Files
edx-platform/xmodule/capa/safe_exec/safe_exec.py
Soban Javed 9eba9f983a refactor!: move common/lib/capa/capa to xmodule/capa
As part of dissolving our sub-projects in edx-platform, we are moving this package under the xmodule directory.
We have fixed all the occurences of import of this package and also fixed all documents related references.
This might break your platform if you have any reference of `import capa` or `from capa import` in your codebase or in any Xblock.

Ref: https://openedx.atlassian.net/browse/BOM-2582
2022-07-19 12:20:04 +05:00

193 lines
6.1 KiB
Python

"""Capa's specialized use of codejail.safe_exec."""
import hashlib
from codejail.safe_exec import SafeExecException, json_safe
from codejail.safe_exec import not_safe_exec as codejail_not_safe_exec
from codejail.safe_exec import safe_exec as codejail_safe_exec
from edx_django_utils.monitoring import function_trace
import six
from six import text_type
from . import lazymod
from .remote_exec import is_codejail_rest_service_enabled, get_remote_exec
# Establish the Python environment for Capa.
# Capa assumes float-friendly division always.
# The name "random" is a properly-seeded stand-in for the random module.
CODE_PROLOG = """\
from __future__ import absolute_import, division
import os
os.environ["OPENBLAS_NUM_THREADS"] = "1" # See TNL-6456
import random2 as random_module
import sys
from six.moves import xrange
random = random_module.Random(%r)
random.Random = random_module.Random
sys.modules['random'] = random
"""
ASSUMED_IMPORTS = [
("numpy", "numpy"),
("math", "math"),
("scipy", "scipy"),
("calc", "calc"),
("eia", "eia"),
("chemcalc", "chem.chemcalc"),
("chemtools", "chem.chemtools"),
("miller", "chem.miller"),
("draganddrop", "verifiers.draganddrop"),
]
# We'll need the code from lazymod.py for use in safe_exec, so read it now.
lazymod_py_file = lazymod.__file__
if lazymod_py_file.endswith("c"):
lazymod_py_file = lazymod_py_file[:-1]
with open(lazymod_py_file) as f:
lazymod_py = f.read()
LAZY_IMPORTS = [lazymod_py]
for name, modname in ASSUMED_IMPORTS:
LAZY_IMPORTS.append("{} = LazyModule('{}')\n".format(name, modname))
LAZY_IMPORTS = "".join(LAZY_IMPORTS)
def update_hash(hasher, obj):
"""
Update a `hashlib` hasher with a nested object.
To properly cache nested structures, we need to compute a hash from the
entire structure, canonicalizing at every level.
`hasher`'s `.update()` method is called a number of times, touching all of
`obj` in the process. Only primitive JSON-safe types are supported.
"""
hasher.update(six.b(str(type(obj))))
if isinstance(obj, (tuple, list)):
for e in obj:
update_hash(hasher, e)
elif isinstance(obj, dict):
for k in sorted(obj):
update_hash(hasher, k)
update_hash(hasher, obj[k])
else:
hasher.update(six.b(repr(obj)))
@function_trace('safe_exec')
def safe_exec(
code,
globals_dict,
random_seed=None,
python_path=None,
extra_files=None,
cache=None,
limit_overrides_context=None,
slug=None,
unsafely=False,
):
"""
Execute python code safely.
`code` is the Python code to execute. It has access to the globals in `globals_dict`,
and any changes it makes to those globals are visible in `globals_dict` when this
function returns.
`random_seed` will be used to see the `random` module available to the code.
`python_path` is a list of filenames or directories to add to the Python
path before execution. If the name is not in `extra_files`, then it will
also be copied into the sandbox.
`extra_files` is a list of (filename, contents) pairs. These files are
created in the sandbox.
`cache` is an object with .get(key) and .set(key, value) methods. It will be used
to cache the execution, taking into account the code, the values of the globals,
and the random seed.
`limit_overrides_context` is an optional string to be used as a key on
the `settings.CODE_JAIL['limit_overrides']` dictionary in order to apply
context-specific overrides to the codejail execution limits.
If `limit_overrides_context` is omitted or not present in limit_overrides,
then use the default limits specified insettings.CODE_JAIL['limits'].
`slug` is an arbitrary string, a description that's meaningful to the
caller, that will be used in log messages.
If `unsafely` is true, then the code will actually be executed without sandboxing.
"""
# Check the cache for a previous result.
if cache:
safe_globals = json_safe(globals_dict)
md5er = hashlib.md5()
md5er.update(repr(code).encode('utf-8'))
update_hash(md5er, safe_globals)
key = "safe_exec.%r.%s" % (random_seed, md5er.hexdigest())
cached = cache.get(key)
if cached is not None:
# We have a cached result. The result is a pair: the exception
# message, if any, else None; and the resulting globals dictionary.
emsg, cleaned_results = cached
globals_dict.update(cleaned_results)
if emsg:
raise SafeExecException(emsg)
return
# Create the complete code we'll run.
code_prolog = CODE_PROLOG % random_seed
if is_codejail_rest_service_enabled():
data = {
"code": code_prolog + LAZY_IMPORTS + code,
"globals_dict": globals_dict,
"python_path": python_path,
"limit_overrides_context": limit_overrides_context,
"slug": slug,
"unsafely": unsafely,
"extra_files": extra_files,
}
emsg, exception = get_remote_exec(data)
else:
# Decide which code executor to use.
if unsafely:
exec_fn = codejail_not_safe_exec
else:
exec_fn = codejail_safe_exec
# Run the code! Results are side effects in globals_dict.
try:
exec_fn(
code_prolog + LAZY_IMPORTS + code,
globals_dict,
python_path=python_path,
extra_files=extra_files,
limit_overrides_context=limit_overrides_context,
slug=slug,
)
except SafeExecException as e:
# Saving SafeExecException e in exception to be used later.
exception = e
emsg = text_type(e)
else:
emsg = None
# Put the result back in the cache. This is complicated by the fact that
# the globals dict might not be entirely serializable.
if cache:
cleaned_results = json_safe(globals_dict)
cache.set(key, (emsg, cleaned_results))
# If an exception happened, raise it now.
if emsg:
raise exception