Insights from experts shaping secure development

Las herramientas de análisis estático y pruebas de penetración (más conocidas como SAST) son solo una parte del proceso general para mitigar los riesgos de seguridad, ya que funcionan de forma bastante independiente de lo que hacemos nosotros, ¡hasta que el código nos devuelva para corregirlo, por supuesto!

Learn how Sensei can identify a coding pattern, and automatically generate a private constructor to make it impossible to instantiate the class.

Ya sea que la incomodidad provenga de las incógnitas de una nueva forma de trabajar, de un poco de desconfianza o quizás de no creer en el trabajo remoto, me parece que las empresas que se resisten a ello tienden a quedarse atrás en términos de atraer a los mejores talentos, mantener el alcance global y, francamente, adaptarse a los tiempos.

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.

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.

According to research company Forrester[1], the tech debt for 75% of organisations will increase to a moderate or high level during this year, due to the rapid expansion of AI usage across a range of areas including software development.

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.