Enhancing Security Operations Through Automated Threat Analysis and Response

Company M, a large enterprise in the ICT industry, operates a Security Operations Center responsible for cyber threat response, data protection, and security solution management. To respond to emerging malware variants and ransomware threats, the company had already been using AhnLab Threat Intelligence Reporting Center together with multiple security solutions.

However, as cyber threats became more sophisticated and security resources remained limited, manual analysis and verification processes began to slow down response activities. To overcome these challenges, Company M adopted AhnLab MDS with an API-based automation framework, enabling faster analysis, more accurate verification, and more efficient security operations.

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Expanding Threat Coverage Through Integrated Analysis

Company M strengthened its analysis process by integrating suspicious file verification with AhnLab Threat Intelligence Reporting Center. This allowed the company to determine whether newly discovered malware variants or suspected ransomware files were actual threats or false positives.

By applying consistent analysis criteria across various types of threat data, Company M reduced detection gaps and improved its ability to respond to emerging and variant-based attacks.

Less Manual Work, Faster Response Through Automation

Before adopting the new framework, Company M relied on a web-based process to collect analysis results. This approach often required retrieving unnecessary webpage data before extracting the information needed for verification, which increased processing time and created additional operational burden.

Some samples still required manual review by analysts, resulting in repetitive tasks and delayed response. Through AhnLab MDS-integrated API automation, Company M was able to selectively retrieve required data, reduce manual filtering, and apply analysis results to security operations more quickly.

Key Benefits

• Expanded threat detection coverage and reduced detection gaps
• Established an API-based automation framework
• Reduced repetitive verification tasks
• Improved analysis accuracy and processing efficiency
• Accelerated response and application of analysis results

Download the case study to explore the full story of how AhnLab MDS and API-based automation helped Company M improve threat analysis, enhance data accuracy, and build a faster, more stable security operations framework.

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