Axiom Prime Certified DefenAI Professional
A 5-day, 100% hands-on certification that equips professionals to defend AI and LLM systems against adversarial attacks, data poisoning, model inversion, extraction and jailbreaks.
The frontline defence for AI systems under attack.
In today's digital age, AI has proliferated across healthcare, finance, transportation and e-commerce. With that adoption has come a sharp rise in AI-targeted attacks. Gartner estimates that by 2025, 50% of organizations will have suffered at least one AI-related security incident — ranging from data poisoning and model inversion to adversarial examples and model extraction.
The sophistication of AI-driven threats is escalating rapidly. An attacker can craft adversarial exploits to slip past AI-fortified defences, or deploy a model extraction attack to steal proprietary models. The consequences — financial loss, reputational damage, legal liability and erosion of public trust — are severe.
The Axiom Prime Certified DefenAI Professional course equips professionals with the knowledge and skills to identify and mitigate risks of AI exploitation and adversarial AI attacks — covering both the offensive techniques used to compromise AI systems and the defensive strategies to protect them.
What you'll learn
- Understand the concepts and techniques used to exploit AI modules — including adversarial attacks, data poisoning and model inversion — with permission from system owners.
- Identify potential vulnerabilities in AI-powered systems and develop strategies to prevent exploitation by malicious actors.
- Implement effective defence mechanisms to protect AI modules from attacks launched by other AI systems.
- Develop a comprehensive understanding of the AI security landscape — latest threats, trends and best practices in AI defence.
After certification you'll be able to
- Understand the different attacks on Large Language Models (LLMs), Deep Learning Models (DLMs), and Tree-Ensemble & Forecasting models.
- Master AI exploitation techniques: model inversion, adversarial examples, data poisoning and model extraction.
- Analyze risks and vulnerabilities in AI systems and design mitigation strategies.
- Design and implement defence mechanisms to protect AI modules from attacks by other AI modules.
Five days. Five domains. Zero theory-only sessions.
Introduction to AI and Machine Learning
- ›Overview of AI and Machine Learning Concepts
- ›Types of AI Models and Architectures
- ›AI Development Lifecycle and Workflows
- ›AI Ethics and Responsible AI Principles
Introduction to AI Security and Attack Vectors
- ›Overview of AI Security Landscape
- ›Common Attack Vectors on AI Models
- ›Threat Modelling for AI Systems
- ›AI Security Best Practices and Frameworks
Attacks on AI Models and Data Sources
- ›Attacks on Large Language Models (LLMs)
- ›Attacks on Deep Learning Models
- ›Attacks on Tree-Ensemble Models and Forecasting
- ›Data Poisoning and Manipulation Attacks
Attacks on AI Infrastructure, APIs, and Jailbreaking LLMs
- ›Reconnaissance and Vulnerability Scanning
- ›Exploiting Vulnerabilities in AI Infrastructure
- ›Attacks on AI APIs and Interfaces
- ›Jailbreaking LLMs and Diffusion Models
Advanced AI Attack Techniques and Defenses
- ›Membership Inference Attacks
- ›Model Inversion and Extraction Attacks
- ›Adversarial Defenses and Robustness
- ›Course Recap & Final Assessment
100% Hands-On Labs
CDAIP is a fully hands-on training with practical exercises designed to deep-dive into AI exploitation — exploring the techniques and tools used to compromise AI systems, alongside the strategies and best practices for protecting AI modules from adversarial attacks.
Certification Exam
- 2-hour hands-on practical exam
- 70% passing score
- ISO 17024 certified credential
- 5-day intensive program
Built for builders and defenders of AI.
Pre-requisites: Basic understanding of cybersecurity principles and AI concepts. Familiarity with machine-learning algorithms and Python is beneficial but not mandatory.
What past cohorts say about DefenAI.
"It was an eye-opener to understand common attack vectors on the AI development lifecycle and AI models. As an LLM developer, this course equipped me with the knowledge to build secure LLM and GenAI applications and protect models from adversarial attacks."
"DefenAI is training every AI architect and developer must attend. It's a journey through the AI security ecosystem with tons of hands-on across various attacks — including adversarial — with deep detail on defence. Highly recommended."
"DefenAI helped me understand AI threat models, attack methods on AI models, and the defenses needed to protect sensitive AI assets being built. Excellent hands-on labs and a fantastic trainer."
"The labs on adversarial perturbations and prompt-injection chains were brutal in the best way. We rebuilt our LLM gateway guardrails the week we got back to the office."
Ready to defend the next generation of AI systems?
Reserve your seat in the next CDAIP cohort, or talk to us about private on-site delivery for your team.