Skip to main content

Ghost Banning and Dynamic Personalisation

So that is a bit of a title.  What’s that all about then?  Login journey’s, especially from a consumer identity and access management (CIAM) or digital identity perspective have become must more complex.  Fine grained authentication has started to take over the linear biometric and MFA (multi-factor-authentication) approaches, where multiple pieces of non-identity contextual data is augmented to the original identity, through powerful choice and matrix flows.

This augmentation process, helps to deliver two really powerful use cases.

Dynamic Personalisation


So what is personalisation referring to, in the CIAM login landscape?  CIAM projects are focused on bringing service providers, who are delivering the latest “killer app” / API / product (delete as applicable) to market as quickly as possible, considerably closer to their  user community, through one-click social registration, single data views and friction free login.  The bi-directional benefits of CIAM, are to deliver better sign up and sign in services for end users – coupled with better data sharing and consent management – as well as fresher data, better analytics and increased trust from a service provider perspective.

The personalisation aspect, is referring to making the user login process responsive – which is going to include everything from user interface, theming and data presentation, right through to pro-active notifications and changes.

The new fine grained authentication in ForgeRock Access Management 5.5, allows all of the non-identity contextual data captured through default login interactions, to be simply made available to downstream protected API’s and applications, via assured session properties.  Those properties are time boxed and dynamic – changing with every interaction, giving the application the ability to dynamically respond to the presented user, even if the credentials

Fine Grained AuthN Trees in AM 5.5
The benefits are a very simple way to capture and release data to the calling application, all using simple REST endpoints that have been available for several years.

Ghost-Banning


So personalisation is a significant benefit to service and application owners, but about leveraging that data from a security perspective?

Well the same data can be used to perform several security related actions.

Increased Auditing


A simple action when presented with numerous different pieces of information, could be to trigger audit or information capture.  Simply using decision nodes within the fine grained authentication tree, basic if/else/switch style gates can be used to pump data to 3rd party tracking or SIEM solutions.

Triggers for Additional Steps


A simple response to the contextual data, that was also leveraged during the authentication chains approach, was to trigger an MFA event based on the previous steps. For example, if the credentials entered, event if correct, but were found to be coming from a previously unknown device - or perhaps via an untrusted device - thinking things like Chrome browser extension version vulnerabilities, or the NHS WannaCry attack on specific Microsoft OS’s – could trigger a step up authentication step or perhaps redirect to a cleansing network.

Contextual Data Via Session Properties

Redirection and Banning


A common “trick” often used on social networks, is the act of “ghost-banning”.  This process, allows users of a system – sometimes malicious, sometimes just in breach of certain terms of service – to be allowed into a system, but then given a minimal set of functionality, or perhaps redirected entirely to a functionally similar system, but on a separate “honey-pot” style network.  The reason?  To allow the service owner a fine grained way of tracking behaviour, improving system response and learning about malicious activity.

So the net-net?  We know that MFA and linear based approaches to authentication and login are not enough.  Not enough from a malicious activity perspective, but also not enough from a deep personalisation standpoint.  Fine grained authentication trees, where end user choice and greated administrative control and integration and delivering much more powerful login use cases in the CIAM space.

Comments

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

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

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