Insights from experts shaping secure development

Début octobre, Apache a publié la version 2.4.49 pour corriger une vulnérabilité liée à la traversée de chemins et à l'exécution de code à distance, puis la version 2.4.50 pour corriger le fait que le correctif était incomplet. Nous nous sommes donné pour mission de démontrer les risques dans un environnement réel. Essayez-le dès maintenant.

Micha Martinez est analyste en cybersécurité et directeur de la photographie chez Nelnet. Lorsqu'il a été chargé de créer un programme de formation pour les développeurs sur le codage sécurisé, il a adopté des moyens créatifs pour impliquer son équipe. Nous avons été tellement impressionnés par la façon dont il gère son programme de formation au code sécurisé que nous nous sommes entretenus avec lui pour en savoir plus.

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.

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.