AI adoption drives new importance for cybersecurity threat modelling

The rapid adoption of AI-assisted coding is expanding the enterprise attack surface and introducing new attack vectors, increasing the importance of proactive threat modelling. While AI presents new risks, it can also serve as a powerful tool for security-proficient experts to accelerate the identification of vulnerabilities and reduce risk within codebases.

Traditional threat modelling often creates friction between security professionals and developers. To address the limitations of generic automation—which often produces high volumes of low-value findings—new approaches are focusing on credibility over raw output. VerSprite has introduced Fork, a continuous application threat modelling platform designed to prioritize findings based on real attacker behavior and business impact rather than merely increasing the speed of automated scans.