Key takeaways
- Visibility is the prerequisite for security. Rapidly changing environments and AI integration create blind spots that attackers exploit. Only 22% of organizations maintain a full API inventory and know which of their APIs return sensitive data, leaving the vast majority exposed to untracked risks.
- AI adoption expands the attack surface. Emerging AI-linked APIs, such as LLM APIs, create new dependencies that retrieve data and execute actions without traditional oversight. As the most common and least defended attack vector, these connectors require robust discovery before they become entry points for exploits.
- Unmanaged assets drive recurring breaches. Organizations struggle to govern shadow or zombie APIs, contributing to the fact that 81% of APAC firms experienced a security incident in the last year; tighter automated tracking is necessary to break this cycle of persistent threats.
- Knowledge gaps between leadership and technical teams hinder resilience. C-suite overconfidence in API testing processes masks the reality of limited software development lifecycle (SDLC) integration. Most organizations do not factor security-focused testing into their APIs’ lifecycles, nor do they integrate API testing into CI/CD processes. Aligning executive perception with what DevSecOps teams are actually seeing can help ensure that API-powered technologies, such as AI applications, are tested to be resilient against threats.
- Weak API oversight carries significant financial and regulatory weight. Inadequate tracking of sensitive data flows leaves firms vulnerable to million-dollar incidents and noncompliance with regional data laws in APAC countries such as China, India, and Japan. Implementing data-aware API visibility is now a basic requirement to protect core business investments.
- Market-specific volatility threatens regional stability. Japan and Singapore face the highest financial stakes, with Japan’s average incident cost skyrocketing by nearly 200% year-on-year. Organizations must move beyond generic policies to address these localized surges in cost and complexity.
Frequently Asked Questions (FAQ)
Frequently Asked Questions (FAQ)
The rapid expansion of AI innovation and cloud adoption has increased the scale and complexity of API estates, making it harder for teams to track connections and identify risks while introducing a flood of new APIs that are unseen, untested, and unprotected.
The typical organization now has an inventory of almost 6,000 APIs, while the largest estates in the top quartile can exceed 32,300 APIs.
According to the study, 43% of organizations in the APAC region experienced an attack involving APIs linked to AI technologies, such as LLMs, apps, and agents, making it the top-ranked incident type.
An average incident costs more than US$1 million, with the highest costs stemming from repairs, remediation, and service downtime.
Only 11% of Japanese respondents have a full API inventory and know which APIs return sensitive data, a sharp decline from 37% in 2025.
Yes; for example, 56% of C-suite respondents feel prepared for AI-linked API attacks, compared to only 44% of the AppSec teams responsible for actual implementation.
Regulations like China’s Data Security Law and India’s Digital Personal Data Protection Act now require organizations to prove they understand and protect API-linked data flows to detect and prevent breaches.
While 40% report advanced testing, only 19% have fully embedded security testing across the API software development lifecycle (SDLC) and CI/CD pipelines.