Insights from experts shaping secure development
Access expert content on secure coding, AI governance, and software risk management.

Driving Meaningful Success for Enterprise Secure-by-Design Initiatives
Our latest research paper, Benchmarking Security Skills: Streamlining Secure-by-Design in the Enterprise is the result of deep analysis of real Secure-by-Design initiatives at the enterprise level, and deriving best practice approaches based on data-driven findings.

Deep Dive: Navigating the Critical CUPS Vulnerability in GNU-Linux Systems
Discover the latest security challenges facing Linux users as we explore recent high-severity vulnerabilities in the Common UNIX Printing System (CUPS). Learn how these issues may lead to potential Remote Code Execution (RCE) and what you can do to protect your systems.
How exceptional CISOs are igniting the security fire in their development team
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Kamer van Koophandel Sets the Standard for Developer-Driven Security at Scale
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.
Going for Gold: Soaring Secure Code Standards at Paysafe
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 Decreases Security Debt with Secure Code Warrior
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.

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.
Trust Agent:AI - Secure and scale AI-Drive development
AI is writing code. Who’s governing it? With up to 50% of AI-generated code containing security weaknesses, managing AI risk is critical. Discover how SCW's Trust Agent: AI provides the real-time visibility, proactive governance, and targeted upskilling needed to scale AI-driven development securely.

The Power of OpenText Application Security + Secure Code Warrior
OpenText Application Security and Secure Code Warrior combine vulnerability detection with AI Software Governance and developer capability. Together, they help organizations reduce risk, strengthen secure coding practices, and confidently adopt AI-driven development.

Secure Code Warrior corporate overview
Secure Code Warrior is an AI Software Governance platform designed to enable organizations to safely adopt AI-driven development by bridging the gap between development velocity and enterprise security. The platform addresses the "Visibility Gap," where security teams often lack insights into shadow AI coding tools and the origins of production code.






