Spent another great day down at HP, talking about implementing E and web-calculus concepts within Twisted and newpb. Tyler Close was kind enough to spend the entire afternoon with me, explaining how his web-calculus works and the design decisions behind it. I'm really excited about implenting this stuff in newpb: I think we can make a system that's both secure and highly usable. Some of the ideas I came away with that I want write up before I forget:

Promises: In addition to Deferred, we can build a Promise. The usage syntax would look like:

p = tub.getReference(url)
when(p.getReady()).addCallback(lambda res: p.trigger())
p2 = Promise(d1) # turn "deferred which fires with an instance" into a Promise
p3 = p2.invoke()
d2 = when(p3)

The Promise object is basically a wrapper around any Deferred that expects to fire with an instance. It has a __getattr__ which lets it pretend to implement any method. Such methods just queue the call and its arguments, then finish immediately, returning a new Promise. Something like:

class Promise:
  def __getattr__(self, methname):
    if self.resolved:
        m = getattr(self.resolution, methname)
        assert callable(m)
        return m
    def newmethod(*args, **kwargs):
        self.calls.append((methname, args, kwargs))
        # except more cleverness in case the method is invoked after the
        # promise is resolved
    return newmethod

When the Deferred fires, all pending calls are invoked on the instance it fired with. Each call also returns a Promise, possibly already fulfilled, with the results of that call, so that p.meth1().meth2() is the asynchronous equivalent of o.meth1().meth2(), or func2(func1(o)). 'p.meth1(); p.meth2()' means that meth2 must be invoked after meth1: I'm not sure what other kind of sequencing promises to make (should we wait until meth1 has finished before invoking meth2?).

If the Deferred errbacks instead, then the Promise is "smashed", which is like an errback. No further method calls are made, any dependent Promises are smashed too.

The idea is to make the asynchronous domain be the normal case, and mark the boundary with the synchronous domain specially. when() would be a function that turns a Promise into a Deferred, with which the transition could be scheduled:

def when(p):
  if not isinstance(p, Promise):
    return defer.succeed(p.resolution)
  if p.resolved:
    return defer.succeed(p.resolution)
    d = defer.Deferred()
    return d

He pointed out that E currently has two separate method invocation syntaxes: 'o.foo()' requires a local reference, and may or may not return a Promise. 'p <- foo()' can accept either a local reference or a Promise, and always returns a Promise. (actually I'm not sure I'm getting this right, but the implication was that there were two forms, one for local and one for remote, whereas Tyler felt that there should only be one).

Then, later, we'll create the RemotePromise, which is a Promise that's associated with a RemoteReference. rp.foo(args) is equivalent to d.addCallback(lambda res: res.callRemote("foo", args)) . When Promises are serialized, they get a clid and show up as another Promises on the far end. You push the waiting as far away as possible, apparently this is the way to reduce the probability of deadlocks.

My main concern with this syntax is that it may confuse the synchronous-domain developers that we (as Twisted) have been trying to gently nudge into the world of asynchronous programming. We're not blocking, but the code looks a lot like that's what's happening. But, once you've stopped thinking that the lack of a .callLater implies immediate execution, the p.meth(args) syntax really is a lot cleaner. You just assume that everything could be a promise, and you use when() if you need to assure that you have an immediate value.

One problem with reference counting is that your peer can force you to retain an object for arbitrarily long times, by just never sending you the decref (and Gifts make things even worse). Tyler's hunch is that distributed reference counting is the wrong approach, and it is more practical to manage object lifetime with the Vat/Tub. Break application processing into units, create a Tub for each unit, when the unit is finished, destroy the Tub. All objects that pass through a Tub are registered (under an unguessable name) in that Tub, so they remain accessible for the lifetime of the Tub, and then become inaccessible when the Tub is destroyed.

To use this well, it must be easy to create new Tubs and destroy them later. These Tubs must be able to share listener ports, which can distinguish the desired Tub by its keyid. To accomplish this with newpb, I think we may need a module-level registry of Listeners, so that two Tubs that are asked to listen on the same port will register with the same Listener. (it might also make sense to use newtub = oldtub.makeTub(), and have the Listener be inherited). We should pay attention to the possibility of sharing a TCP connection to an existing Tub, but keep in mind that separate TLS keys will require separate TCP connections.

Secure PB URLs want a key as the primary specifier, followed by a list of location hints, followed by a Tub-scoped name:

PBY url: pby://key@,foo.com,[::1],loc2,loc3/name
 key is base32(sha1(tub.pubkey))
 unix socket is trickier
 non-authenticated url still requires Tub ID

He also feels that DoS prevention (one of the three reasons for Constraints, the other two being semantic typechecking assertions and API documentation) is difficult to implement and hard to get right, and unlikely to do the complete job that you'd want out of it. He said MarkM burned a lot of cycles trying to build DoS prevention techniques into CapIDL, and it would be worth asking him for his thoughts.

He said one deployment pattern would be to put security proxies in a set of separate processes, which perform deserialization, check arguments, etc, and then pass the results on to the real object. The security proxies would be CPU/memory limited, and there would be one per connection, so that if someone started to abuse their connection, only they would suffer. Once you get to a service large enough to be worried about DoS attacks, you'd want this architecture anyway because then you can distribute it out to multiple machines. I was skeptical about how to go about implementing this sort of proxy: how much CPU time do you give it? If it takes 1ms to deserialize a message that then consumes 1s of server time, do you have to restrict it to 1/1000th the CPU time of the server? Note that other possibilities include strict prioritization of the processes/threads (so the connections are starved until the server becomes idle), and enforcing one-at-a-time processing of messages.

His approach in web-amp was just to limit each serialized argument to 8kb. The objection that this might not be enough is countered by the fact that if you're sending more data than that, you should mark it explicitly (by creating a publish/subscribe model), because there's a good chance that the data is being used on the wrong side of the wire. The attacker is allowed to do whatever evil they can accomplish in 8kb, maybe that means a 2k-deep nested series of lists, but whatever it is won't be too big. I feel that at some point you have to enforce a limit.. in web-amp, you must limit the total number of arguments they can send you, or the number of method calls per second, or something.

The non-DoS-related semantic typechecking (I'm expecting an int, is it really an int?) is just as easily done with assert()s inside the method body. I want this kind of checking to happen as close to the top of the method as possible.. doing it in a RemoteInterface in some separate file feels wrong to me. One approach is a func.guard method attribute (whose constructor takes arguments much like the RemoteInterface methods do), which could be pulled up to the top of the method body with a decorator. The big difference in thought here is the idea of providing objects (which happen to implement a certain set of methods) versus providing methods (which happen to be bound to a particular object).

A lot of the typechecking concerns are eased with finer-grained capabilities. Ideally, the worst they can do by sending you a weird object type is to cause an exception. As long as you haven't registered an Unslicer that gives the resulting object some ambient authority, you aren't going give them any new privileges by invoking a method on something they can give you. Tyler says you only do typechecking when you're considering granting them some new privileges. The notion is that it's the bound-method capability that is the basis of power, not what they do with it or what they send to it.

The constraints are useful for method documentation, especially if they can be serialized and passed to an object browser, but can only document the list of methods and the names/types of their arguments. The actual API description still needs to be in epydoc, which can provide (non-machine-parseable) argument name/type docs too.

positional parameters for interoperability with java:

java doesn't have keyword args. To provide interoperability, the python-newpb method call serializer needs to send args in strict order, the java newpb receiver would ignore the argument names (only using the values). In the other direction, the java method call serializer would send None for the argument names, and the python receiver would use the local RemoteInterface to turn the argument list into a kwargs dict.

Finally, I need to study the XML schemas in the web-calculus more closely. In it, the bound method closure URL can be used for two purposes: a GET returns the method schema (a description of what types the positional parameters will accept), while a POST will invoke the closure. However, the object which provided that URL has a class, and the method clause had a name, and the method schema is always the same for any given (class, methodname) pair, so even a fully send-time-checking implementation doesn't have to retrieve any method schema more than once. I had first thought that there was some reduncancy in the XML data being returned, but Tyler's put a lot of thought and time into it to minimize the round-trips and avoid redundancy. newpb would be well-served by studying his approach carefully.