Skip to content

Security: Dynamic import and callable selection from config allows attacker-controlled code execution #732

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
tuanaiseo wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Security: Dynamic import and callable selection from config allows attacker-controlled code execution #732

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
37 changes: 35 additions & 2 deletions src/scivision/io/autoplumber.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,29 @@
import numpy as np


_ALLOWED_IMPORT_PREFIXES = ("scivision",)


def _validate_import_path(import_path: str):
if not isinstance(import_path, str) or not import_path:
raise ValueError("`import` must be a non-empty string.")

parts = import_path.split(".")
if not all(part.isidentifier() for part in parts):
raise ValueError(f"Invalid import path `{import_path}` in configuration.")

if parts[0] not in _ALLOWED_IMPORT_PREFIXES:
raise ValueError(
f"Import path `{import_path}` is not allowed. "
f"Allowed top-level modules: {_ALLOWED_IMPORT_PREFIXES}."
)


def _validate_attr_name(attr: str, field: str):
if not isinstance(attr, str) or not attr or not attr.isidentifier() or attr.startswith("_"):
raise ValueError(f"`{field}` must be a public identifier.")


class DataPipe(NamedTuple):
input: inspect.Parameter
output: inspect.Parameter
Expand All @@ -30,7 +53,12 @@ class AutoPlumber:
def __init__(self, config: dict):

# import the module and get the model object
self._module = importlib.import_module(config["import"])
import_path = config["import"]
_validate_import_path(import_path)
_validate_attr_name(config["model"], "model")
_validate_attr_name(config["prediction_fn"]["call"], "prediction_fn.call")

self._module = importlib.import_module(import_path)
model = getattr(self._module, config["model"])

# we could instantiate the model using the args here
Expand Down Expand Up @@ -96,7 +124,12 @@ class DataPlumber:
def __init__(self, config: dict):

# import the module and get the data function
self._module = importlib.import_module(config["import"])
import_path = config["import"]
_validate_import_path(import_path)
_validate_attr_name(config["class"], "class")
_validate_attr_name(config["func"]["call"], "func.call")

self._module = importlib.import_module(import_path)
data_class = getattr(self._module, config['class'])
self._fn = getattr(data_class, config['func']['call'])

Expand Down