Prompt Injection Defense Platform for Securing AI-Integrated Mobile Applications

One of the most effective ways to avoid prompt injections is to implement a dedicated LLM runtime firewall that validates and sanitizes all inputs before they reach your AI model. Protectt.ai's Runtime Protection layer continuously monitors every prompt in real time, intercepting adversarial inputs that attempt to override system instructions, exfiltrate data, or manipulate model behavior—without adding any performance overhead to your mobile application.

Prompt injection is an attack where a malicious actor crafts inputs designed to hijack an AI model's instructions, causing it to ignore safety guidelines, leak sensitive data, or execute unintended actions. In AI-integrated mobile applications—especially in banking, fintech, and insurance—this can lead to unauthorized transactions, data breaches, or complete bypass of security controls, making robust defense essential.

Protectt.ai deploys an intelligent LLM Runtime Security firewall that uses AI/ML-driven behavioral analysis to inspect every prompt and model interaction at runtime. It identifies anomalous input patterns, jailbreak attempts, and adversarial injections in milliseconds—blocking threats before they influence model outputs. The system continuously learns from new attack techniques, ensuring adaptive protection as threat vectors evolve.

AI Red Teaming involves automated adversarial simulations that mimic real-world prompt injection, jailbreaking, and model manipulation attacks against your AI-integrated mobile application. Protectt.ai's Red Teaming service systematically uncovers exploitable weaknesses in your AI logic, prompt handling, and model boundaries before malicious actors can exploit them—delivering actionable remediation insights and hardening your application's AI defenses proactively.

The ML Model Scanner applies zero-trust verification to every AI model and dependency within your mobile app's supply chain. It detects tampered model weights, poisoned training datasets, unauthorized model substitutions, and compromised AI components introduced during development or third-party integration. This ensures that only verified, integrity-confirmed models are deployed in production—eliminating a critical and often overlooked attack surface in AI-integrated applications.

Yes. Protectt.ai holds ISO 42001 certification—the international standard for AI management systems—alongside PCI DSS, ISO 27001, and ISO 22301 certifications. The platform's automated compliance monitoring and reporting capabilities reduce manual audit preparation time by up to 90%, helping enterprises meet AI governance requirements, data privacy regulations, and sector-specific mandates without adding significant operational burden to security teams.

Protectt.ai's security capabilities are delivered as a lightweight, easy-to-integrate SDK for both Android and iOS platforms. The SDK plugs into your existing mobile app development workflow with minimal engineering effort, requires no architectural overhaul, and introduces zero performance overhead for end users. It supports rapid deployment across Java, Kotlin, Swift, Objective-C, React Native, and Ionic codebases, enabling enterprises to achieve security without sacrificing development velocity.

Any enterprise deploying AI-integrated mobile applications benefits from prompt injection defense, but the risk is especially acute in Banking, Insurance, FinTech, NBFCs, Stock Trading, and Government sectors—where AI models handle sensitive financial data, authentication decisions, and transaction approvals. Protectt.ai currently secures AI-integrated applications for major institutions including RBL Bank, Yes Bank, Bajaj Finserv, BSE, ICICI Lombard, LIC, and dozens more globally.