On Wed, Dec 19, 2012 at 12:39:21PM +0100, Joris Meys wrote:
> The safest way to prevent attacks using an R connector, is managing the
> permissions for the application on your own server. We do that with the
> RStudio Server application we have running. You have to take into account
> that R allows for many interactions with the system. Also file(), dir(),
> unlink() and all sys. functions have the potential to screen and possibly
> alter your system. Not only system() and eval() pose a security problem...
just out of curiosity, how do you disable these functions? Is there
a way to "blacklist" functions as such in R, regardless of what name
is used to call them? Simple string pattern matching (as I understand
Michael's "grepping" suggestion below) can be circumvented by using
the get function, as in
s <- paste(letters[i], collapse = "");
f <- get(s);
f("insidiouscommand");
where i contains suitable indices to produce "system". So the system
function needs disabling as such, as there are innumerable ways to
code up its invocation.
> How to do this exactly, depends very much on both the server and OS
> settings and the specific R connector you use/build. But don't count on R
> alone to provide safety.
Personally, I'd suggest to consider long and hard whether executing
user submitted R code is really necessary, and if that's the case, my
inclination would be to run that on a virtual machine and sandbox that
as much as you can.
Best regards, Jan
> Cheers
> Joris
>
> On Wed, Dec 19, 2012 at 12:28 PM, Michael Weylandt <
> michael.weyla...@gmail.com> wrote:
>
> >
> >
> > On Dec 18, 2012, at 12:48 PM, Etienne S?vin <e.se...@epiconcept.fr> wrote:
> >
> > > Hey all,
> > >
> > > We are building a R connector for our web application.
> > > The user can upload a script so it can be executed on the server.
> > >
> > > Is there a way to scan the script for insidious commands (writing on the
> > > disk for example) and purge them out?
> >
> > Completely, not that I know of: but grepping for system() and eval()
> > should catch a majority of red flags.
> >
> > Michael
> >
> > > I guess a simple search is not enough so is there a way to analyse the
> > > pseudo code?
> > >
> > > Best,
> > >
> > > Etienne
> > >
> > > ______________________________________________
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> >
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> >
>
>
>
> --
> Joris Meys
> Statistical consultant
>
> Ghent University
> Faculty of Bioscience Engineering
> Department of Mathematical Modelling, Statistics and Bio-Informatics
>
> tel : +32 9 264 59 87
> joris.m...@ugent.be
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+- Jan T. Kim -------------------------------------------------------+
| email: jtt...@gmail.com |
| WWW: http://www.jtkim.dreamhosters.com/ |
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