Insights from experts shaping secure development

Les attaques par injection, tristement célèbre roi des vulnérabilités (par catégorie), ont perdu la première place au profit d'une violation du contrôle d'accès, en tant que pire des pires, et les développeurs doivent en tenir compte.

Les développeurs font partie de ceux qui maîtrisent le mieux le code, en plus des configurations de sécurité et du contrôle d'accès. Leurs compétences en matière de sécurité doivent être renforcées, et pour atteindre les normes élevées définies par le NIST, une structure de cours pratique pourrait bien être le moyen le plus efficace d'y remédier, en particulier pour les grandes cohortes de développement.

Tout comme les logiciels Web, les API et les appareils mobiles, le code vulnérable des systèmes embarqués peut être exploité s'il est découvert dans la nature par un attaquant.

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.

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.

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.

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.

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.