Background chapter on restricted execution. Additional sections are

rexec and bastion.
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Guido van Rossum 1996-10-22 01:10:56 +00:00
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\chapter{Restricted Execution}
In general, executing Python programs have complete access to the
underlying operating system through the various functions and classes
contained in Python's modules. For example, a Python program can open
any file\footnote{Provided the underlying OS gives you permission!}
for reading and writing by using the
\code{open()} built-in function. This is exactly what you want for
most applications.
There is a class of applications for which this ``openness'' is
inappropriate. Imagine a web browser that accepts ``applets'', snippets of
Python code, from anywhere on the Internet for execution on the local
system. 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 Python framework 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) of 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 the term ``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, privledge.
An interesting aspect of Python's restricted execution model is that
the attributes 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
\code{open()} function in its \code{__builtin__} module, 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.
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}

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\chapter{Restricted Execution}
In general, executing Python programs have complete access to the
underlying operating system through the various functions and classes
contained in Python's modules. For example, a Python program can open
any file\footnote{Provided the underlying OS gives you permission!}
for reading and writing by using the
\code{open()} built-in function. This is exactly what you want for
most applications.
There is a class of applications for which this ``openness'' is
inappropriate. Imagine a web browser that accepts ``applets'', snippets of
Python code, from anywhere on the Internet for execution on the local
system. 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 Python framework 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) of 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 the term ``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, privledge.
An interesting aspect of Python's restricted execution model is that
the attributes 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
\code{open()} function in its \code{__builtin__} module, 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.
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}