Cybersecurity is becoming a key testing ground for frontier artificial intelligence (AI), moving beyond simple question-and-answer tasks or document generation. The field now requires large-scale code analysis, vulnerability detection, attack path inference, and exploit creation, showcasing AI's long-term reasoning and autonomous agent capabilities.
According to the Korea Internet & Security Agency (KISA), the government is strengthening the national AI security framework to counter cyber threats that exploit high-performance AI. In May, it approved the 'Private Information Protection Plan for AI-Based Cyber Threat Response' and aims to gradually transition the domestic information security system to an AI technology base starting in 2027.
Global AI companies are also expanding their technological competition into the cybersecurity sector. Recently, AI models with enhanced security capabilities, such as Anthropic's Mythos and OpenAI's 'GPT-5.5-Cyber,' have emerged, broadening the application of AI from conversation and document generation to vulnerability analysis and both offensive and defensive operations.
Cybersecurity is recognized as a field that can simultaneously validate AI's reasoning abilities and autonomy. Actual security tasks require understanding complex code and attack paths, as well as verifying results through multiple layers of judgment.
Vulnerability analysis and exploit creation demand a high level of reasoning ability. An exploit is a code or technique that leverages security weaknesses for actual attacks, necessitating an understanding of the context of vast codebases, tracking control flows, formulating hypotheses, and validating them through proof of concept. This is why the ability to detect zero-day vulnerabilities or solve Capture The Flag (CTF) hacking challenges is used as a benchmark for assessing the practical level of AI agents.
Kim Eun-sung, head of KISA's Threat Response Policy Team, highlighted that security-focused AI can be utilized for both offensive and defensive purposes. He explained that it can be applied not only in aggressive security tasks like vulnerability detection and red teaming but also in defensive operations such as threat hunting, security operations center (SOC) automation, and automated patch generation.
The importance of protecting AI itself is also growing. 'AI for Security' refers to using AI to enhance existing security tasks like vulnerability detection, incident analysis, and response automation.
Conversely, 'Security for AI' pertains to protecting AI models and systems from threats such as prompt injection, model theft, data contamination, and supply chain risks. These two areas are not separate; as AI utilization expands, a comprehensive security framework is necessary.
The government's and KISA's emphasis on securing domestic security-focused foundation models stems from South Korea's unique threat environment and data sovereignty issues. South Korea faces threats from specific attackers like North Korea and is exposed to Korean-style attack techniques, along with specialized operational and security environments involving Hangul (HWP) documents, network separation, and document security (DRM).
KISA believes that generic overseas models may not adequately reflect this environment and that it is challenging to transmit sensitive information about system configurations or software used to foreign services.
Instead of competing directly with global tech giants in generic AI, a strategy focusing on specific areas like security has been proposed. Kim noted that while it may be difficult to quickly close the gap with generic frontier models, a specialized model that intensively learns in specific fields tailored to the South Korean security environment could enhance competitiveness.
He stated that since it is not easy to secure a market position by competing directly with generic frontier AI, building a foundation model specialized for the South Korean security environment to enhance expertise is a viable direction. Kim remarked, "The direction of the security-focused foundation model is to follow one discipline at a time."
* This article has been translated by AI.
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