Testing predictors

To test predictors, you can simulate risk events with a sample application in PingOne.

Before you begin

You’ll need a PingOne account and an environment with the PingOne Protect service. You can use an existing account or start a PingOne trial. For more information, see Starting a PingOne trial and Adding the PingOne Protect service to your environment.
You can optionally use a sample app to test the risk predictors. To learn how to configure an environment with a sample app, see Trying PingOne Protect with a sample app.

About this task

Simulations allow you to deepen your understanding of how PingOne Protect detects different types of risk events. For more information on predictors, see Introduction to predictors and Predictors.

Steps

To test common predictors:

Predictor	Testing Steps
Geovelocity anomaly	Sign on to your account. Sign on again with a Remote Desktop Protocol (RDP) in a server from a remote datacenter. You can alternatively have a colleague based in a different location sign on to the sample app with the same user.
New device	Sign on from one device. Sign on again from another device.
Anonymous network detection	Use a public VPN/server or browser extension that hides your IP address. Sign on.
User-based risk behavior	Train the predictor by creating risk evaluations (such as signing on with the same user account several times and authenticating successfully each time). Create a new risk evaluation (such as signing on again from a different browser or a different operating system if possible).

Predictor

Testing Steps

Geovelocity anomaly

Sign on to your account.
Sign on again with a Remote Desktop Protocol (RDP) in a server from a remote datacenter. You can alternatively have a colleague based in a different location sign on to the sample app with the same user.

New device

Sign on from one device.
Sign on again from another device.

Anonymous network detection

Use a public VPN/server or browser extension that hides your IP address.
Sign on.

User-based risk behavior

Train the predictor by creating risk evaluations (such as signing on with the same user account several times and authenticating successfully each time).
Create a new risk evaluation (such as signing on again from a different browser or a different operating system if possible).