Failure rates in phishing simulations range from 1.8% to 30.8% depending on the lure. So what does a repeat-clicker list measure, and what can you do with it?
Failure rates in phishing simulations range from 1.8% to 30.8% depending on the lure. So what does a repeat-clicker list measure, and what can you do with it?
Self-efficacy predicts secure behavior better than knowledge does, and no awareness dashboard tracks it. What the evidence says and what a program can decide.
Automation bias shows up when an AI layer rules on an email before the person does. What the evidence shows and which programme decisions change.
A habit fires on a context cue rather than on the intention of the moment. Which behaviours can become habits, and when it pays to intervene.
Normalization of deviance explains why an unsafe practice becomes the team’s norm, and why punishing the case leaves that norm untouched.
Deepfake detection by eye performs at chance, and warning people about them erodes trust in real evidence. What to fix in your awareness program.
Knowing what phishing is doesn’t stop you from falling for it. Cyberpsychology explains why we decide on autopilot and how to trigger reflection before the click.