Insights from experts shaping secure development

Les outils AppSec ne sont pas utilisés comme on aurait pu s'y attendre pour plusieurs raisons. Il s'agit moins des outils et de leurs fonctionnalités que de la manière dont ils s'intègrent à un programme de sécurité dans son ensemble.

En ce qui concerne l'apprentissage du codage sécurisé, quelles sont les principales motivations des développeurs et comment les exploiter pour concevoir et mettre en œuvre un programme de sécurité des applications efficace ?

Alors que le nombre de cybermenaces ne cesse de croître, les entreprises font des compromis quotidiens entre sécurité, praticité et rapidité, s'exposant ainsi à des risques.

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.

The doomsayers are, so far, losing the argument. The panic around AI replacing humans has been countered with a new narrative: “Let AI redefine your job rather than replace it.” According to a recent survey from Stack Overflow, 44% of developers are either using or planning to use AI tools—even though just 3% “highly trust” the accuracy of the results. Twice as many (6%) say they highly mistrust AI due to security concerns and inaccuracy.

While it’s true that AI can help save some time for overworked programmers, the future will likely be one where humans and AI work together, with trained personnel in charge of applying critical thinking and precision skills to ensure all code is as secure as possible.

CISA’s Secure-By-Design guidelines, which call for shifting the responsibility for secure coding back to those making the devices, software and applications people increasingly rely on, and trust with sensitive data. The program defines what many frustrated technology users already know, that the industry needs a new model for cybersecurity in which vulnerabilities are fixed long before they reach the public.

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.