float literals in Numpy types
+        int_type_str: int Numpy wrapping type string
+        float_type_str: float Numpy wrapping type string
+
+    Raises:
+        ValueError: raised when any node in the AST parsed from `expr` has a type not in `allowed_types`
+
+    Returns:
+        The evaluated expression value, using `eval` with `globals_vars` and `locals_vars`
+    """
+    parsed = ast.parse(expr.strip(), mode="eval")
+
+    # collect nodes in the AST which aren't permitted and unparse them for inclusion in the exception message
+    disallowed = [ast.unparse(n) for n in ast.walk(parsed) if not isinstance(n, tuple(allowed_types))]
+
+    if disallowed:
+        raise ValueError(f"Unsafe expression `{expr}` not evaluated, contains disallowed components: {disallowed}")
+
+    if rewrite_np:
+        parsed = _RewriteConstNp(int_type_str, float_type_str).visit(parsed)
+        locals_vars = {"np": np, **(locals_vars or {})}
+
+    return eval(expr, dict(globals_vars) if globals_vars else None, locals_vars)

tests/utils/test_alias.py

@@ -23,7 +23,10 @@
 
 
 class TestModuleAlias(unittest.TestCase):
-    """check that 'import monai.xx.file_name' returns a module"""
+    """
+    Check that 'import monai.xx.file_name' returns a module. Note that this test will fail if a module has the same name
+    as a member of that module (or any other) which is imported in a `__init__.py` file.
+    """
 
     def test_files(self):
         src_dir = os.path.dirname(TESTS_PATH)

tests/utils/test_safe_eval.py

@@ -0,0 +1,67 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+import ast
+import unittest
+
+from parameterized import parameterized
+
+from monai.utils import safe_eval
+
+GOOD_EXPRS = [
+    ("1+2", None, None, 3),
+    ("     1    +     2   ", None, None, 3),
+    ("1+2+x", {"x": 4}, None, 7),
+    ("1+2+x", None, {"x": 4}, 7),
+    ("1*2+x", {"x": 4}, None, 6),
+    ("(1+2)*3", None, None, 9),
+    ("foo+bar", {"foo": 1030}, {"bar": 204}, 1234),
+]
+
+BAD_EXPRS = [("foo()",), ("foo.bar",), ("foo[123]",), ("(1,2)",), ("[3,4]",), ("int.__class__.__init__.__globals__",)]
+
+
+class TestSafeEval(unittest.TestCase):
+    @parameterized.expand(GOOD_EXPRS)
+    def test_good_exprs(self, expr, globals_vars, locals_vars, expected):
+        """Test valid expressions with globals/locals evaluate to correct values."""
+        result = safe_eval(expr, globals_vars, locals_vars)
+        self.assertEqual(result, expected)
+
+    @parameterized.expand(GOOD_EXPRS)
+    def test_good_exprs_np(self, expr, globals_vars, locals_vars, expected):
+        """Test valid expressions with globals/locals evaluate to correct values with Numpy wrapping."""
+        result = safe_eval(expr, globals_vars, locals_vars, rewrite_np=True)
+        self.assertEqual(result, expected)
+
+    @parameterized.expand(BAD_EXPRS)
+    def test_bad_exprs(self, expr):
+        """Test bad expressions correctly raise ValueError."""
+        with self.assertRaises(ValueError):
+            safe_eval(expr)
+
+        with self.assertRaises(ValueError):
+            safe_eval(expr, rewrite_np=True)
+
+    def test_allowed_types(self):
+        """Test restricting the allowed list of types."""
+        allowed = [ast.Expression, ast.Constant, ast.BinOp, ast.Add]
+        result = safe_eval("1+2", allowed_types=allowed)
+        self.assertEqual(result, 3)
+
+        with self.assertRaises(ValueError):
+            safe_eval("1*2", allowed_types=allowed)
+
+
+if __name__ == "__main__":
+    unittest.main()