- Domain Overview and Weighting
- Domain 1: Evolution and Concepts of AI
- Domain 2: Developing GenAI & Training LLM Models
- Domain 3: LLM Usage within Applications
- Domain 4: LLM Vulnerabilities and Exploits
- Domain 5: AI Risk Management & ISO Standards
- Domain 6: Advanced Architectures, Agentic AI & Security
- Domain 7: Edge AI, Distributed Security & Future of GenAI
- Sequencing Your Study Around the Blueprint
- Who Hires CSPAI-Certified Professionals
- Frequently Asked Questions
- Domain 2 (GenAI development & LLM training) carries 29% of the blueprint - the single largest content area.
- Domain 6 (Advanced Architectures & Agentic AI) is second-largest at 18%, reflecting SISA's focus on emerging agentic protocols.
- The exam is 50 questions in 60 minutes, so domain weighting directly maps to how many questions you'll face on each topic.
- Domains 1, 3, and 5 are each 9-10% - foundational but lower-yield for last-minute review.
Domain Overview and Weighting
The Certified Security Professional in Artificial Intelligence (CSPAI) exam blueprint is built around seven domains, each representing a fixed percentage of the 50-question exam administered by Prometric on behalf of SISA. Because the exam is scored against a 70% passing threshold with no partial credit for reasoning shown, understanding exactly how many questions come from each domain is the difference between a targeted study plan and a scattershot one.
Unlike generic security certifications that spread weight evenly, the CSPAI blueprint is heavily skewed toward two domains: Concept behind Developing GenAI & Training of LLM Models (29%) and Advanced AI Model Architectures, Agentic AI Protocols & Security (18%). Together these account for nearly half of your exam. The remaining five domains fill out the rest, each contributing between 9% and 12%.
| Domain | Weight | Approx. Questions (of 50) |
|---|---|---|
| 1. Evolution and Concepts of AI | 10% | ~5 |
| 2. Developing GenAI & Training of LLM Models | 29% | ~14-15 |
| 3. LLM Usage within Applications | 10% | ~5 |
| 4. LLM Vulnerabilities and Exploits | 12% | ~6 |
| 5. AI Risk Management & ISO Standards for AI Cybersecurity | 9% | ~4-5 |
| 6. Advanced AI Model Architectures, Agentic AI Protocols & Security | 18% | ~9 |
| 7. Edge AI, Distributed Security & Future of GenAI | 12% | ~6 |
Domain 1: Evolution and Concepts of AI (10%)
This domain establishes the vocabulary and historical context examiners assume you already know before diving into GenAI specifics. It's foundational, not flashy, but questions here are often quick wins if you understand core distinctions rather than trying to memorize a timeline.
Evolution and Concepts of AI
Candidates must be able to distinguish between AI paradigms and explain how each generation of models changed security assumptions.
- Differences between symbolic AI, machine learning, deep learning, and generative AI
- Key milestones that shaped current AI security thinking (expert systems, neural networks, transformer architectures)
- Foundational terminology: supervised vs. unsupervised learning, narrow vs. general AI
- How AI evolution created new attack surfaces compared to traditional software
Because this domain is only 10% of the exam, treat it as a warm-up domain rather than a deep-dive area - enough to answer confidently, not enough to over-invest your limited study hours.
Domain 2: Concept behind Developing GenAI & Training of LLM Models (29%)
This is the domain that decides whether you pass. At 29% of the blueprint, it's larger than the next two domains combined, and SISA's exam questions here go deep into the mechanics of how large language models are actually built and trained - not just what they do.
Developing GenAI & Training of LLM Models
Candidates need practical, mechanism-level understanding of the GenAI development pipeline, not surface-level familiarity.
- Transformer architecture fundamentals: attention mechanisms, tokenization, embeddings
- Pretraining vs. fine-tuning vs. reinforcement learning from human feedback (RLHF)
- Data pipeline security: training data poisoning, data provenance, dataset curation risks
- Model alignment techniques and their security implications
- Compute and infrastructure considerations for training at scale
- How training choices introduce downstream vulnerabilities exploited later in a model's lifecycle
Key Takeaway
Allocate roughly a third of your total prep time to Domain 2 alone. If you're building a week-by-week plan, see the domain-by-domain breakdown in the CSPAI Study Guide 2026: How to Pass on Your First Attempt for how this domain should anchor your schedule.
Expect scenario-based questions that describe a training pipeline decision and ask you to identify the resulting security weakness - this domain rewards conceptual fluency over rote memorization.
Domain 3: LLM Usage within Applications (10%)
Once a model is trained, it gets deployed - and Domain 3 tests your understanding of that deployment layer. This is where prompt engineering, retrieval-augmented generation (RAG), and application-layer integration patterns live.
LLM Usage within Applications
This domain focuses on how LLMs are embedded into real products and the security implications of those integration choices.
- RAG architecture and how external data sources introduce risk
- API-level integration patterns and authentication considerations
- Prompt design, system prompts, and how instructions can be manipulated
- Output filtering and content moderation layers
Questions in this domain often present a short application scenario (a chatbot, a customer-service integration, an internal copilot) and ask you to spot the weak link in how the LLM is wired into the surrounding system.
Domain 4: LLM Vulnerabilities and Exploits (12%)
This is the domain most closely aligned with traditional offensive security thinking, translated into LLM-specific attack classes. Expect it to feel familiar if you have a background in application security, but with new terminology layered on top.
LLM Vulnerabilities and Exploits
Candidates must recognize and differentiate between the major categories of LLM-specific attacks.
- Prompt injection (direct and indirect) and jailbreaking techniques
- Model extraction and inversion attacks
- Data leakage through memorization and training data extraction
- Adversarial inputs and evasion techniques specific to generative models
- Supply chain risks in pretrained model reuse
Because this domain builds directly on Domain 2's training concepts, studying them back-to-back - rather than in blueprint order - often helps candidates retain the connections between how a model is built and how it's later exploited.
Domain 5: AI Risk Management & ISO Standards for Cybersecurity for AI (9%)
The smallest domain by weight, but not one to skip. This section tests governance and compliance knowledge - the kind of material that ties directly back to CSPAI's ANAB-accredited, ANSI/ISO/IEC 17024-aligned foundation.
AI Risk Management & ISO Standards
Expect questions on formal risk frameworks and how they apply specifically to AI systems rather than generic IT risk.
- AI-specific risk assessment methodologies
- Relevant ISO standards for AI cybersecurity and how they map to organizational controls
- Governance structures for AI model lifecycle management
- Documentation and audit requirements for AI risk programs
This domain rewards candidates who can connect regulatory language to practical controls rather than memorizing standard numbers in isolation.
Domain 6: Advanced AI Model Architectures, Agentic AI Protocols & Security (18%)
The second-largest domain and the one most likely to feel new even to experienced security professionals, since agentic AI is a rapidly evolving area. At 18%, it demands serious attention.
Advanced Architectures & Agentic AI
This domain covers multi-agent systems, autonomous decision-making frameworks, and the protocols that let AI agents act on behalf of users or systems.
- Agentic AI architectures: planning, tool-use, and memory components
- Multi-agent communication protocols and their attack surfaces
- Autonomous action risks - what happens when an agent executes without human review
- Security controls for agent-to-agent and agent-to-tool interactions
- Emerging architectures beyond standard transformer-based LLMs
Domain 7: Edge AI, Distributed Security & Future of GenAI (12%)
The final domain looks outward - beyond centralized cloud-trained models to distributed and edge deployments, plus forward-looking trends the exam expects certified professionals to anticipate.
Edge AI, Distributed Security & Future of GenAI
Candidates should understand how security assumptions change when AI moves off centralized infrastructure and onto distributed or resource-constrained devices.
- Edge deployment constraints: compute limits, model compression, quantization risks
- Distributed training security (federated learning considerations)
- Securing AI in IoT and embedded contexts
- Emerging trends in GenAI evolution and their security implications
This domain ties together the entire blueprint - you'll need Domain 2's training concepts and Domain 6's architecture knowledge to fully reason through edge and distributed scenarios.
Sequencing Your Study Around the Blueprint
Rather than studying domains in numerical order, many candidates get better retention by grouping related domains and front-loading the highest-weight material. A simple four-week structure built around blueprint weight looks like this:
Foundations + Heaviest Domain (Start)
- Domain 1: Evolution and Concepts of AI
- Begin Domain 2: transformer architecture and pretraining fundamentals
Finish Domain 2 + Move to Exploits
- Complete Domain 2: fine-tuning, RLHF, data pipeline risks
- Domain 4: LLM Vulnerabilities and Exploits (builds directly on Domain 2)
Applications + Second-Largest Domain
- Domain 3: LLM Usage within Applications
- Domain 6: Advanced Architectures & Agentic AI Protocols
Governance, Edge Topics & Full Review
- Domain 5: AI Risk Management & ISO Standards
- Domain 7: Edge AI, Distributed Security & Future of GenAI
- Full-blueprint timed practice runs
If you'd rather follow a more detailed day-by-day breakdown, the CSPAI Study Guide 2026: How to Pass on Your First Attempt expands this into a complete plan, and running timed sets through our practice test platform throughout each week helps confirm which domains still need reinforcement before you commit to a real exam date.
Who Hires CSPAI-Certified Professionals
Because the blueprint spans everything from LLM training mechanics to agentic AI security and edge deployment, the credential appeals to a fairly specific slice of the security field: professionals working at the intersection of AI/ML engineering and information security, rather than purely traditional network or application security roles.
Organizations building or securing GenAI products - including those training custom LLMs, deploying RAG-based applications, or building agentic systems - are the most natural fit for CSPAI-holders. Given that SISA co-developed the certification with CERT-In and maintains it under ANSI/ISO/IEC 17024, it also carries weight in regulated or compliance-heavy environments where formal, accredited AI security credentials matter during vendor or personnel vetting.
If you're evaluating whether the investment translates into career opportunity, the CSPAI Jobs overview and the CSPAI Salary Guide 2026: Complete Earnings Analysis go into more detail, and the broader Is the CSPAI Certification Worth It? Complete ROI Analysis 2026 article weighs the certification-only path ($250) against the training-plus-certification path ($1,000) described in SISA's fee structure.
Key Takeaway
Eligibility is met through two years of verifiable full-time information-security or AI/ML experience, the 16-hour CSPAI workshop, or equivalent blueprint-aligned training - check the CSPAI Requirements 2026: Eligibility, Prerequisites & How to Qualify guide before registering to confirm which path applies to you.
Frequently Asked Questions
Domain 2, Concept behind Developing GenAI & Training of LLM Models, carries 29% of the blueprint - the largest single domain, translating to roughly 14-15 of the 50 exam questions.
No. The blueprint is weighted unevenly, with Domains 2 and 6 together making up 47% of the exam. Studying proportionally to domain weight is more efficient than spending equal time on all seven.
The exam contains 50 questions with a 60-minute time limit, and a 70% score is required to pass, per SISA's published exam facts.
Domain 6, Advanced AI Model Architectures, Agentic AI Protocols & Security, reflects one of the more recently emphasized areas in the blueprint and carries significant weight at 18%, so it deserves focused review alongside Domain 2.
The CSPAI Passing Score 2026: Exactly What You Need to Pass and CSPAI Certification Cost 2026: Complete Pricing Breakdown articles cover the exact scoring threshold and SISA's fee structure, including the certification-only and training-plus-certification options.