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AI-assisted coding tools like GitHub Copilot and ChatGPT are driving faster software development, but also introducing new vulnerabilities and security challenges. The rapid rise in AI-generated code is leading to a significant increase in reported vulnerabilities, overwhelming traditional security frameworks that struggle to keep up. To thrive in this new environment, security teams must move beyond simply finding issues to a contextual prioritization approach—assessing vulnerabilities based on business impact, environmental exposure, and threat likelihood. This strategy helps focus efforts on what's truly critical, enabling faster, smarter remediation and supporting development velocity without compromising security.

According to our research, for many organizations, determining who will fix a security issue takes as much time as actually fixing it. This means that half of the time allocated to meeting security SLAs is spent simply routing issues to the correct team. This lack of clarity creates friction at every stage of the remediation process, leading to inefficiencies, delays, and strained relationships between security and development teams.

In today’s agile development landscape, where cloud-based software is constantly evolving and deployed at unprecedented speed, traditional, manual threat modeling is no longer enough. As development teams iterate quickly and deploy in real-time, requirements and architecture changes rapidly, creating potential gaps in security that static threat models simply cannot keep up with. This has paved the way for continuous and agile threat modeling—a real-time approach to identifying, assessing, and mitigating risks early in the software lifecycle.

At Heeler, we’re not just building a product; we’re reshaping the future of application security. In today’s rapidly evolving digital landscape, the traditional approach to security has reached its limits. As applications grow more complex and threats become more sophisticated, the need for a unified security approach that integrates code, runtime, and business context is more critical than ever.

In the fast-paced world of software development, the adoption of agile methodologies and continuous delivery practices has revolutionized how applications are built, deployed, and maintained. In an agile environment, where code and cloud are constantly changing and new features are continuously being integrated, threat modeling needs to be just as agile and continuous. The idea is to ensure that security is built into the development process rather than bolted on as an afterthought.

Security prioritization has become an overwhelming challenge for organizations, as they try to manage an ever-expanding application footprint alongside an increasingly sophisticated threat landscape. In 2024 alone, we've seen a 30% year-over-year increase in reported CVEs through July, according to the Qualys Threat Research Unit. The rise of AI-assisted coding—often trained on the same vulnerable code we're trying to defend against—likely exacerbates this issue even further.