Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For years, the cybersecurity community has discussed the theoretical risks of artificial intelligence. We’ve imagined biased algorithms and adversarial attacks, but these conversations usually stayed hypothetical. That era is over. It’s time to move beyond the theory and into the practical “how-to” of finding and exploiting vulnerabilities in AI systems. To execute this, the new OWASP AI Testing Guide (AITG) is indispensable.

Generative AI is reshaping how software is made, secured, and scaled. At Snyk’s Lighthouse event in Silicon Valley, leaders from engineering, security, and platform teams gathered to explore one big question: How do we build AI-powered systems that move fast, without breaking trust? For many, that future is already here — 60% of organizations at the Summit reported building agentic apps internally. The answers weren’t just technical. They were cultural. Organizational. Strategic.

Tech companies love a good framework, especially ones that promise structure, transparency, and alignment with internal standards. Zoom’s Vulnerability Impact Scoring System (VISS) is one of those. It’s designed to translate internal security policies into a scoring model that supports impact-based decision making, particularly for bug bounty programs and external disclosure workflows. On paper, that sounds useful. But in practice, it doesn’t scale.

When we talk about healthcare today, it’s impossible not to consider application security. As healthcare providers increasingly lean on digital solutions to deliver patient care, they are creating an explosion of healthcare data requiring protection to ensure its confidentiality, integrity, and availability.

As the Chief Information Security Officer at Snyk, my primary role is to ensure the security and integrity of our products, our systems, and our customers' data. But my responsibility extends beyond our walls. It involves championing a vision for a more secure digital world—a vision I am proud to say we share with the U.S. Cybersecurity and Infrastructure Security Agency (CISA).

The recent revelation of a critical vulnerability in Base44, a prominent vibe coding platform, has spotlighted the intricate relationship between innovation and security in AI-assisted development. Researchers at Wiz uncovered a flaw in the platform that allowed unauthorized access to private enterprise applications, exposing sensitive data and raising urgent questions about the security of vibe coding practices.

In this article Chief Information Security Officers (CISOs) face the daunting task of balancing technical cybersecurity risks with the financial realities of their organization. One critical component in this balancing act is the use of vulnerability scoring systems, in particular, the CVSS score. This article provides a detailed guide on how to translate CVSS scores into tangible financial impact estimates using proven methods of risk quantification.