Skip to main content

Enhancing User Privacy with OpenID Connect Pairwise Identifiers

This is a quick post to describe how to set up Pairwise subject hashing, when issuing OpenID Connect id_tokens that require the users sub= claim to be pseudonymous.  The main use case for this approach, is to prevent clients or resource servers, from being able to track user activity and correlate the same subject's activity across different applications.

OpenID Connect basically provides two subject identifier types: public or pairwise.  With public, the sub= claim is simply the user id or equivalent for the user.  This creates a flow something like the below:

Typical "public" subject identifier OIDC flow

This is just a typical authorization_code flow - end result is the id_token payload.  The sub= claim is simply clear and readable.  This allows the possibility of correlating all of sub=jdoe activity.

So, what if you want a bit more privacy within your ecosystem?  Well here comes the Pairwise Subject Identifier type.  This allows each client to be basically issued with a non-reversible hash of the sub= claim, preventing correlation.

To configure in ForgeRock Access Management, alter the OIDC provider settings.  On the advanced tab, simply add pairwise as a subject type.

Enabling Pairwise on the provider

Next alter the salt for the hash, also on the provider settings advanced tab.

Add a salt for the hash
Each client profile, then needs either a request_uri setting or a sector_identifier_uri.  Basically akin to the redirect_uri whitelist.  This is just a mechanism to identify client requests.  On the client profile, add in the necessary sector identifier and change the subject identifier to be "pairwise".  This is on the client profile Advanced tab.

Client profile settings
Once done, just slightly alter the incoming authorization_code generation request to looking something like this:

/openam/oauth2/authorize?response_type=code
&save_consent=0
&decision=Allow
&scope=openid
&client_id=OIDCClient
&redirect_uri=http://app.example.com:8080
&sector_identifier_uri=http://app.example.com:8080

Note the addition of the sector_identifier_uri parameter.  Once you've exchanged the authorization_code for an access_token, take a peak inside the associated id_token.  This now contains an opaque sub= claim:

{
  "at_hash": "numADlVL3JIuH2Za4X-G6Q",
  "sub": "lj9/l6hzaqtrO2BwjYvu3NLXKHq46SdorqSgHAUaVws=",
  "auditTrackingId": "f8ca531a-61dd-4372-aece-96d0cea21c21-152094",
  "iss": "http://openam.example.com:8080/openam/oauth2",
  "tokenName": "id_token",
  "aud": "OIDCClient",
  "c_hash": "Pr1RhcSUUDTZUGdOTLsTUQ",
  "org.forgerock.openidconnect.ops": "SJNTKWStNsCH4Zci8nW-CHk69ro",
  "azp": "OIDCClient",
  "auth_time": 1517485644000,
  "realm": "/",
  "exp": 1517489256,
  "tokenType": "JWTToken",
  "iat": 1517485656

}


The overall flow would now look something like this:


OIDC flow with Pairwise

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