GIAC AI Security Automation Engineer (GASAE) Exam Syllabus
Use this quick start guide to collect all the information about GIAC GASAE Certification exam. This study guide provides a list of objectives and resources that will help you prepare for items on the GIAC AI Security Automation Engineer (GASAE) exam. The Sample Questions will help you identify the type and difficulty level of the questions and the Practice Exams will make you familiar with the format and environment of an exam. You should refer this guide carefully before attempting your actual GIAC AI Security Automation Engineer (GASAE) certification exam.
The GIAC GASAE certification is mainly targeted to those candidates who want to build their career in Artificial Intelligence domain. The GIAC AI Security Automation Engineer (GASAE) exam verifies that the candidate possesses the fundamental knowledge and proven skills in the area of GIAC GASAE.
GIAC GASAE Exam Summary:
| Exam Name | GIAC AI Security Automation Engineer (GASAE) |
| Exam Code | GASAE |
| Exam Price | $999 (USD) |
| Duration | 180 mins |
| Number of Questions | 82 |
| Passing Score | 70% |
| Books / Training | SEC598: AI and Security Automation for Red, Blue, and Purple Teams |
| Schedule Exam | PearsonVUE |
| Sample Questions | GIAC GASAE Sample Questions |
| Practice Exam | GIAC GASAE Certification Practice Exam |
GIAC GASAE Exam Syllabus Topics:
| Topic | Details |
|---|---|
| Adversary Emulation Fundamentals | - The candidate will demonstrate an understanding of adversary emulation frameworks and automation techniques, tools and breach-and-attack simulation platforms to model and chain offensive attack behaviors. |
| Artificial Intelligence Fundamentals | - The candidate will demonstrate an understanding of artificial intelligence fundamentals, including how AI processes text, large language models, retrieval-augmented generation, different types of AI models, and the characteristics of agentic AI. |
| Automating Offensive Workflows | - The candidate will demonstrate an understanding of how to deploy and automate offensive security workflows using frameworks and tools such as agentic AI, cloud adversary emulation platforms, and orchestration techniques for chaining attacks to simulate real-world adversaries. |
| Automating Workflows | - The candidate will demonstrate an understanding of workflow automation using scripting languages, infrastructure as code tools, and collaborative environments to support incident response, offensive operations, and purple team collaboration. |
| AWS Cloud Security and Incident Response Automation | - The candidate will demonstrate an understanding of AWS security and automation services and how they are applied to compliance, logging, automated incident response, and continuous security improvement. The candidate will also demonstrate an understanding of how AWS tools can be used to build AI-assisted security workflows. |
| Azure Cloud Security and Incident Response Automation | - The candidate will demonstrate an understanding of the security controls and automation capabilities in Azure, including infrastructure as code, Microsoft Defender, Sentinel, and AI-driven services and how they support incident response, security monitoring, and continuous improvement. |
| Defensive Security Automation | - The candidate will demonstrate an understanding of how automation supports defensive security operations, including agent deployment, incident artifact collection, enrichment, and integration into modern SOC and fusion center workflows. |
| Security Automation Fundamentals | - The candidate will demonstrate an understanding of common security automation terminology, tools, and strategies for selecting, planning, and deploying automation workflows leveraging DevOps principles. |
| Security Orchestration Automation and Response | - The candidate will demonstrate an understanding of how to utilize security orchestration and automation techniques to enhance incident response efficiency and effectiveness of a security operations team using playbooks, independent tool integrations, and common SOAR tools. |
| Using Automation and AI for Detection Engineering and Incident Response | - The candidate will demonstrate an understanding of how automation and AI support detection engineering and incident response, including their application across incident response models, forensic tooling, SOAR playbooks, enrichment, and the integration of generative and agentic AI to enhance SOC capabilities. |
To ensure success in GIAC GASAE certification exam, we recommend authorized training course, practice test and hands-on experience to prepare for GIAC AI Security Automation Engineer (GASAE) exam.
