Software Composition Analysis (SCA)

Software Composition Analysis (SCA) is an automated process to identify open-source components, their known vulnerabilities, and licensing risks. It enables enterprises to generate a Software Bill of Materials (SBOM) as required by ISO/IEC 50863 and the EU AI Act. Unlike SAST, which analyzes custom code, SCA focuses on third-party dependencies. This is critical for modern enterprises where up to 80% of application code is composed of open-source libraries. The tool-set typically includes vulnerability detection, license compliance checking, and policy enforcement. This aligns with the NIST Software Supply Chain Security guidance, ensuring that software-related risks are identified before deployment. For companies subject to the GDPR, SCA helps prevent data breaches originating from vulnerable third-party libraries, thereby reducing the risk of regulatory fines. This is particularly relevant in the AI era, where AI models often rely on numerous open-source packages with unknown security postures.

Practical application of SCA follows a three-step approach: Inventory, Monitor, and Remediate. First, the tool generates a comprehensive SBOM, mapping every dependency,-transitive dependency, and version number. This inventory-building phase is the foundation of the Software Bill of Materials (SBOM)-centric risk management. Second, continuous monitoring against databases like the Global Vulnerability Database (GVD) ensures that new vulnerabilities are detected in real-time, even for software already in production. Third, the remediation workflow prioritizes vulnerabilities based on reachability and exploitability, preventing developers from wasting time on non-exploitable risks. A Taiwan-based electronics manufacturer, for instance, could use SCA to ensure its IoT firmware-free of critical vulnerabilities before shipping to international clients. Key performance indicators (KPIs) include a 70% reduction in zero-day exposure time and 100% compliance with the EU AI Act's transparency requirements within the first year of implementation.

Taiwan enterprises face three primary challenges: lack of specialized talent, supply chain complexity, and evolving international regulations. Many SMEs lack the expertise to interpret SCA reports, which often contain high false-positive rates. To overcome this, companies should invest in AI-enhanced SCA tools that provide reachability analysis to filter out non-exploitable vulnerabilities. Secondly, the complexity of global supply chains makes it difficult to obtain SBOMs from all vendors; the solution lies in standardizing procurement requirements to include SBOMs as a contractual obligation. Lastly, the EU AI Act and the US Executive Order 14028 are creating new compliance pressures. Taiwan companies must be closely monitoring these regulations to avoid being locked out of key markets. A phased implementation—starting with critical systems and expanding to the entire portfolio—is the most cost-effective way to manage these challenges while ensuring continuous improvement.

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