Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A leading voice in cybersecurity, Gina Yacone is a trusted advisor to senior security leaders, guiding them through emerging trends and recommending strategies to strengthen defenses. She was also recently named Cybersecurity Woman Volunteer of the Year 2024. As regional and advisory CISO at the elite technology consultancy Trace3, she also participates in the Trace3 AI Center of Excellence (CoE) Champion Program, keeping her at the forefront of AI and security innovation.

Unlike traditional software, where testing is relatively straightforward, Gen AI apps introduce complexities that make testing far more intricate. This blog explores why traditional software testing methodologies fall short for Gen AI applications and highlights the unique challenges posed by these advanced technologies.

By James Rees, MD, Razorthorn Security Times must change (and always will) and nowhere is this more true than in the realm of technological advancement. Thirty years ago, the technological landscape was vastly different from what we have today and technological change has outpaced Moore’s Law for some time now. Information security must keep pace with these advancements. This has become especially true with the advent of AI.

Worried about GitHub Copilot’s security and privacy concerns? Learn about potential risks and best practices to protect yourself and your organization while leveraging AI.

After speaking to a wide spectrum of customers ranging from SMBs to enterprises, three things have become clear: Add that together, and we get Shadow AI. This refers to AI usage that is not known or visible to an organization’s IT and security teams. Shadow AI comes in many forms, but in this blog we’ll stick to a discussion of Shadow AI as it pertains to applications. Application security teams are well aware that AI models come with additional risk.