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Enterprise AI Security Practice: From Data Leakage Prevention to Governance

As the adoption of generative AI accelerates, new security threats such as corporate confidential information leaks and prompt injections are surging. This course covers strategies for embedding security throughout the entire AI lifecycle, based on the National Intelligence Service (NIS) guidelines' 30 core security measures and 15 practical threat cases. It also addresses security issues in the latest AI trends, such as Agentic AI and Physical AI, and presents methods for establishing governance frameworks that can be immediately applied in practice.

21 learners are taking this course

Level Beginner

Course period Unlimited

security
security
agents
agents
AI
AI
security training
security training
Government-Funded Bootcamp
Government-Funded Bootcamp
security
security
agents
agents
AI
AI
security training
security training
Government-Funded Bootcamp
Government-Funded Bootcamp

What you will gain after the course

  • Customized security design for 4 types of AI adoption and establishment of 30 core security measures

  • Identification and response to 15 major AI security threats, including prompt injection and data leakage

  • Establishing Security Governance and Safe Utilization Frameworks for Agentic AI and Physical AI Environments


Generative AI Security, Information Leakage Can We Prevent It?

In the early stages of AI adoption, you will systematically learn 30 core security measures based on the National Intelligence Service guidelines to resolve security anxieties and prevent information leakage incidents.


You are someone who actively uses generative AI like ChatGPT and Claude for work, yet remains cautious about the possibility of internal information being exposed to AI services.

Are you feeling frustrated because you cannot clearly distinguish between the 15 types of AI security threats encountered in practice, such as prompt injection and data leakage, and the 30 core security measures presented in the National Intelligence Service guidelines?

You will learn practical methods for internalizing security across the entire AI lifecycle, from customized security designs for the four types of AI adoption to the latest security issues in Agentic AI and Physical AI.

AI security is no longer a vague anxiety; you can be perfectly prepared through systematic learning and practical application.


Master the security design for
4 types of corporate AI adoption and
the implementation methods for 30
core practical security measures.


Transitioning from the risks of AI adoption
to a secure organization,
without the worry of data leaks,
you will grow into an AI governance expert.




By the end of this course, you will


You will be able to effectively respond to new security threats arising from the adoption of generative AI.

  • You will be able to accurately identify 15 major security threats that frequently occur when using generative AI, such as corporate confidential information leakage and prompt injection, and establish customized response strategies for each threat type. You no longer have to worry about information leakage accidents caused by AI utilization.

You can directly build the optimal security design tailored to the four types of AI adoption.

  • By selecting and applying 30 key security measures tailored to your company's AI adoption goals and methods, you will complete a framework that internalizes security throughout the entire AI lifecycle. You will be able to present a security roadmap optimized for each corporate environment.

You can deeply understand the security issues of the latest AI trends, such as Agentic AI and Physical AI, and utilize them safely.

  • You can accurately identify the unique security risks of autonomous Agentic AI and real-world-connected Physical AI, and present governance and utilization strategies for their safe operation. Preemptively prepare for the potential risks of future AI technologies.

You can lead the establishment of AI governance and the settlement of a safe AI culture within the enterprise.

  • You will learn how to establish practical AI governance policies based on National Intelligence Service (NIS) guidelines and foster a culture of safe AI usage by raising the security awareness of organizational members. You can grow into a security expert leading the AI era.






✔️

Strengthening core practical capabilities to take responsibility for corporate security in the era of generative AI

AI Era, Corporate Security Practice:
From Information Leakage Prevention to Governance

This course provides an in-depth study of practical strategies to counter emerging security threats, such as information leakage and prompt injection, which are surging with the adoption of generative AI. Based on the National Intelligence Service (NIS) guidelines, the curriculum covers 30 core security measures and 15 practical threat cases. It addresses security embedding across the entire AI lifecycle and explores security issues in the latest trends, including Agentic AI and Physical AI, while presenting methods for establishing governance frameworks that can be immediately applied in the field.

Practical AI Security Threat Identification and Response

We analyze 15 major AI security threat cases, such as prompt injection and data leakage, alongside customized security designs for four types of corporate AI adoption, and learn practical response strategies for each threat. Furthermore, through hands-on exercises in establishing security governance and safe utilization systems for Agentic AI and Physical AI environments, participants will develop capabilities that can be immediately applied in the field.

Core Measures and Guidelines for AI Security Internalization

You will systematically acquire 30 core security measures based on the National Intelligence Service (NIS) guidelines and learn how to apply the 'Security by Design' principle, a security internalization strategy for each stage of the AI lifecycle. Through this, we provide practical guidance for establishing AI security governance policies optimized for corporate environments and fostering a security culture within the organization.


📚

AI Security Practical Strategy:
From Information Leakage to Governance

Section 1

Analysis of AI Security Threat Cases and Countermeasures Based on NIS Guidelines

We provide an in-depth analysis of real-world AI security incidents and cover 30 core security measures based on the National Intelligence Service (NIS) guidelines. Additionally, we present customized security designs for different implementation types and methods for the safe utilization of commercial AI.


Section 2

Latest AI Trends and Establishing Corporate Security Governance

This course covers security issues related to the latest AI technology trends, such as Agentic AI and Physical AI, and teaches how to establish security governance and safe utilization systems in these environments. Finally, it aims to spread a practical security culture through the establishment of in-house AI governance and implementation tasks.


We can solve the concerns
of these people!

📌

Corporate Security Managers
Those who have personally experienced or received reports of accidental internal information leakage after the introduction of generative AI tools.


📌

Compliance Officers
Those tasked with managing the risk of corporate confidential information leakage caused by AI adoption, and establishing and implementing an AI governance framework within the organization, including 30 core security measures based on National Intelligence Service guidelines.


📌

Information Security Managers
Those who need to establish practical countermeasures against 15 major security threats, such as prompt injection and data leakage, that may arise while utilizing generative AI like ChatGPT in business operations.




security, agents, devsecops, Midjourney, prompt engineering, AI security

 security, agents, artificial intelligence (AI), security education, government-funded bootcamp


Notes before taking the course


Practice Environment

  • Operating System: General-purpose operating systems such as Windows, macOS, Linux, etc.

  • Required Tools: Web browser (Chrome recommended), PDF viewer

  • PC Specifications: No special high-end requirements

Prerequisite Knowledge and Important Notes

  • Security personnel currently reviewing or operating AI implementation

  • Those with experience using generative AI, such as ChatGPT, for work tasks

  • It is even better if you have experience related to establishing AI governance.

Learning Materials

  • Lecture slide PDF (provided separately)

  • Security measures documentation based on practical threat cases and National Intelligence Service (NIS) guidelines

  • Security Internalization Checklist for Each Stage of the AI Lifecycle


Recommended for
these people

Who is this course right for?

  • Security officers and information security managers who are considering or currently operating AI implementation within their organizations.

  • Practitioners who need to manage security risks while utilizing generative AI, such as ChatGPT, for work.

  • Executives and compliance officers responsible for establishing AI governance policies and embedding a security culture within the organization

Need to know before starting?

  • Understanding of basic information security concepts (Confidentiality, Integrity, Availability, etc.)

  • Experience using or basic understanding of generative AI services such as ChatGPT and Claude

  • Practical experience in corporate IT systems and data management processes

Hello
This is Slearnic AI LAB

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As the CEO of 'Slurnic,' a startup maximizing the value of digital labor through AI, he develops and provides solutions that analyze early-stage startup business development and organizational tasks at the workflow level and transform them into AI-based processes. Additionally, as the co-founder of 'Slurners,' a routine management solution company for individuals with borderline intellectual functioning, he leads product and technology strategy while building practical support systems to help design daily life.


He conducts AI lectures across various educational platforms and industrial sites, including Multi Campus, Inflearn, Crowd Academy, Fast Campus, and Class101. In particular, his practical AI education capabilities have been proven at Inflearn, where he received a 2025 Award and surpassed 9,000 cumulative students. Based on his actual entrepreneurial experience, he also serves as a business development mentor at Ablen, supporting early-stage teams with market entry strategies, productization, and sales/partnership design. Ultimately, he aims to enhance both corporate productivity and individual capabilities through the practical application of AI, contributing to the productivity of society as a whole and, on a larger scale, the Gross Domestic Product (GDP).

Contact: mingyu.kim@slearnic.com

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