Protect AI systems
Secure models, data and infrastructure from emerging threats and vulnerabilities.
AI Security Specialization
Secure the Future of AI
Master the cybersecurity skills you need to secure AI systems, LLM applications, AI agents and data pipelines. Learn to assess risks, prevent attacks and build trustworthy AI-powered solutions.
- Hands-on labs
- Real-world projects
- Expert instructors
- Job-ready skills
AI securityCore specialization
Hands-onLabs you build
PortfolioDocumented projects
ExpertIndustry instructors
CareerJob-ready skills
Why AI security matters
AI is powerful.
So are the risks.
From large language models and AI agents to RAG systems and autonomous tools, attackers are evolving fast. PrimeSec helps you stay ahead by building the skills to secure AI at every layer.
Learn more about AI securityPrevent attacks
Learn to stop prompt injection, jailbreaking, data poisoning and model abuse.
Ensure trust & safety
Build responsible, reliable and compliant AI systems and applications.
Advance your career
In-demand skills for AI security engineers, analysts and architects.
What you'll learn
AI security topics you'll master
LLM security
Understand LLM architecture, risks and secure deployment strategies.
Prompt injection
Prevent direct, indirect and multi-turn prompt injection attacks.
RAG security
Secure retrieval pipelines, knowledge bases and vector databases.
AI agent security
Secure autonomous agents, tools, memory and orchestration.
Data poisoning
Detect and prevent data poisoning in training and fine-tuning pipelines.
Model security
Protect models from theft, extraction, inversion and misuse.
AI governance
Implement policies, controls and responsible AI frameworks.
AI threat modeling
Model threats unique to AI systems and applications.
OWASP for LLM apps
Apply OWASP guidance for LLM applications to real projects.
MITRE ATLAS
Map and defend against adversarial tactics targeting AI systems.
Cloud AI security
Secure AI workloads on Azure, AWS and Google Cloud.
AI monitoring & IR
Monitor AI behaviour, detect anomalies and respond to AI incidents.
AI security learning paths
Choose your path
Beginner
AI Security Foundations
Start your journey and learn the essentials of AI security.
Intermediate
AI Security Engineer
Deepen your skills and secure AI systems and applications.
Advanced
AI Security Architect
Design secure AI solutions and architectures at scale.
Expert
AI Red Team Specialist
Test, break and secure AI systems like an elite red teamer.
AI security FAQ
Frequently asked questions
Everything you need to know about PrimeSec's AI security specialization.
What is AI security training at PrimeSec?
AI security at PrimeSec covers LLM and application security, prompt injection and jailbreaking, RAG and vector database security, AI agent and MCP security, model and supply-chain security, adversarial AI, AI threat modelling, cloud AI security, AI monitoring and incident response, and AI governance.
Do I need machine learning experience to start?
No. The specialization starts with AI and LLM fundamentals before moving into attack surfaces, defences and governance. Comfort with a cloud platform and basic scripting will help you move faster through the labs.
Which frameworks does the AI security content follow?
The content maps to widely used industry references including the OWASP guidance for LLM applications, MITRE ATLAS and the NIST AI Risk Management Framework, plus the AI security controls of Azure, AWS and Google Cloud.
What is prompt injection and how do I defend against it?
Prompt injection is an attack where malicious input manipulates an LLM into ignoring its instructions or revealing sensitive data. Defences include input validation, output filtering, system prompt isolation, least-privilege tool access and continuous monitoring of model behaviour.
How does PrimeSec teach RAG and vector database security?
PrimeSec labs guide you through securing retrieval-augmented generation pipelines: validating and sanitizing knowledge-base content, applying access controls to vector stores, preventing knowledge-base poisoning, and monitoring retrieval outputs for sensitive data leakage.
What is AI agent security and why does it matter?
AI agents can call tools, access data and take actions autonomously. Securing them means limiting excessive agency, validating tool inputs and outputs, sandboxing execution, protecting agent memory and monitoring for tool abuse or unintended actions.
Are the AI security labs hands-on?
Yes. PrimeSec labs are practical: you build and configure your own environments using your computer, containers or cloud accounts, following detailed lab guides. You document your work as portfolio evidence such as threat models, detection rules and remediation reports.
What career roles does AI security prepare me for?
The specialization builds skills for roles such as AI security engineer, AI threat analyst, responsible AI specialist, cloud AI security architect and AI red team specialist. You develop demonstrable evidence through labs and projects rather than passive video consumption.
Still have a question?
Ask our AI security instructors directly — we reply within 48 hours.
Free PDF
Download the AI Security syllabus
A four-page breakdown of everything covered in the AI Security specialization — modules, labs, learning paths and the portfolio evidence you finish with.
- 12 AI security domains with module-level detail
- Four learning paths from foundations to red team
- How PrimeSec labs and portfolio evidence work
Ready to secure the future of AI?
Tell us what you want to secure and we will send the AI security curriculum, lab list and next cohort dates.
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