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AI Security Training

Learn to assess and secure AI applications

Practical, instructor-led training in LLM security, prompt injection, RAG security, and AI application security — built for people who need to test and defend real AI systems, not just read about them.

Why It Matters

AI applications introduce security challenges traditional testing misses

A factual look at what changes when the application under test is powered by an LLM.

A new, less understood attack surface

LLM-powered applications accept natural-language input as a control channel, which traditional input validation isn't designed to handle.

Vulnerability classes without a mature playbook

Prompt injection, insecure output handling, and excessive agency don't map cleanly onto existing web security frameworks.

Higher stakes when AI is connected to real systems

AI applications increasingly call tools, query internal data, and take actions — so a security failure can have consequences beyond the chat window.

Training Topics

What the training covers

LLM Security

New

Security fundamentals for large language model deployments.

AI Application Security

New

Securing applications built on top of AI/LLM services.

Prompt Injection

New

Understanding and defending against prompt injection attacks.

RAG Security

New

Securing retrieval-augmented generation pipelines.

AI Threat Modeling

New

Structured threat modeling approaches for AI systems.

AI Security Testing

New

Practical testing methodology for AI system security.

Sensitive Information Disclosure

New

Preventing AI systems from leaking sensitive data through their outputs.

Insecure Output Handling

New

Safely handling and validating AI-generated output before it's trusted downstream.

AI/LLM Vulnerability Assessment

New

Systematic vulnerability assessment for AI and LLM-powered systems.

Agent and Tool Security

New

Security fundamentals for AI agents and their tool integrations.

How We Teach

Practical, hands-on security testing

The training is built around doing the work in authorized lab environments, not just discussing it.

Understanding the attack surface
Testing AI applications
Analyzing requests & responses
Identifying vulnerabilities
Exploitation in authorized labs
Root-cause analysis
Remediation
Security testing methodology

Curriculum

Curriculum & modules

The detailed module-by-module curriculum for AI Security Training is being finalized alongside the topics above. Rather than publish placeholder modules, we'll share the current syllabus directly — contact us for the latest curriculum and scheduling.

Who It's For

Built for people who test and build AI systems

Generally suited to, though not limited to:

Application Security professionals
Penetration testers
Security engineers
Developers building on LLMs
Security researchers

Training Format

Live, instructor-led sessions

This is delivered as live, instructor-led training with hands-on labs — not a self-paced video course.

Ready to secure what you're building with AI?

Explore the curriculum above or reach out to discuss scheduling AI Security Training for your team.