Mobile Fraud Vector Explorer: Every Attack Pattern
Analysis of top vectors exploited by fraudsters in FY 25-26. Explore pathways used to compromise systems, exploit vulnerabilities, and cause impact.
Landscape Overview
This section provides a high-level summary of the failure vectors distributed across different system domains based on FY 25-26 intelligence.
Vectors by Category (FY 25-26)
Severity Distribution (Top Exploits)
Vector Explorer
Filter the top failure vectors by category, the underlying vulnerability they exploit, or their ultimate impact. High severity vectors are highlighted in red.
How to use the fraud vector explorer
Each vector in the explorer is a way fraudsters attack a mobile app or the customer using it. Pick a category to see how the attack works, the signals that give it away and the NonaShield layer that responds.
Use it as a checklist when you review your own app. For each vector ask three questions: can the attacker reach it on our app, would we see it, and what would we do before money moves?
Vectors are grouped by where they happen. Runtime attacks such as hooking, overlays and tampering are caught by mobile RASP. Identity attacks such as cloned apps, emulators and stolen sessions are caught by device fingerprinting and hardware-bound identity. Session attacks such as remote access and coached payments are caught by behaviour and risk scoring.
For worked examples see the real 2026 fraud stories and the mobile banking fraud detection guide.
Frequently asked questions
What is the Fraud Vector Explorer?
An interactive view of mobile attack patterns by category, showing how each pattern works and which NonaShield layer detects it.
Which attacks does it cover?
Runtime tampering, overlays, remote access, emulators and cloned apps, SIM swap, account takeover, mule accounts and signal injection, among others.
Is the explorer a complete list of fraud?
No. It covers the patterns we track. New techniques are added as they appear.