epicbox2

A Python library to run untrusted code in secure, isolated Docker based sandboxes.

It allows to spawn a process inside one-time Docker container, send data to stdin, and obtain its exit code and stdout/stderr output. It's very similar to what the subprocess module does but additionally you can specify a custom environment for the process (a Docker image) and limit the CPU, memory, disk, and network usage for the running process.

Usage

Run a simple Python script in a one-time Docker container using the python:3.6.5-alpine image:

import epicbox

epicbox.configure(
    profiles=[
        epicbox.Profile('python', 'python:3.6.5-alpine')
    ]
)
files = [{'name': 'main.py', 'content': b'print(42)'}]
limits = {'cputime': 1, 'memory': 64}
result = epicbox.run('python', 'python3 main.py', files=files, limits=limits)

The result value is:

{'exit_code': 0,
 'stdout': b'42\n',
 'stderr': b'',
 'duration': 0.143358,
 'timeout': False,
 'oom_killed': False}

Alternatively, you can also use the session context manager:

from epicbox import create_session

with create_session("python") as session:
    command = (
        "python3 -c 'import sys; "
        'print("stdout data"); print("stderr data", file=sys.stderr)\''
    )
    result = session.exec(command)
    # result contains stdout and stderr

The advantage of a session is that a container will start upon entering the context manager, and commands can be run via exec. The standard run commands will create and start a new container for every command.

Available Limit Options

The available limit options and default values:

DEFAULT_LIMITS = {
    # CPU time in seconds, None for unlimited
    'cputime': 1,
    # Real time in seconds, None for unlimited
    'realtime': 5,
    # Memory in megabytes, None for unlimited
    'memory': 64,

    # limit the max processes the sandbox can have
    # -1 or None for unlimited(default)
    'processes': -1,
}

Advanced usage

A more advanced usage example of epicbox is to compile a C++ program and then run it multiple times on different input data. In this example epicbox will run containers on a dedicated Docker Swarm cluster instead of locally installed Docker engine:

import epicbox

PROFILES = {
    'gcc_compile': {
        'docker_image': 'stepik/epicbox-gcc:6.3.0',
        'user': 'root',
    },
    'gcc_run': {
        'docker_image': 'stepik/epicbox-gcc:6.3.0',
        # It's safer to run untrusted code as a non-root user (even in a container)
        'user': 'sandbox',
        'read_only': True,
        'network_disabled': False,
    },
}
epicbox.configure(profiles=PROFILES, docker_url='tcp://1.2.3.4:2375')

untrusted_code = b"""
// C++ program
#include <iostream>

int main() {
    int a, b;
    std::cin >> a >> b;
    std::cout << a + b << std::endl;
}
"""
# A working directory allows to preserve files created in a one-time container
# and access them from another one. Internally it is a temporary Docker volume.
with epicbox.working_directory() as workdir:
    epicbox.run('gcc_compile', 'g++ -pipe -O2 -static -o main main.cpp',
                files=[{'name': 'main.cpp', 'content': untrusted_code}],
                workdir=workdir)
    epicbox.run('gcc_run', './main', stdin='2 2',
                limits={'cputime': 1, 'memory': 64},
                workdir=workdir)
    # {'exit_code': 0, 'stdout': b'4\n', 'stderr': b'', 'duration': 0.095318, 'timeout': False, 'oom_killed': False}
    epicbox.run('gcc_run', './main', stdin='14 5',
                limits={'cputime': 1, 'memory': 64},
                workdir=workdir)
    # {'exit_code': 0, 'stdout': b'19\n', 'stderr': b'', 'duration': 0.10285, 'timeout': False, 'oom_killed': False}

Installation

epicbox can be installed by running pip install epicbox2. It's tested on Python 3.4+ and Docker 1.12+.