The digital economy today runs on mobile applications. Banks are opening accounts on Mobile apps before branches, fintechs are redefining payments with a tap, and healthcare services are delivered over mobile screens. For businesses, Mobile apps are no longer just an extension of their services—they are the primary gateway to customer trust, engagement, and revenue.
CEO & Founder
Protectt.ai
But as enterprises leaned on mobile apps to accelerate digital transformation, cybercriminals found new ways to exploit them. Powered by automation and even adversarial use of AI, threats have shifted from broad, opportunistic attacks to surgical fraud campaigns. From runtime tampering and overlay malware to API abuse and device spoofing, attackers now deploy AI-driven tools to mimic user behavior, bypass controls, and scale fraud at speeds previously unseen.
This evolving threat landscape exposes a paradox: while businesses adopt AI to defend mobile apps, attackers are also weaponizing AI to break them. This duality raises an urgent question—how do we rebuild trust in cybersecurity AI so that enterprises can rely on it as a true guardian, not just another buzzword?
Why Traditional Security Falls Short
Most traditional security tools were built for detecting anomalies at the network or endpoint level. But mobile apps demand something more contextual:
• They must remain secure inside the hostile environment of a user’s device.
• They must react in real time, without waiting for a cloud-based verdict.
• They must protect against zero-day exploits, polymorphic malware, and fraud bots that adapt faster than static defenses.
Traditional security often lacks transparency, overburdens devices, and sometimes misjudges actions—leading to mistrust.
RASP: Proactive Defense, Rebuilt on Trust
The answer lies in Runtime Application Self-Protection (RASP), built to operate at the core of mobile apps. Unlike external defenses, RASP embeds security within the mobile app itself, enabling it to:
• Continuously monitor runtime behavior to detect tampering, reverse engineering, or injection attacks as they happen.
• Separate genuine users from fraudsters deploying emulators, spoofing tools, or automated attack scripts.
• Block threats proactively before they can compromise data, transactions, or user sessions—ensuring fraud prevention happens in real time.
• Provide explainable telemetry, giving enterprises clarity on what was stopped, why, and how.
This makes RASP not just a proactive shield but a trust-building mechanism: safeguarding users while assuring businesses that protection is working transparently and efficiently.
Securing the Digital Economy’s Trust Pillar
For a digital economy to thrive, trust in mobile apps is non-negotiable. Regulatory bodies across the world are echoing this sentiment, mandating stronger in-app protections for financial services and critical industries. Enterprises that adopt proactive RASP-driven defenses not only comply with these frameworks but also strengthen customer loyalty by ensuring their digital journeys remain seamless and secure.
Mobile apps are the currency of today’s digital economy. But as attackers harness AI to fuel more sophisticated fraud, businesses must respond with equally intelligent, proactive, and transparent defenses. RASP represents this new generation of cybersecurity AI—smarter, lighter, and focused on real-time protection.
Rebuilding trust in cybersecurity AI starts here: at the runtime layer, where mobile apps and user trust intersect.
-Authored by Manish Mimani, CEO & Founder, Protectt.ai
