Insights from experts shaping secure development

보안 코딩에 대해 배울 때 개발자의 주된 동기는 무엇이며 성공적인 애플리케이션 보안 프로그램을 설계하고 구현하는 데 이를 어떻게 활용할 수 있을까요?

사이버 위협의 수가 계속 증가함에 따라 조직은 보안, 실용성 및 속도 사이에서 매일 균형을 유지하며 프로세스의 위험에 노출되고 있습니다.

사이버 위협이 계속 증가하는 상황에서 코더들이 한 걸음 더 나아가고 있습니까?가장 중요한 개발자인 시큐어 코딩의 인적 요소가 연결된 세상을 보호하는 데 자신의 역할을 할 준비가 되었나요?이 질문에 답하기 위해 Secure Code Warrior가 Evans Data Corp와 함께 수행한 보안 코딩, 보안 코드 관행 및 보안 운영에 대한 개발자의 태도에 대한 최근 연구에서 얻은 몇 가지 인사이트를 살펴보겠습니다.

Kamer van Koophandel shares how it embedded secure coding into everyday development through role-based certifications, Trust Score benchmarking, and a culture of shared security ownership.

See how Paysafe's partnership with Secure Code Warrior led to a 45% boost in developer productivity and a major reduction in code vulnerabilities.

DigitalOcean's use of Secure Code Warrior training has significantly reduced security debt, allowing teams to focus more on innovation and productivity. The improved security has strengthened their product quality and competitive edge. Looking ahead, the SCW Trust Score will help them further enhance security practices and continue driving innovation.

Secure code should be grounded more in concepts like secure by default and secure by design than by “spot the vuln” thinking. Matias Madou shares his experience in secure coding training and the importance of teaching critical thinking. He also discusses why critical thinking is so closely related to threat modeling and how LLMs can be a tool for helping developers get beyond the superficial advice of, “Think like an attacker.”

Organizations are at an inflection point driven by the explosive adoption of AI, which promises significant changes in how businesses operate. That leaves CISOs on unsteady ground. As the gatekeepers of their organization’s data and access, they must ensure the security of the enterprise. However, the prospects of a headlong charge into wide-ranging, and possibly unchecked, use of AI could create a flood of security issues that many CISOs, under their current organizational structures, aren’t equipped to handle.

Security leaders and developers alike are already acutely aware that AI coding assistants and agentic agents can introduce vulnerabilities into the code they generate. A recent study unveiled another critical concern to keep them up at night — LLMs used for making iterative code improvements may introduce new vulnerabilities over time, even when explicitly asked to make code more secure.

AI risk doesn't stop at engineering. Get the one-pager on Citizen AI — build AI literacy and safe habits across your whole workforce.

From AI autocomplete to autonomous agents—explore how software development is evolving and what it means for security, governance, and your team.

Gartner named SCW twice in the 2026 Hype Cycle for Secure Software Engineering. Here's why it matters for AI-driven development.