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AI security is becoming a more specialized area of cybersecurity as organizations deploy LLMs, RAG applications, AI agents, and other AI-powered systems. For security professionals, developers, and people entering the field, choosing a certification can be difficult because different programs focus on different areas.
Here are three AI security certifications worth considering, depending on your experience and career goals.
1. Modern Security – Certified AI Security Expert (MSec-CAIS)
For someone who wants to understand AI security from the fundamentals and then move into practical security testing, the Certified AI Security Expert (MSec-CAIS) from Modern Security is a strong option to consider.
One useful aspect of the program is that it does not assume prior AI or LLM knowledge. The course starts with the modern AI stack, including LLMs, RAG, embeddings, vector databases, agentic systems, and MCPs, before moving into security.
The training covers both offensive and defensive areas. Learners work through topics such as prompt injection, indirect prompt injection, sensitive information disclosure, authorization problems, model poisoning, backdoors, AI threat modeling, and defensive controls. The course also includes hands-on labs rather than focusing only on theoretical concepts.
Best for: Beginners in AI security, security engineers, developers, penetration testers, red teamers, and technical professionals who want a practical introduction to securing AI applications.
Why consider it: It provides a path from understanding how AI applications are built to understanding how those applications can be attacked and defended.
Modern Security AI Security Certification
2. GIAC AI Platform Security (GAIPS)
The GIAC AI Platform Security (GAIPS) certification is aimed more at practitioners who want to demonstrate their ability to assess and secure generative AI applications and LLM development pipelines.
GAIPS covers areas including AI and LLM fundamentals, AI application architecture, agentic systems, AI integrations, MLOps and MLSecOps, data flows, APIs, and deployment workflows. The certification uses GIAC's CyberLive hands-on testing format, which is designed to assess practical skills in realistic environments.
The certification is particularly relevant for people already working in areas such as application security, cloud security, AI/ML engineering, software development, security consulting, or security auditing.
Best for: Experienced security practitioners, AppSec engineers, cloud security professionals, AI/ML engineers, and professionals who already have a technical cybersecurity foundation.
Why consider it: It has a strong focus on securing the AI application and LLM development lifecycle, with hands-on assessment rather than relying solely on multiple-choice testing.
3. GIAC AI Security Automation Engineer (GASAE)
If your interest is less about securing an individual AI application and more about using AI and automation within security operations, the GIAC AI Security Automation Engineer (GASAE) is another option.
GASAE focuses on applying AI and automation across offensive, defensive, and cloud security operations. Its coverage includes automated asset discovery, vulnerability discovery, adversary emulation, AI-driven attack simulations, infrastructure automation, and SOAR-based incident response.
It also covers AI fundamentals such as large language models, RAG, and agentic AI, making it relevant for security professionals who want to incorporate AI into existing security workflows rather than focusing exclusively on AI application security.
Best for: Security engineers, red and blue team professionals, cloud security teams, SOC professionals, and practitioners interested in security automation.
Why consider it: The focus is on applying AI to real security operations, including offensive and defensive workflows.
Which One Should You Choose?
There isn't one AI security certification that is perfect for everyone.
If you're new to AI security, Modern Security's Certified AI Security Expert is worth looking at because it starts with AI and LLM fundamentals before moving into attacks, threat modeling, and defenses.
If you're already an experienced security practitioner and want a certification focused specifically on securing GenAI applications and LLM pipelines, GAIPS is a more specialized option.
If your main goal is to use AI and automation in offensive, defensive, or cloud security operations, GASAE is more closely aligned with that path.
Ultimately, the certification is only one part of building an AI security career. Hands-on experience, understanding how AI applications are actually built, and the ability to identify and mitigate real security weaknesses are just as important as having the credential itself.
Here are three AI security certifications worth considering, depending on your experience and career goals.
1. Modern Security – Certified AI Security Expert (MSec-CAIS)
For someone who wants to understand AI security from the fundamentals and then move into practical security testing, the Certified AI Security Expert (MSec-CAIS) from Modern Security is a strong option to consider.
One useful aspect of the program is that it does not assume prior AI or LLM knowledge. The course starts with the modern AI stack, including LLMs, RAG, embeddings, vector databases, agentic systems, and MCPs, before moving into security.
The training covers both offensive and defensive areas. Learners work through topics such as prompt injection, indirect prompt injection, sensitive information disclosure, authorization problems, model poisoning, backdoors, AI threat modeling, and defensive controls. The course also includes hands-on labs rather than focusing only on theoretical concepts.
Best for: Beginners in AI security, security engineers, developers, penetration testers, red teamers, and technical professionals who want a practical introduction to securing AI applications.
Why consider it: It provides a path from understanding how AI applications are built to understanding how those applications can be attacked and defended.
Modern Security AI Security Certification
2. GIAC AI Platform Security (GAIPS)
The GIAC AI Platform Security (GAIPS) certification is aimed more at practitioners who want to demonstrate their ability to assess and secure generative AI applications and LLM development pipelines.
GAIPS covers areas including AI and LLM fundamentals, AI application architecture, agentic systems, AI integrations, MLOps and MLSecOps, data flows, APIs, and deployment workflows. The certification uses GIAC's CyberLive hands-on testing format, which is designed to assess practical skills in realistic environments.
The certification is particularly relevant for people already working in areas such as application security, cloud security, AI/ML engineering, software development, security consulting, or security auditing.
Best for: Experienced security practitioners, AppSec engineers, cloud security professionals, AI/ML engineers, and professionals who already have a technical cybersecurity foundation.
Why consider it: It has a strong focus on securing the AI application and LLM development lifecycle, with hands-on assessment rather than relying solely on multiple-choice testing.
3. GIAC AI Security Automation Engineer (GASAE)
If your interest is less about securing an individual AI application and more about using AI and automation within security operations, the GIAC AI Security Automation Engineer (GASAE) is another option.
GASAE focuses on applying AI and automation across offensive, defensive, and cloud security operations. Its coverage includes automated asset discovery, vulnerability discovery, adversary emulation, AI-driven attack simulations, infrastructure automation, and SOAR-based incident response.
It also covers AI fundamentals such as large language models, RAG, and agentic AI, making it relevant for security professionals who want to incorporate AI into existing security workflows rather than focusing exclusively on AI application security.
Best for: Security engineers, red and blue team professionals, cloud security teams, SOC professionals, and practitioners interested in security automation.
Why consider it: The focus is on applying AI to real security operations, including offensive and defensive workflows.
Which One Should You Choose?
There isn't one AI security certification that is perfect for everyone.
If you're new to AI security, Modern Security's Certified AI Security Expert is worth looking at because it starts with AI and LLM fundamentals before moving into attacks, threat modeling, and defenses.
If you're already an experienced security practitioner and want a certification focused specifically on securing GenAI applications and LLM pipelines, GAIPS is a more specialized option.
If your main goal is to use AI and automation in offensive, defensive, or cloud security operations, GASAE is more closely aligned with that path.
Ultimately, the certification is only one part of building an AI security career. Hands-on experience, understanding how AI applications are actually built, and the ability to identify and mitigate real security weaknesses are just as important as having the credential itself.