Skip to main content

API Throttling with OpenIG

A common requirement with regards to API access, is the ability to throttle the number of hits a user or service can have against a particular endpoint or set of endpoints - similar to a soft paywall style use case.

The nightly build of OpenIG contains a new filter - the ThrottlingFilter - which allows a simple way to limit and then time-out, a user who hits an endpoint x-number of times.

To test, I created a simple node.js API that allows the read (GET) and write (POST) of widgets.  Each widget has a numerical id that is used as the identifier.  I also created a basic queryAll route within my node.js API to do a wildcard-esque search to return all ids.

So now, I wanted to add OpenIG into the mix and do a little reverse-proxying.  I wanted to basically expose only the GET queries against my API, preventing POST requests entirely and only allowing GETs to specific endpoints.  To those endpoints I also wanted to limit the number of requests per user to 3 - if that threshold was hit I would redirect the user to a warning page and time them out for 10 seconds.

To set things up, I added a few things to my config.json main heap. Firstly, I used the defaultHandler attribute within my main router, to act as a catch all and handle all the requests that came in for which a specific route file was not defined.  I also added in the new ThrottlingFilter so I could use this from within any of my routes - as objects in the config.json main heap are visible to allow my lower level route handlers.  The ThrottlingFilter just looks like this:

I then setup a couple of static HTML files that I housed in a config/html folder in my OpenIG base directory. I had a noRouteResponse.html that my defaultHandler delivered via a StaticResponseHandler (note here, I also wanted to include an image in my HTML, so I included the image as a base64 encoded object, so I didn't have to worry about access to the image URL).  I also created a thresholdBreachedResponse.html, that I would redirect to, again via a StaticResponseHandler, when a user racked up 3 hits to my API.

In my config/routes directory I had two routes - one for a GET on an :id and another for a GET on the queryAll endpoint.  I added no explicit routes for POST requests, so they would be caught by my defaultHandler and redirected and thus preventing access.

The route for my throttling does a few things. Firstly, I added a conditional on what would trigger it - using the out of the box matches function, I added a basic regex for capturing requests that matched '/widget/[0-9][0-9]' - that is, only requests with digits as the :id - /widget/AA would fail for example.  The route passed all traffic that matched into a chain - which is just an ordered set of filters.  Here I could call my throttle filter and also a SwitchFilter.  The switch allowed me to check if a user had the threshold imposed by my throttle.  If the throttle was triggered, a 429 response code was hit back - if so, OpenIG would catch this and I would redirect to my thresholdBreachedResponse.html page.

At a high level, the set up looks like the following:

The redirect for the threshold breach in reality, may redirect to an identity provider like Facebook or OpenAM to log the user in, before allowing unlimited access that avoided the throttle filter entirely.

Code for the node.js API example is available here.

Artifacts for the OpenIG config are available here.


Popular posts from this blog

WebAuthn Authentication in AM 6.5

ForgeRock AccessManagement 6.5 , will have out of the box integration for the W3C WebAuthn . This modern “FIDO2” standard allows cryptographic passwordless authentication – integrating with a range of native authenticators, from USB keys to fingerprint and facial recognition systems found natively in many mobile and desktop operating systems. Why is this so cool? Well firstly we know passwords are insecure and deliver a poor user experience. But aren’t there loads of strong MFA solutions out there already? Well, there are, but many are proprietary, require complex integrations and SDK’s and ultimately, don’t provide the level of agility that many CISO’s and application designers now require.  Rolling out a secure authentication system today, will probably only result in further integration costs and headaches tomorrow, when the next “cool” login method emerges. Having a standards based approach, allows for easier inter-operability and a more agile platform for chan

Set Session Limits Using Context

Session limits typically cover 4 main items: total number of sessions a user can have at any one time, the max length of each session, the max idle time and max caching time. In an out of the box deployment in ForgeRock AM, these settings are configured via the session service.  However there are few tweaks than can be made to allow these settings to be run via a per user or per tree flow.  For example. think of the following scenario - user is logging via a device, location or network that has a higher risk rating.   Perhaps you would like to reduce session length on a BYOD device running an out of support version of Android to have a length of only 15 minutes.  If they switched back to their main trusted device, we can spin that back to 1hr. Another example, could be the spotting of a higher suspicion of bot activity for a particular user.  Maybe we need to set the entire quota limit to 1, to stop a bot spawning multiple sessions with the same credentials. This is all pretty trivial

Implementing Zero Trust & CARTA within AM 6.x

There is an increasing focus on perimeterless approaches to security design and the buzzy "defensive security architectures".  This blog will take a brief look at implementing a contextual and continuous approach to access management, that can help to fulfil those design aspirations. The main concept, is to basically collect some sort of contextual data at login time, and again at resource access time - and basically look for differences between the two.  But why is this remotely interesting?  Firstly, big walls, don't necessarily mean safer houses.  The classic firewall approach to security.  Keeping the bad out and the good in.  That concept no longer works for the large modern enterprise.  The good and bad are everywhere and access control decisions should really be based on data above and beyond that directly related to the user identity, with enforcement as close as possible to the protected resource as possible. With Intelligent AuthX, we can start to collect an