Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Why Legacy DLP Fails: The Hidden Data Risks You Can't See

Legacy data loss prevention (DLP) tools were built for a different era—a time when data sat safely behind firewalls and security meant scanning files for keywords. But today, data moves across cloud apps, personal devices, and collaboration tools faster than ever. Legacy DLP simply can’t keep up. In this video, we break down: If your organization is still relying on outdated DLP systems, it’s time to evolve. Because what your tools can’t see will hurt you.

Why Traditional DLP Fails in the Age of Cloud and Collaboration Tools

DLP emerged at a time when corporate IT environments were relatively straightforward. Employees worked primarily from corporate offices, data resided in on-premises servers, and communications happened through company-managed email systems and file shares. Traditional DLP solutions were designed to thrive in this environment.

The Evolution of Data Loss Prevention: From Perimeter to Insider Risk

Data loss prevention, or DLP as most of us know it, began as a strategy to control how information was stored and moved within organizations. Ultimately the goal was to prevent data from leaving. The premise was simple – identify where sensitive data was stored, define what could or couldn’t happen to it, and enforce those rules through network and endpoint controls. These early DLP tools relied heavily on static content inspection and then blocking or alerting based on pre-configured rules.

[Webinar] Protecting Innovation: Use AI Securely While Safeguarding Data

AI use at work has exploded—nearly every employee is experimenting with AI tools. But behind the productivity gains lies a major blind spot: 71% of AI apps in use today were not approved by IT or security teams. These tools are flying under the radar, and they’re sending sensitive company data to unknown third parties. Cyberhaven Labs analyzed AI tool usage across millions of real-world events and found widespread shadow AI, uncontrolled data exposure, and risky behavior by employees—often without realizing it. The implications are clear: you can’t secure what you can’t see.

Cyberhaven Spring 2025 Product Launch

AI Took Off. We’re Launching the Controls. Discover how Cyberhaven is rewriting the rules of AI data security. Our newest innovation is too big to call a feature — it’s a new frontier. AI changed everything... fast. Productivity soared, but so did risk. Employees embraced AI, and data raced across tools without oversight. The question isn’t if your organization is using AI — it’s how much risk it’s exposing in the process.

Cyberhaven Winter 2025 Product Launch

Join us for the exclusive unveiling of Cyberhaven's next evolution, hosted by our leadership & product teams. We're (once again) changing the way companies visualize, detect, and protect their data. Be the first to see what's next. Imagine if You Could: Discover how Cyberhaven is setting the gold standard for the future of data security in the age of AI.

Cyberhaven Spring 2025 Product Launch

AI Took Off. We’re Launching the Controls. Discover how Cyberhaven is rewriting the rules of AI data security. Our newest innovation is too big to call a feature — it’s a new frontier. AI changed everything... fast. Productivity soared, but so did risk. Employees embraced AI, and data raced across tools without oversight. The question isn’t if your organization is using AI — it’s how much risk it’s exposing in the process.

Security for AI: enabling secure AI adoption across the enterprise

AI is transforming productivity across every industry—from marketing and design to legal and engineering. But while employees rush to embrace tools like ChatGPT, Gemini, and Microsoft Copilot, many are using other tools without oversight from IT or security. As this grassroots usage grows, so does the volume—and sensitivity—of data flowing into AI tools.