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CompTIA SecAI+ Certification
Artificial intelligence changes not just how systems learn and decide – it also opens up new attack vectors. Those who understand AI-driven security mechanisms can detect threats earlier and defend against them more effectively.
Key topics
- Applying ML methods to detect and counter threats
- Evaluating and classifying advanced attack patterns
- Building and embedding AI-driven security architectures
- Using data-driven methods to support security decisions
- Legal and regulatory frameworks for AI security
Prerequisite
Anyone already familiar with IT infrastructure, networks, and basic security concepts can get started right away.
Target group
This certification is for those who want to actively manage AI risks and take responsibility for intelligent security architectures – across industries and company sizes.
AI expertise in security is becoming a decisive advantage. Combining both disciplines enables faster action, better decisions, and more resilient digital systems.
Course Content
AI and Data Concepts for Cybersecurity
- Core AI concepts and key types of AI
- Generative AI: how it works and transformer architectures
- Machine learning and neural networks at a glance
- Natural language processing: fundamentals and use cases
- Training methods for AI models and their variants
- Prompt engineering: principles and applications
- Security-relevant properties and vulnerabilities of models
- Data types in AI systems and data protection methods
- Retrieval-Augmented Generation (RAG): concept and application
- Ensuring integrity and control in data processing
Threat Modeling for AI Systems
- Introduction to threat modeling for AI
- Procedures and conditions for effective threat modeling
- Methodical frameworks for AI threat analysis
- Categories and types of AI security measures
- Security boundaries in models and prompt template use
- Controls at gateways and system interfaces
- Access restrictions and usage limits for AI systems
- Validating and verifying implemented security controls
Access and Permission Controls for AI
- Principles and architecture models of AI access management
- Permission management for models and AI agents
- Securing API access and network communication
- Protecting sensitive AI training data
- Encryption techniques and data protection strategies
- Monitoring and logging in AI environments
- Cost and performance control in AI deployments
- Audit processes and compliance monitoring for AI systems
Detecting and Countering AI Attacks
- Security requirements throughout the full AI lifecycle
- Ethical principles in the development of AI systems
- Classification and methods of current AI attacks
- Backdoor and trojan attacks on AI models
- Poisoning attacks and inversion attacks on models
- Extraction and theft of model knowledge
- Defence strategies and technical countermeasures
- Forensic AI analysis following security-relevant incidents
AI Applications in Security Operations
- Tools and platforms for AI-powered security operations
- AI for threat detection and forensic analysis
- Automated vulnerability detection using AI methods
- Attack vectors that exploit AI technologies
- AI-based social engineering techniques and deception attacks
- Using AI for reconnaissance and intelligence gathering
- Automation scenarios using AI in security environments
- Integrating AI methods into DevSecOps processes
- Code generation and summarisation with AI support
Governance, Risk Management, and Compliance for AI
- Structures and responsibilities in AI governance
- Roles and responsibilities in AI-driven organisations
- Principles and requirements for responsible AI development
- Risk identification and assessment in AI projects
- Legal and regulatory requirements for AI
- Frameworks and standards for AI compliance
- Developing and implementing organisational AI policies
- Reporting and documentation for AI compliance
Up to 100% funding for your continuing education
Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.
Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.
What specific professional benefits does this certification offer?
- Demonstrating AI security expertise positions you for specialised roles and increases your visibility in security teams and AI-focused projects.
Why is the importance of AI security growing continuously?
- AI-powered attack methods are growing rapidly. Professionals who can assess these risks are immediately valuable to organisations.
Which topic areas define the training?
- The focus is on AI-based threat detection, securing models, and dealing correctly with emerging attack techniques.
Who benefits most from this certification?
- Particularly suited to professionals in IT security and systems analysis, as well as anyone looking to advance specifically into AI security roles.
What happens when AI security expertise is missing?
- Without solid AI security knowledge, attacks on models often go undetected. The risk posed by data manipulation and security gaps in AI systems increases significantly.
What sets this certification apart from other security certificates?
- The combination of traditional IT security and a specific AI focus makes this certification unique – in a field where demand is growing strongly.
How quickly can the knowledge be put into practice?
- The content can be applied immediately in practice – particularly for the analysis, protection, and quality assessment of AI systems.
