Insights from experts shaping secure development

Les responsables de la sécurité doivent repenser la valeur que les développeurs tirent de l'expérience d'apprentissage du code sécurisé et la manière de rendre le programme plus attrayant et, surtout, plus percutant. Dans ce blog, nous verrons comment intéresser les développeurs à la formation au code sécurisé grâce à un apprentissage plus pratique et à des intégrations avec leurs outils afin d'obtenir des résultats probants et de réduire les vulnérabilités introduites jusqu'à 53 %.

Découvrez comment vous pouvez réduire les vulnérabilités et les failles de sécurité grâce à la formation pratique sur la sécurité agile de Secure Code Warrior.

Les versions concernées de la bibliothèque curl sont sensibles à une vulnérabilité de débordement de mémoire tampon basée sur HEAP, liée à un problème existant avec le protocole proxy SOCKS5. Apprenez à trouver et à corriger ce type de vulnérabilité grâce à une mission jouable.

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.