Insights from experts shaping secure development

코딩 문제가 문제의 일부일 수 있지만 비즈니스 로직 오류는 대부분 앱을 처음 만들 때 설계 결함이나 잘못된 논리적 가정으로 인해 발생합니다.

사이버 보안 분야에서 우리는 종종 사냥꾼과 같습니다.우리의 눈은 지평선에 단단히 고정되어 다음 취약점을 찾아냅니다.하지만 이러한 미래 지향적인 초점은 전반적인 보안 인식을 약화시키는 놀라운 결과를 초래할 수 있습니다.

웹 사이트와 애플리케이션에서는 사용자가 이메일을 사용하여 애플리케이션을 통해 피드백 및 기타 다양한 정보를 보낼 수 있도록 하는 것이 일반적입니다.그리고 대부분의 사람들은 잠재적인 보안 위험 측면에서는 이에 대해 생각조차 하지 않습니다.

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.

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.

Government bodies are trying to develop rules and regulations for safe AI use, but enterprises can't afford to wait. They need to address the risks now.

See how 16 leading AI models actually code, scored across 11 real-world frameworks and 1,760 codebases — the framework matters as much as the model.

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.