Insights from experts shaping secure development

Post-quantum cryptography (PQC) is critical for protecting data from quantum computing threats. Learn how “harvest now, decrypt later” exposes risk and how developers can prepare for quantum-safe security.

Explore Enabler 2: Senior Leadership Sponsorship. Learn why active buy-in from the CIO, CTO, and CISO is vital to drive developer adoption and program credibility.

While development teams look to make the most of GenAI’s undeniable benefits, we’d like to propose a four-point foundational framework that will allow security leaders to deploy AI coding tools and agents with a higher, more relevant standard of security best practices. It details exactly what enterprises can do to ensure safe, secure code development right now, and as agentic AI becomes an even bigger factor in the future.

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.

Developer Risk Management is a holistic and proactive approach to application security, focused on code contributors rather than within the bits and bytes of the application layer itself.

In this research paper, Secure Code Warrior co-founders, Pieter Danhieux and Dr. Matias Madou, Ph.D., along with expert contributors, Chris Inglis, Former US National Cyber Director (now Strategic Advisor to Paladin Capital Group), and Devin Lynch, Senior Director, Paladin Global Institute, will reveal key findings from over twenty in-depth interviews with enterprise security leaders including CISOs, a VP of Application Security, and software security professionals.

This October, turn awareness into action. Make Cyber Awareness Month memorable for your developers with a high-impact, high-participation experience—led by Secure Code Warrior's Professional Services team.