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Insights from experts shaping secure development
Access expert content on secure coding, AI governance, and software risk management.
Gartner Security & Risk Management Summit 2026
Excited to sponsor the Gartner Security & Risk Management Summit in London, September 22–24, 2026! Come connect with our team to see how Secure Code Warrior is helping organizations govern AI-generated code and build lasting security skills across the SDLC. See you there!
MVC 요청/매처 스프링 취약점 자세히 살펴보기
2023년 3월 20일, 스프링 시큐리티 어드바이저리는 내부적으로 발견된 취약점인 CVE-2023-20860 취약점을 언급하는 블로그 게시물을 게시했습니다.'MVCMatchers' 사용과 관련된 액세스 제어 문제라는 점을 제외하고 자세한 정보는 공개되지 않았습니다.Spring 개발자들이 이 문제를 해결했으며 버전 업데이트가 권장됩니다.Secure Code Warrior에서는 보안이 주안점이기 때문에 MVCrequestMatchers의 취약점을 자세히 살펴보고 핵심 문제가 어디에 있는지 알아보기로 했습니다.
Kamer van Koophandel Sets the Standard for Developer-Driven Security at Scale
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.
Going for Gold: Soaring Secure Code Standards at Paysafe
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 Decreases Security Debt with Secure Code Warrior
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.
Security Boulevard: Threat Modeling with AI: A Developer-Driven Boon for Enterprise Security
Developers have long struggled to truly claim a seat at the table in traditional threat modeling programs, but with the right skills, they have the opportunity to wield AI responsibly to seriously cut risk and rework in their codebase.
The AI Journal: Understanding LLM Coding Personalities Is Now Key to Developer Risk Management
AI-generated code may be “made by machine”, but taking a cookie-cutter approach to securing that code would fall well short of mitigating the vulnerabilities LLMs can introduce. Organizations need to establish precise security reviews, with human developers anchoring the process to implement effective security controls while also managing the specific coding temperament of each LLM used. AI-generated code must undergo the same personalized risk assessments as code written by human developers.
SecurityBrief: The security challenges in AI-assisted software development
s artificial intelligence (AI) tools become more widely used in the software development process, their impact on security is becoming clearer. According to recent research, nearly 70% of organisations have discovered vulnerabilities caused by AI tools while one in five have experienced a serious incident as a result of those vulnerabilities.
Citizen AI by Secure Code Warrior
AI risk doesn't stop at engineering. Get the one-pager on Citizen AI — build AI literacy and safe habits across your whole workforce.
Understand how AI is transforming software development—and how security must evolve with it.
From AI autocomplete to autonomous agents—explore how software development is evolving and what it means for security, governance, and your team.