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

Post-Quantum Cryptography: Quantum Computers Will Break Today’s Encryption – Are You Ready?
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.
Enabler 2: Senior Leadership Sponsorship
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.

Observe and Secure the ADLC: A Four-Point Framework for CISOs and Development Teams Using AI
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.

Driving Actionable Awareness: FINRA's Push For Super-Secure Developers
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Creating a revolutionary security certification experience
Learn how they created an in-house technology education initiative, aimed at supporting thousands of employees to learn practical, cutting-edge skills in a number of disciplines, including machine learning and cybersecurity.
Beyond Compliance: Motorola Solutions Drives Winning Security Culture
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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.
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.








