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- Security
Securing AI Applications
1 Course
2 Hours
Skill IQ
Master the security lifecycle of modern AI applications by learning to threat model complex architectures, execute sophisticated prompt and RAG exploits, and implement robust, multi-layered defenses for autonomous agents.
Content in this path
Securing AI Applications
Learn to secure AI applications end to end; threat model LLM, RAG, and agent architectures, execute prompt injection and tool-use attacks, and build layered runtime defenses.
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What You'll Learn
- Analyze AI application architectures to map attack surfaces, trust boundaries, and data flows, and build a prioritized test plan.
- Execute prompt injection, RAG manipulation, and agent tool-use attacks against AI-enabled systems.
- Launch abuse and operational attacks — denial-of-wallet, cost amplification, and tool-loop degradation — and report infrastructure risk.
- Build a repeatable AI security test harness with regression testing for model and prompt drift, and produce decision-grade reporting.
- Design layered defenses for AI apps, hardening RAG and tool-use interfaces and establishing a continuous security assurance loop.
Prerequisites
- A mid-level understanding of application and API security and cloud-native architectures. Familiarity with how LLM, RAG, and agent-based applications work is helpful but not required.
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