1. Comprehensive Endpoint and Asset Detection

To continuously enhance security, integrated checks on existing assets are necessary. Knowing exactly what structure internal assets have and what threats they may be exposed to is important.

• Accurate Asset Identification: As AI adoption increases assets, security teams must decide 'where to look first.' After identifying assets based on IP/domain, they should filter genuine threats based on sophisticated asset reliability assessments to reduce resource use and focus on real threats.

• Vulnerable Asset Map Construction: Visual mapping of asset connections to predict the spread of risks from vulnerable assets.

• Initial Threat Modeling: Analyze the structure and flow of AI systems before deployment, and derive potential threat scenarios. This goes beyond simply understanding the system, predicting where penetration is possible and forming the basis for responses.

2. Visualization of Vulnerabilities and Issue Response

When vulnerabilities are found within the company, if all security personnel aren't aware simultaneously, response speeds decrease, and threats may accumulate. While technical responses are important, without a clear sharing system on 'who took what action and when,' the same issues tend to recur or might be overlooked.

• AI-Specific Vulnerability Identification: Check for potential real threats like authentication bypass, session hijacking, and malicious data injection into models, identifying hidden high-risk vulnerabilities. Discovered vulnerabilities should be classified by risk level (critical, high, medium, low) to set priorities and develop corresponding response strategies.

• Status Sharing Report: Sharing reports on rankings of vulnerable assets, frequently found types, etc., to inform prioritization and response.

• Establish Internal Communication System: Relevant staff should share updates in real-time regarding security issues, accumulate history, and maintain a communication channel to prevent breaches.

3. Conduct Penetration Testing from an Attacker's Perspective

Automated vulnerability scanning or internal audits may miss complex attack scenarios. Particularly, social engineering, insider threats, and multi-stage evasive attacks are difficult to counter with purely segmented checks. What is needed now is to view the system as a hacker does and realistically simulate vulnerable pathways.

• White Hat Hacker-Based Red Team Testing: Conduct simulation hacking that replicates the techniques attackers use when actually infiltrating systems. Test the entire process from external penetration → privilege escalation → internal spread → data exfiltration as if it's real.

• Scenario-Based Evaluation: Utilize the MITRE ATT&CK framework to visualize attack techniques and tactics related to AI systems and design custom scenarios tailored to the corporate environment.

• Develop Response Strategies: Based on test results, improve not only vulnerability measures but also prevention and response systems to avoid recurrence.

For the more advanced IT environment brought by AI, security must become smarter.
To prevent additional breaches, a system that looks through the perspective of the attacker and continuously checks and improves is necessary.
Proactive security fitting the AI era, it’s time to begin.