SISA CSPAI : Certified Security Professional in Artificial Intelligence

  • Exam Code: CSPAI
  • Exam Name: Certified Security Professional in Artificial Intelligence
  • Updated: Oct 29, 2026
  • Q & A: 52 Questions and Answers

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SISA CSPAI Exam Syllabus Topics:

SectionObjectives
Topic 1: Evolution of Gen AI and Its Impact- Generative AI evolution
  • 1. Threat landscape transformation
  • 2. Impact of GenAI on cybersecurity
  • 3. AI and GenAI fundamentals
Topic 2: AI Governance and Ethical AI- Responsible AI implementation
  • 1. Ethical AI principles
  • 2. Regulatory compliance
  • 3. Trustworthy AI systems
Topic 3: Using Gen AI for Improving the Security Posture- AI-driven cybersecurity enhancement
  • 1. Security automation
  • 2. Threat detection and prediction
  • 3. Cyber resilience improvement
Topic 4: AIMS and Privacy Standards- Compliance and governance
  • 1. AI governance and privacy
  • 2. ISO 27563
  • 3. ISO 42001
Topic 5: Improving SDLC Efficiency Using Gen AI- Secure AI-assisted development lifecycle
  • 1. Vulnerability identification
  • 2. Secure software development practices
  • 3. AI-assisted code generation
Topic 6: Models for Assessing Gen AI Risk- AI risk management frameworks
  • 1. Risk assessment models
  • 2. Risk mitigation strategies
  • 3. Risk identification
Topic 7: Securing AI Models and Data- AI security controls
  • 1. Data poisoning
  • 2. Adversarial attacks
  • 3. AI data security
  • 4. Model theft protection

SISA CSPAI Exam: Frequently Asked Questions

SISA Certified Security Professional in Artificial Intelligence is an official SISA certification exam, identified by exam code CSPAI. Passing earns you the Cyber Security for AI certification, classified at the Professional level. It also connects with SISA AI Security Certifications, so it can serve as a stepping stone in a wider certification plan. In hiring, certificates work as a quick, quantitative standard, and this one tells employers your skills passed the vendor's own measurement.

Candidates must either possess at least 2 years of experience in Information Security or AI/ML-related roles, attend a 16-hour CSPAI workshop, or complete equivalent formal training covering the exam blueprint topics.

Because vendors adjust their policies, verify the current requirements before registering on the official exam page.

Yes. BraindumpsPrep provides a free PDF demo of the SISA Certified Security Professional in Artificial Intelligence questions, so you can evaluate the material before committing. After purchase, updates are free for 365 days, and when your product expires you can extend the update service at a 50% discount.

Your purchase is backed by a 100% money-back guarantee with transparent conditions. Take the SISA Certified Security Professional in Artificial Intelligence exam within 60 days of purchase; if you fail, you qualify for a full refund, provided the exam matches your product. Attempts within 3 days of purchase do not qualify, and neither do downloaded-but-unused products, free materials, or expired orders; the candidate name must match the payer name. File with a scanned enrollment slip and the official Score Report PDF within 2 days of the exam, and claims are processed within 7 days. You may instead choose an exchange: two other exam products of equal value, free, while your original purchase keeps its update service.

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The SISA Certified Security Professional in Artificial Intelligence syllabus is organized into 7 domains, with the largest being AIMS and Privacy Standards, AI Governance and Ethical AI, and Securing AI Models and Data. The complete breakdown appears in the topics section above; a clear classification of what the exam tests is the first step toward efficient preparation.

SISA Certified Security Professional in Artificial Intelligence Sample Questions:

Question #1

When deploying LLMs in production, what is a common strategy for parameter-efficient fine-tuning?

  • A. Implementing multiple independent models for each specific task instead of fine tuning a single model
  • B. Freezing the majority of model parameters and only updating a small subset relevant to the task
  • C. Training the model from scratch on the target task to achieve optimal performance.
  • D. Using external reinforcement learning to adjust the model's parameters dynamically.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #2

In the Retrieval-Augmented Generation (RAG) framework, which of the following is the most critical factor for improving factual consistency in generated outputs?

  • A. Utilising an ensemble of multiple LLMs to cross-check the generated outputs.
  • B. Tuning the retrieval model to prioritize documents with the highest semantic similarity
  • C. Fine-tuning the generative model with synthetic datasets generated from the retrieved documents
  • D. Implementing a redundancy check by comparing the outputs from different retrieval modules.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

In a machine translation system where context from both early and later words in a sentence is crucial, a team is considering moving from RNN-based models to Transformer models. How does the self-attention mechanism in Transformer architecture support this task?

  • A. By assigning a constant weight to each word, ensuring uniform translation output
  • B. By considering all words in a sentence equally and simultaneously, allowing the model to establish long-range dependencies.
  • C. By processing words in strict sequential order, which is essential for capturing meaning
  • D. By focusing only on the most recent word in the sentence to speed up translation
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

What is the main objective of ISO 42001 in AI management systems?

  • A. To focus solely on technical specifications for AI algorithms.
  • B. To provide guidelines only for small-scale AI projects.
  • C. To regulate hardware used in AI deployments.
  • D. To establish requirements for an AI management system within organizations.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #5

What aspect of privacy does ISO 27563 emphasize in AI data processing?

  • A. Maximizing data collection for better AI performance.
  • B. Consent management and data minimization principles.
  • C. Storing all data indefinitely for auditing.
  • D. Sharing data freely among AI systems.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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