[R-pkg-devel] Sanitize Input Code for a Shiny App

[Tomas Kalibera]

On 3/1/23 07:35, Matthias Gondan wrote:
> For the record, here's the documentation of the Prolog sandbox,
>
> https://www.swi-prolog.org/pldoc/doc/_SWI_/library/sandbox.pl
>
> You get an idea of the implementation by clicking at the ":-" icons. It does not seem too complicated, but I might be too optimistic. It would be very nice to have such a thing in R, and I would be willing to help if someone takes the lead.

 From my (very quick) look at the page, my understanding is that it is 
analyzing Prolog code to decide whether it is safe to execute or not. If 
my reading is correct, please let me reiterate that this would not be a 
good strategy for R. As Simon already wrote, R is a very dynamic 
language allowing to change almost anything at runtime. It is not 
possible to correctly and effectively reason about what an R program 
could do. Trying to do this would be a waste of effort which might only 
provide false sense of security. R cannot be made safe for such uses 
this way. While enough as a show stopper, it is more than that, R 
doesn't have a specification, any such tools would have to be written 
against a specific R release. Also, in practice one would probably also 
want to use some extension packages, which may again do anything (in 
native code).

With R, I would only think of ensuring security at the machine level, as 
discussed already - via virtual machines, containers (with care, not all 
are sandboxes), etc. That would be much safer, much less work, and could 
re-use existing technologies.

Tomas


>
> Best regards,
>
> Matthias
>
>> Am 01.03.2023 um 01:52 schrieb Bill Denney <bill using denney.ws>:
>>
>> Hi Simon and Ivan,
>>
>> Thanks for confirming my suspicions.  The most common case for our code
>> would be generally trusted users within an organization.  So, the main
>> threat is lower.  But, there may be scenarios that also allow use outside
>> organizations.
>>
>> I think that in the end, we will likely do some minimal sanitization of the
>> input, but then we will also ensure that we do anything in a container with
>> limits applied from the outside, too.
>>
>> Thanks,
>>
>> Bill
>>
>> On Sun, Feb 26, 2023, 4:57 PM Simon Urbanek <simon.urbanek using r-project.org>
>> wrote:
>>
>>> Bill,
>>>
>>> the short answer is you can't limit anything at R level. Any attempts to
>>> create a list of "bad" commands are trivial to circumvent since you can
>>> compute on the language in R, so you can construct and call functions with
>>> trivial operations. Similarly, since R allows the loading of binary code
>>> the same applies for arbitrary code. So if you give users access to R, you
>>> should assume that is equivalent to allowing arbitrary code execution.
>>> Therefore all you can do is limit the resources and reach - as you pointed
>>> out using a container is a good idea so each session is only limited to a
>>> single container that goes away when the session ends. Similarly you can
>>> restrict main parts of R and the system to be read-only in the container.
>>>
>>> In practice, that's why real analytic systems are about provenance rather
>>> than prevention. For example, in RCloud all code is first committed to a
>>> git repository outside of the container before it can be executed, so
>>> malicious users can do whatever they want, but they cannot hide the
>>> malicious code they used as the container cannot manipulate the history.
>>>
>>> As for package installation - again, it's impossible to prevent it in
>>> general unless you make everything read-only which also prevents the users
>>> from doing meaningful work. So the real question what do you want to allow
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