Insights from experts shaping secure development
Access expert content on secure coding, AI governance, and software risk management.
Gartner Security & Risk Management Summit 2026
Excited to sponsor the Gartner Security & Risk Management Summit in London, September 22–24, 2026! Come connect with our team to see how Secure Code Warrior is helping organizations govern AI-generated code and build lasting security skills across the SDLC. See you there!
The Future of AI Software Governance Is Built on Strong Partnerships
Discover why Secure Code Warrior is becoming a channel-first company and how trusted partners help organizations adopt AI Software Governance securely and at scale.
Citizen AI by Secure Code Warrior: Build an AI-Ready Workforce
Secure Code Warrior's AI literacy program for non-developer employees.
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Why most CISOs are navigating AI adoption blindfolded (and how they can remove it)
Today, Secure Code Warrior issued an all-new white paper covering a prescriptive, directional AI adoption model that security leaders can use to identify their adoption stage and make real progress in bringing the AI security risks within their organization under control.
ASRG's push for automotive software security
Explore this comprehensive case study to learn more about how they utilized Secure Code Warrior's tournaments to engage developers, increase awareness of key vulnerabilities affecting automotive software, and gain metrics across multiple languages and frameworks.
Application Security @ NAB | Gamified Security Training: The Key to Scalable Developer Growth
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Security Boulevard: Threat Modeling with AI: A Developer-Driven Boon for Enterprise Security
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.
The AI Journal: Understanding LLM Coding Personalities Is Now Key to Developer Risk Management
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.
SecurityBrief: The security challenges in AI-assisted software development
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.
Citizen AI by Secure Code Warrior
AI risk doesn't stop at engineering. Get the one-pager on Citizen AI — build AI literacy and safe habits across your whole workforce.
Understand how AI is transforming software development—and how security must evolve with it.
From AI autocomplete to autonomous agents—explore how software development is evolving and what it means for security, governance, and your team.