Revolutionizing Cybersecurity in the Age of Artificial Intelligence

Launch Date: February 17, 2026 | Exam Code: CY0-001

The cybersecurity landscape is undergoing its most significant transformation in decades, driven by the explosive growth of artificial intelligence. Recognizing this seismic shift, CompTIA has announced SecAI+ (CY0-001), the world’s first certification specifically designed to validate skills in securing AI systems, leveraging AI for security operations, and navigating the complex governance landscape surrounding AI technologies.

This groundbreaking credential represents CompTIA’s inaugural entry into their new “Expansion Series” of certifications—specialized credentials that address emerging technologies reshaping the IT security field. For cybersecurity professionals looking to future-proof their careers, SecAI+ offers a critical competitive advantage in an AI-driven world.

Why SecAI+ Matters Now

The AI Security Skills Gap

The numbers tell a compelling story:

• By 2026, 90% of organizations will have adopted AI technologies in some capacity
• 73% of security leaders report they lack personnel with AI security expertise
• AI-powered attacks are growing at 300% year-over-year
• Regulatory frameworks like the EU AI Act are creating urgent compliance requirements

Traditional cybersecurity training hasn’t kept pace with AI’s rapid evolution. Security professionals who understand firewalls, intrusion detection, and vulnerability management now face an entirely new challenge: securing AI systems themselves while leveraging AI to enhance security operations.

SecAI+ bridges this critical gap.

The Dual Challenge: Securing AI and Using AI Securely

SecAI+ addresses both sides of the AI security equation:

1. Defensive AI Security

• Protecting AI models from adversarial attacks
• Securing training data and inference pipelines
• Preventing model theft, poisoning, and manipulation
• Implementing guardrails and access controls

2. Offensive AI Capabilities

• Leveraging AI for threat detection and hunting
• Automating security workflows and incident response
• Using AI to analyze massive log volumes and detect anomalies
• Integrating AI into SOC operations

This dual focus makes SecAI+ uniquely valuable: you’ll learn to both defend AI systems and harness AI’s power to strengthen your organization’s security posture.

SecAI+ at a Glance

Certification Details

Attribute	Details
Exam Code	CY0-001 V1
Launch Date	February 17, 2026
Pre-Order	Available Now
Question Format	Multiple-choice and performance-based
Languages	English (at launch)
Certification Duration	3 years from date earned
Prerequisites	None (recommended: Security+, CySA+, or equivalent)
Recommended Experience	3-4 years IT experience, 2+ years hands-on cybersecurity
Estimated Retirement	2029 (typical 3-year cycle)

Target Audience

SecAI+ is ideal for:

• Security Analysts integrating AI tools into SOC operations
• Security Engineers building AI-powered security solutions
• AI/ML Engineers with security responsibilities
• Compliance Officers navigating AI regulatory frameworks
• Security Architects designing AI-enabled security infrastructure
• Penetration Testers defending against AI-driven attacks
• Risk Analysts assessing AI-related security risks

The Four Domains: Deep Dive

SecAI+ consists of four comprehensive domains that together create a holistic understanding of AI security.

Domain 1: Basic AI Concepts Related to Cybersecurity (17%)

This foundational domain ensures candidates understand the AI technologies they’ll be securing and leveraging.

Key Topics Include:

1.1 AI Types and Techniques

• Generative AI: Understanding LLMs, SLMs, and GANs
• Machine Learning: Supervised, unsupervised, and reinforcement learning
• Deep Learning and Transformers: Neural networks and attention mechanisms
• Natural Language Processing: How AI understands and generates human language

1.2 Data Security in AI

• Data Processing: Cleansing, verification, lineage, and provenance
• Retrieval-Augmented Generation (RAG): Vector storage and embeddings
• Watermarking: Protecting AI-generated content
• Data Types: Structured, semi-structured, and unstructured data handling

1.3 AI Lifecycle Security

• Business Use Cases: Aligning AI projects with organizational objectives
• Data Collection: Ensuring trustworthiness and authenticity
• Model Development and Evaluation: Security throughout the ML pipeline
• Human-Centric AI: Human-in-the-loop, oversight, and validation principles

Why This Matters: You can’t secure what you don’t understand. This domain provides the technical foundation necessary to implement meaningful security controls around AI systems.

Domain 2: Securing AI Systems (40%)

The largest domain reflects the critical importance of protecting AI infrastructure, data, and models from sophisticated attacks.

Key Topics Include:

2.1 AI Threat Modeling

• OWASP LLM Top 10: The definitive list of large language model vulnerabilities
• OWASP ML Security Top 10: Machine learning-specific attack vectors
• MITRE ATLAS: Adversarial Threat Landscape for AI Systems framework
• MIT AI Risk Repository: Comprehensive AI risk taxonomy
• CVE AI Working Group: Tracking AI-specific vulnerabilities

2.2 Security Controls for AI Systems

• Model Controls: Model evaluation and guardrails
• Gateway Controls: Prompt firewalls, rate limits, token limits, and input quotas
• Guardrail Testing: Validation methodologies for AI safety controls

2.3 Access Controls

• Model Access: Controlling who can interact with AI models
• Data Access: Protecting training and inference data
• Agent Access: Managing autonomous AI agent permissions
• API Access: Securing network endpoints for AI services

2.4 Data Security Controls

• Encryption: In transit, at rest, and in use (homomorphic encryption)
• Data Safety: Anonymization, masking, redaction, minimization
• Classification Labels: Proper data categorization for AI workloads

2.5 Monitoring and Auditing

• Prompt Monitoring: Query and response analysis
• Log Protection: Sanitization and security of AI system logs
• AI Cost Monitoring: Tracking prompts, storage, responses, and processing costs
• Quality Auditing: Hallucinations, accuracy, bias and fairness assessments

2.6 Analyzing AI Attacks

• Prompt Injection: Manipulating AI responses through crafted inputs
• Poisoning Attacks: Corrupting training data or models
• Jailbreaking: Bypassing AI safety controls
• Model Theft: Extracting proprietary models through inference
• Membership Inference: Determining if specific data was in training sets
• Supply Chain Attacks: Compromising AI development pipelines

Real-World Relevance: These aren’t theoretical concerns. Prompt injection attacks have compromised production systems, data poisoning has corrupted models, and AI supply chain vulnerabilities have led to breaches. SecAI+ ensures you can defend against these emerging threats.

Domain 3: AI-Assisted Security (24%)

This domain focuses on using AI to enhance security operations—automating workflows, accelerating threat detection, and scaling incident response.

Key Topics Include:

3.1 AI-Enabled Security Tools

• IDE Plug-ins: AI-assisted secure coding
• Browser and CLI Plug-ins: Enhanced security workflows
• Chatbots and Personal Assistants: AI-powered security guidance
• Use Cases: Signature matching, vulnerability analysis, automated pentesting, anomaly detection, pattern recognition, incident management, threat modeling, fraud detection

3.2 AI-Enhanced Attack Vectors

• Deepfakes: AI-generated impersonation and disinformation
• Adversarial Networks: Using AI to discover vulnerabilities
• Automated Data Correlation: AI-assisted reconnaissance
• Automated Attack Generation: AI-created payloads, malware, and DDoS attacks

3.3 Automating Security Tasks

• Low-Code/No-Code Tools: Accessible AI automation
• Document Synthesis: Automated security documentation
• Incident Response: AI-assisted ticket management
• CI/CD Integration: Code scanning, software composition analysis, automated testing

Practical Impact: Imagine reducing alert triage time by 80%, automatically correlating threats across millions of log entries, or generating incident reports in seconds instead of hours. This domain teaches you to harness AI’s power for these transformational use cases.

Domain 4: AI Governance, Risk, and Compliance (19%)

As governments worldwide implement AI regulations, understanding compliance requirements has become mission-critical.

Key Topics Include:

4.1 Organizational Governance

• AI Center of Excellence: Structuring AI governance teams
• AI Policies and Procedures: Corporate AI governance frameworks
• AI-Related Roles: Data scientists, AI architects, MLOps engineers, AI security architects, AI governance engineers, AI risk analysts

4.2 AI Risks

• Responsible AI Principles: Fairness, reliability, transparency, privacy, explainability, inclusiveness, accountability, consistency
• Risk Categories: Bias introduction, data leakage, reputational loss, IP concerns, autonomous system risks

4.3 Compliance Frameworks

• EU AI Act: Europe’s comprehensive AI regulation (world’s first)
• OECD AI Standards: International AI governance principles
• ISO AI Standards: Technical standards for AI systems
• NIST AI RMF: U.S. AI Risk Management Framework
• Corporate Policies: Sanctioned vs. unsanctioned AI, private vs. public models, sensitive data governance

Global Importance: The EU AI Act alone affects any organization doing business in Europe. Non-compliance can result in fines up to €35 million or 7% of global annual turnover—whichever is higher. SecAI+ ensures you understand these regulatory landscapes.

What Makes SecAI+ Different?

1. First-to-Market Advantage

SecAI+ is the world’s first AI security certification. There’s no competing credential that addresses this space comprehensively. Early adopters will have a significant competitive advantage as demand for these skills explodes.

2. Vendor-Neutral Approach

Unlike vendor-specific AI certifications, SecAI+ provides platform-agnostic knowledge applicable across:

• AWS AI services
• Azure AI and OpenAI integrations
• Google Cloud AI Platform
• Open-source frameworks (TensorFlow, PyTorch, Hugging Face)
• Enterprise AI platforms (Databricks, Snowflake, etc.)

3. Practical, Hands-On Focus

The exam includes performance-based questions requiring candidates to:

• Configure AI security controls
• Analyze attack evidence
• Implement monitoring solutions
• Apply governance frameworks to real scenarios

4. Aligned with Industry Frameworks

SecAI+ maps directly to critical AI security resources:

• OWASP AI Security projects
• MITRE ATLAS framework
• NIST AI Risk Management Framework
• EU AI Act requirements
• ISO AI standards

Career Impact and Salary Potential

Job Roles Aligned with SecAI+

The certification prepares you for emerging high-demand roles:

AI Security Specialist

• Average Salary: $120,000 – $160,000
• Responsibilities: Securing AI systems, implementing guardrails, threat modeling

AI Security Architect

• Average Salary: $140,000 – $190,000
• Responsibilities: Designing secure AI infrastructure, establishing governance frameworks

MLOps Engineer (Security Focus)

• Average Salary: $130,000 – $175,000
• Responsibilities: Securing CI/CD pipelines, automating security testing, model monitoring

AI Governance Engineer

• Average Salary: $115,000 – $155,000
• Responsibilities: Implementing compliance controls, auditing AI systems, policy development

AI Risk Analyst

• Average Salary: $110,000 – $150,000
• Responsibilities: Assessing AI-related risks, evaluating model vulnerabilities

Market Demand

According to recent industry research:

• AI security job postings increased 412% in 2024
• 68% of organizations plan to hire AI security specialists in 2026
• Average time-to-fill for AI security roles: 89 days (indicating talent shortage)
• Salary premiums for AI + security skills: 25-35% above traditional security roles

Preparing for SecAI+: Study Strategy

Recommended Background

Before Pursuing SecAI+:

1. Foundational Security Knowledge
   • Security+ or equivalent understanding
   • Network security concepts
   • Incident response fundamentals
2. AI/ML Basics
   • Understanding of machine learning concepts
   • Familiarity with Python programming
   • Basic exposure to AI tools (ChatGPT, Claude, etc.)
3. Hands-On Experience
   • 2+ years in cybersecurity roles
   • Exposure to cloud environments
   • API security experience

Study Resources

Supplemental Resources:

• OWASP LLM Top 10: Essential reading for understanding AI vulnerabilities
• MITRE ATLAS Knowledge Base: Framework for AI threat modeling
• NIST AI RMF Documentation: Understanding AI risk management
• EU AI Act Text: Compliance requirements and classifications

Hands-On Practice:

• Experiment with LLMs: Try prompt injection, jailbreaking techniques (in sandbox environments)
• Cloud AI Services: Get hands-on with AWS Bedrock, Azure OpenAI, Google Vertex AI
• Open-Source Tools: Deploy and secure models using Ollama, Hugging Face
• Vector Databases: Practice with Pinecone, Weaviate, Chroma
• AI Security Tools: Explore prompt firewalls, guardrail frameworks

Lab Environment

CompTIA recommends the following for hands-on practice:

Hardware:

• Laptop with GPUs (NVIDIA Jetson Nano Orin recommended)
• Cloud VM access (AWS, Azure, or GCP)
• Minimum 16GB RAM, 50GB storage

Software:

• Python environment with Jupyter
• R environment (for statistical analysis)
• Docker containers for isolated testing
• Vector databases (NoSQL, Neo4j Graph Database)
• Open-source LLMs (via Ollama, Hugging Face)
• AI IDEs and chatbots for experimentation

The SecAI+ Certification Journey

Step 1: Self-Assessment (Now – January 2026)

• Evaluate your current AI and security knowledge
• Identify knowledge gaps
• Begin foundational study

Step 2: Intensive Preparation (January – February 2026)

• Complete official CompTIA training materials
• Practice with hands-on labs
• Join study groups and online communities
• Take practice exams

Step 3: Certification (February 17, 2026 and Beyond)

• Schedule your exam
• Pass SecAI+ CY0-001
• Update resume, LinkedIn profile
• Begin applying specialized skills

Step 4: Continuing Education (Ongoing)

• Maintain certification through CEUs
• Stay current with emerging AI threats
• Participate in AI security community
• Consider advanced specializations

Common Questions About SecAI+

Is SecAI+ required to work with AI security?

No—there are no legal requirements. However, SecAI+ provides:

• Validated proof of knowledge for employers
• Structured learning path through complex material
• Industry-recognized credential
• Competitive advantage in job market

Should I wait for more study materials?

Pre-order now if: You want guaranteed access and early-adopter advantage. Wait until Q1 2026 if: You prefer fully developed third-party study resources and community forums.

How does SecAI+ relate to other CompTIA certifications?

Prerequisite Path (Recommended):

1. Security+ → Foundational security knowledge
2. CySA+ → SOC analyst and threat detection skills
3. SecAI+ → Specialized AI security expertise

Alternative Path:

• Security+ → SecAI+ (if you have AI/ML background)
• CySA+ → SecAI+ (if you’re SOC analyst adding AI skills)

Will AI security knowledge become obsolete quickly?

No—SecAI+ teaches foundational principles that will remain relevant:

• Threat modeling methodologies
• Risk management frameworks
• Governance structures
• Attack patterns and defenses

While specific tools evolve, core concepts persist. CompTIA will update the exam every 3 years to reflect new developments.

Can I take SecAI+ without coding experience?

Recommended but not required. While programming knowledge (especially Python) enhances your capabilities, SecAI+ focuses on security concepts, not development. Understanding code helps but isn’t mandatory for passing.

The Future of AI Security

Industry Predictions

By 2027:

• 85% of SOCs will have integrated AI-powered tools
• AI security specialist will be among the top 5 most in-demand IT roles
• Regulatory frameworks will expand to 50+ countries
• AI-powered attacks will account for 30% of all cyber incidents

By 2030:

• Autonomous AI agents will require dedicated security teams
• AI supply chain security will be mandatory for government contractors
• SecAI+ will be as common as Security+ in job requirements
• New AI threat categories will emerge requiring specialized defenses

The Arms Race: AI Defense vs. AI Attack

We’re entering an era where both defenders and attackers leverage AI. SecAI+ prepares you for this reality by teaching:

• How attackers weaponize AI for reconnaissance and exploitation
• How defenders use AI for threat hunting and response
• The techniques for staying ahead in this technological arms race

Why Choose ITU Online for SecAI+ Training

At ITU Online, we’re preparing comprehensive training for CompTIA SecAI+ that goes beyond exam preparation to build real-world skills.

Our SecAI+ Training Approach

1. Expert-Led Instruction

• Courses developed by security professionals with AI specialization
• Real-world examples from actual AI security implementations
• Guest lectures from AI security practitioners

2. Hands-On Labs

• Cloud-based lab environments pre-configured for AI security practice
• Real AI systems to secure and test
• Scenario-based exercises mimicking production environments

3. Comprehensive Coverage

• All exam objectives thoroughly explained
• Supplemental content on emerging AI threats
• Case studies from AI security incidents

4. Exam Preparation

• Full-length practice exams mirroring actual test
• Performance-based question simulations
• Personalized study plans based on knowledge gaps

5. Career Support

• Resume optimization for AI security roles
• Interview preparation specific to AI security positions
• Job placement assistance and career counseling

Training Formats

• Self-Paced Online: Study on your schedule
• Instructor-Led Virtual: Live classes with expert instructors
• Bootcamp Intensive: Accelerated 5-day preparation course
• Corporate Training: Customized programs for enterprise teams

Conclusion: The Time to Act Is Now

The convergence of AI and cybersecurity represents one of the most significant paradigm shifts in the technology sector’s history. Organizations worldwide are racing to adopt AI technologies while simultaneously struggling to secure them and defend against AI-powered threats.

CompTIA SecAI+ provides the validated expertise that employers desperately need. As the first and only comprehensive AI security certification, it offers early adopters an unparalleled competitive advantage.

The exam launches February 17, 2026, but preparation should begin now. The complexity of AI security, combined with the breadth of material covered, demands dedicated study time. Early preparation also allows you to:

• Build hands-on experience with AI security tools
• Stay current with rapidly evolving AI threats
• Network with other AI security professionals
• Position yourself for the emerging job opportunities

Your Next Steps

1. Pre-order SecAI+ to secure your exam voucher
2. Begin foundational study on AI concepts and security frameworks
3. Set up a lab environment for hands-on practice
4. Join the community of AI security professionals
5. Enroll in training at ITU Online for structured preparation

The future of cybersecurity is AI-driven. SecAI+ ensures you’re not just prepared for that future—you’re leading it.

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About CompTIA SecAI+ Certification

Exam Code: CY0-001
Launch Date: February 17, 2026
Domains: Basic AI Concepts (17%), Securing AI Systems (40%), AI-Assisted Security (24%), AI Governance, Risk, and Compliance (19%)
Recommended Experience: 3-4 years IT, 2+ years cybersecurity
Prerequisites: None (Security+, CySA+, or equivalent recommended)
Official Website: CompTIA SecAI+

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