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author Guido van Rossum <guido@python.org>
date Thu, 17 Jul 1997 16:29:42 +0000
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1 \chapter{Restricted Execution}
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2
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3 In general, Python programs have complete access to the underlying
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4 operating system throug the various functions and classes, For
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5 example, a Python program can open any file for reading and writing by
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6 using the \code{open()} built-in function (provided the underlying OS
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7 gives you permission!). This is exactly what you want for most
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8 applications.
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9
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10 There exists a class of applications for which this ``openness'' is
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11 inappropriate. Take Grail: a web browser that accepts ``applets'',
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12 snippets of Python code, from anywhere on the Internet for execution
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13 on the local system. This can be used to improve the user interface
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14 of forms, for instance. Since the originator of the code is unknown,
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15 it is obvious that it cannot be trusted with the full resources of the
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16 local machine.
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17
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18 \emph{Restricted execution} is the basic framework in Python that allows
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19 for the segregation of trusted and untrusted code. It is based on the
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20 notion that trusted Python code (a \emph{supervisor}) can create a
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21 ``padded cell' (or environment) with limited permissions, and run the
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22 untrusted code within this cell. The untrusted code cannot break out
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23 of its cell, and can only interact with sensitive system resources
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24 through interfaces defined and managed by the trusted code. The term
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25 ``restricted execution'' is favored over ``safe-Python''
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26 since true safety is hard to define, and is determined by the way the
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27 restricted environment is created. Note that the restricted
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28 environments can be nested, with inner cells creating subcells of
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29 lesser, but never greater, privilege.
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30
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31 An interesting aspect of Python's restricted execution model is that
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32 the interfaces presented to untrusted code usually have the same names
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33 as those presented to trusted code. Therefore no special interfaces
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34 need to be learned to write code designed to run in a restricted
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35 environment. And because the exact nature of the padded cell is
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36 determined by the supervisor, different restrictions can be imposed,
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37 depending on the application. For example, it might be deemed
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38 ``safe'' for untrusted code to read any file within a specified
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39 directory, but never to write a file. In this case, the supervisor
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40 may redefine the built-in
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41 \code{open()} function so that it raises an exception whenever the
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42 \var{mode} parameter is \code{'w'}. It might also perform a
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43 \code{chroot()}-like operation on the \var{filename} parameter, such
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44 that root is always relative to some safe ``sandbox'' area of the
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45 filesystem. In this case, the untrusted code would still see an
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46 built-in \code{open()} function in its environment, with the same
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47 calling interface. The semantics would be identical too, with
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48 \code{IOError}s being raised when the supervisor determined that an
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49 unallowable parameter is being used.
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50
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51 The Python run-time determines whether a particular code block is
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52 executing in restricted execution mode based on the identity of the
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53 \code{__builtins__} object in its global variables: if this is (the
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54 dictionary of) the standard \code{__builtin__} module, the code is
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55 deemed to be unrestricted, else it is deemed to be restricted.
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56
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57 Python code executing in restricted mode faces a number of limitations
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58 that are designed to prevent it from escaping from the padded cell.
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59 For instance, the function object attribute \code{func_globals} and the
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60 class and instance object attribute \code{__dict__} are unavailable.
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61
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62 Two modules provide the framework for setting up restricted execution
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63 environments:
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64
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65 \begin{description}
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66
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67 \item[rexec]
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68 --- Basic restricted execution framework.
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69
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70 \item[Bastion]
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71 --- Providing restricted access to objects.
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72
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73 \end{description}