# cpython-2.6-fixed / Doc / librestricted.tex

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 \chapter{Restricted Execution} \label{restricted} In general, Python programs have complete access to the underlying operating system throug the various functions and classes, For example, a Python program can open any file for reading and writing by using the \code{open()} built-in function (provided the underlying OS gives you permission!). This is exactly what you want for most applications. There exists a class of applications for which this openness'' is inappropriate. Take Grail: a web browser that accepts applets'', snippets of Python code, from anywhere on the Internet for execution on the local system. This can be used to improve the user interface of forms, for instance. Since the originator of the code is unknown, it is obvious that it cannot be trusted with the full resources of the local machine. \emph{Restricted execution} is the basic framework in Python that allows for the segregation of trusted and untrusted code. It is based on the notion that trusted Python code (a \emph{supervisor}) can create a padded cell' (or environment) with limited permissions, and run the untrusted code within this cell. The untrusted code cannot break out of its cell, and can only interact with sensitive system resources through interfaces defined and managed by the trusted code. The term restricted execution'' is favored over safe-Python'' since true safety is hard to define, and is determined by the way the restricted environment is created. Note that the restricted environments can be nested, with inner cells creating subcells of lesser, but never greater, privilege. An interesting aspect of Python's restricted execution model is that the interfaces presented to untrusted code usually have the same names as those presented to trusted code. Therefore no special interfaces need to be learned to write code designed to run in a restricted environment. And because the exact nature of the padded cell is determined by the supervisor, different restrictions can be imposed, depending on the application. For example, it might be deemed safe'' for untrusted code to read any file within a specified directory, but never to write a file. In this case, the supervisor may redefine the built-in \code{open()} function so that it raises an exception whenever the \var{mode} parameter is \code{'w'}. It might also perform a \code{chroot()}-like operation on the \var{filename} parameter, such that root is always relative to some safe sandbox'' area of the filesystem. In this case, the untrusted code would still see an built-in \code{open()} function in its environment, with the same calling interface. The semantics would be identical too, with \code{IOError}s being raised when the supervisor determined that an unallowable parameter is being used. The Python run-time determines whether a particular code block is executing in restricted execution mode based on the identity of the \code{__builtins__} object in its global variables: if this is (the dictionary of) the standard \code{__builtin__} module, the code is deemed to be unrestricted, else it is deemed to be restricted. Python code executing in restricted mode faces a number of limitations that are designed to prevent it from escaping from the padded cell. For instance, the function object attribute \code{func_globals} and the class and instance object attribute \code{__dict__} are unavailable. Two modules provide the framework for setting up restricted execution environments: \begin{description} \item[rexec] --- Basic restricted execution framework. \item[Bastion] --- Providing restricted access to objects. \end{description} \begin{seealso} \seetext{Andrew Kuchling, Restricted Execution HOWTO.'' Available online at \url{http://www.python.org/doc/howto/rexec/}.} \end{seealso}