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The following content comes from “https://lwn.net/Articles/574215/“.
The failure of pysandbox
By Jake Edge, November 20, 2013
Running applications securely, such that they cannot escape confinement and affect other parts of the system, is the general goal of various types of sandboxes. They can be used to safely run untrusted code, for example. Java (in)famously has sandboxing built into the language, and pysandbox was an attempt to do something similar for Python. But the developer of pysandbox, Victor Stinner, recently declared that the project has failed in its goals and warned others away from that style of sandbox. There are some useful lessons in Stinner’s experience that others looking at sandboxes will benefit from.
Pysandbox takes the approach of allowing semi-arbitrary Python to be run in a protected sandbox namespace. While the goal might be to allow all of the Python language, that has led to several different ways to escape the confinement. The sandbox does attempt to provide a portable mechanism for running some Python code safely, using the standard CPython interpreter. Unfortunately, as his declaration made clear, Stinner is convinced that pysandbox is the wrong approach.
Stinner’s post to the python-dev mailing list is worth reading in full. He starts with a bit of history that includes some of the difficulties faced by the project over the years. As time went on, more and more holes were found in the sandbox, which required restricting various Python language features so that they couldn’t be used to escape. Recently, a security challenge targeted pysandbox and found two vulnerabilities in less than a day. This has led him to two conclusions. The first is that “pysandbox is broken“ at a fundamental level:
I now agree that putting a sandbox in CPython is the wrong design. There are too many ways to escape the untrusted namespace using the various introspection features of the Python language. To guarantee the [safety] of a security product, the code should be [carefully] audited and the code to review must be as small as possible. Using pysandbox, the “code” is the whole Python core which is a really huge code base. For example, the Python and Objects directories of Python 3.4 contain more than 126,000 lines of C code.
The security of pysandbox is the security of its weakest part. A single bug is enough to escape the whole sandbox.
He outlined some of the kinds of problems that were found. For example, the builtins dictionary could be modified in various ways to circumvent the sandbox functions and escape. Any segmentation fault in the CPython executable (there are known “crashers” of this sort) could also be used to break out of confinement.
The two most recent vulnerabilities were some of the most fundamental. One used the compile() function to get access to the contents of arbitrary disk files (using a syntax error to print lines as part of the traceback message). The other used a traceback object to unwind the stack frame to one in the trusted namespace, then use the f_globals attribute to retrieve a global object. In both cases, the fix limited the usefulness of pysandbox even further.
The second fundamental flaw is that pysandbox “cannot be used in practice“, Stinner said. Because so many restrictions have needed to be added, pysandbox cannot be used for anything “more complex than evaluating ‘1+(2*3)’“. Basic language constructs like “del dict[key]” have been removed because they can be used to modify builtins and break out of the restricted namespace.
He notes that various folks had contacted him about using pysandbox in web applications, so he believes there is a real need for the functionality. He ended his message with a call for information on alternative approaches beyond the PyPy sandbox he already knows about. Based on what he has learned, he believes a different approach, outside of the standard CPython interpreter, will be required:
To build a secure sandbox, the whole Python process must be put in an external sandbox. There are for example projects using Linux SECCOMP security feature to isolate the Python process.
Several developers spoke up to thank Stinner for his analysis and to laud his admission of a defeat of sorts. He set out to create a secure CPython-based sandbox and ended up recognizing that it may well be an unattainable goal. As Python benevolent dictator for life (BDFL) Guido van Rossum put it: “Negative results are also results, and they need to be published.“
In addition, several posters were not particularly surprised by the outcome Stinner reported. Nick Coghlan noted the “many JVM vulnerabilities“ as one indication that sandboxing is a difficult problem to solve. He continued: “the only ones I even remotely trust are the platform level mechanisms that form the foundation of the various PaaS [platform as a service] services, including SELinux and Linux containers.“ He is skeptical of trying to have sandboxes that are cross-platform or in-process because of the attack surfaces of both CPython and Java.
The PyPy solution may make sense for some, as Maciej Fijalkowski pointed out, but it is a very different model. A special PyPy interpreter is created that cannot do any library or system calls, but instead sends the operation name and arguments to stdout and waits for a response on stdin. In that way, an outer process completely controls the sandboxed program’s interaction with the rest of the system. It may be more difficult to use than was envisioned for pysandbox, however.
Creating a sandbox is clearly a difficult problem—solutions are often quite fragile. But the need to be able to safely run more or less arbitrary code is real. In the thread, Terry Reedy listed a number of sites that accept and run Python code, while Stinner noted a Python shell web application that uses Google’s App Engine; all of those use some kind of sandbox—presumably one at the operating system level. But Stinner’s tale should serve as a cautionary one to anyone considering a CPython-based solution—or the equivalent for other languages.