Why do some people fall for phishing, scams and fake news while others don't? The Atlas maps what the published research shows so far: which human factors have been studied, how much evidence sits behind each, and what has been tried to help.
Every factor the research has examined, grouped into six categories: cognitive, psychological, behavioural, situational, demographic, and external (the message itself). The size of a bubble shows how many studies looked at that factor, and the ring shows which way their findings point. Switch between threats to see the evidence for each. What each study found is in the full Atlas. The map covers phishing and scams, and misinformation. A third area, manipulative design in apps and online shopping ("dark patterns"), has just been added with studies so far: too few to show separately yet.
What stands out when you read the rings. Study counts are live; the detail, the exceptions and the open questions are in the full Atlas.
Every kind of intervention tested in the research, from most to least studied. Each study counts once, by its best result. A long bar means well studied, not necessarily effective; read the colours. The full Atlas breaks this down by audience and threat, with what each study found.
A plain-English summary of the evidence on every factor, which way it points and how strong it is; a practitioner's playbook by audience and threat; filters for recent or high-quality research only; and the classical roots of each idea. This page is the public overview; the full Atlas is available by invitation while the research is being written up.
Researchers, security-awareness and trust-and-safety teams, journalists and policy people, and anyone trying to understand why people fall for things online.
A systematic review of the published research on susceptibility to phishing, scams and online manipulation, part of a PhD at Nelson Mandela University. Ongoing research, updated as studies are coded. Not professional advice.
Collard, A. (2026). The Susceptibility Atlas. Digital Mindfulness. Data as of .