Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

For most CISOs, data loss prevention (DLP) has long been a familiar acronym. It’s a category of security technology that has been around for more than a decade, often associated with compliance and the need to keep regulated data under control. Yet while the concept sounds straightforward—preventing sensitive data from leaving the organization—the reality is that modern DLP platforms are far more sophisticated than their early predecessors.

The speed of software development today is driven by fierce competition and the constant demand for innovation. Organizations are launching software faster than ever to keep up with the market and drive growth. This need for speed has led to several key trends: These trends introduce a critical dilemma: How do you balance speed vs. trust? While fast releases are essential to meet market and user demands, sacrificing trust for speed can lead to severe business repercussions.

There are two enormous cybersecurity events each year in the United States: RSA Conference and the week in Vegas that is so full of conferences, summits, and ancillary events that it’s simply known as “Hacker Summer Camp.” From Security BSides Las Vegas to Black Hat and DEF CON, it takes the fortitude of a camel to survive the desert heat and the late nights.

Over the last year, I’ve spent countless hours with CISOs, CTOs, and security architects talking about a new wave of technology that’s changing the game faster than anything we’ve seen before: Agentic AI and Model Context Protocol (MCP) servers. If you think AI is still in the “cool demos and pilot projects” stage, think again. We’re already seeing autonomous agents reasoning, remembering, and taking actions in live production environments.

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.

As CISOs, you’ve invested heavily in desktop security, built out Zero Trust architectures, and hardened your perimeter. But there’s a critical gap many are still leaving exposed: mobile devices and the human behind the screen. In a world where your workforce runs on smartphones, overlooking mobile security is no longer an option.