Smartphones now run powerful on-device AI that learns from your behavior—and that means new risk. In this intermediate course, you’ll learn how AI turns phones into active attack surfaces and how adversaries weaponize deepfakes, side-channel inference, and mobile LLM agents. Through short, focused videos and scenario-based discussions, you’ll see exactly how zero-permission sensors and cache traces reveal activity, how overlays and prompt injection hijack agents, and why “permissions” alone don’t ensure privacy. Then you’ll turn knowledge into action: baseline telemetry, write simple detection rules, verify links and intents, quarantine devices, rotate tokens, and draft a one-page SOP. AI-graded labs provide hands-on practice, and a capstone project ties everything together. By the end, you can detect, respond, and harden against AI-driven mobile threats—skills you can apply immediately at home or in an enterprise.

Detect & Respond to Mobile AI Threats

Detect & Respond to Mobile AI Threats
This course is part of AI Security: Security in the Age of Artificial Intelligence Specialization


Instructors: Reza Moradinezhad
Included with
Recommended experience
What you'll learn
Analyze how AI features like sensors, models, and agents make phones attack surfaces and enable deepfake-based scams.
Evaluate technical attack paths—zero-permission inference and multi-layer agent attacks—using real research cases.
Design a mobile-focused detection and response plan with simple rules, containment steps, and key resilience controls.
Skills you'll gain
Tools you'll learn
Details to know

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December 2025
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