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With a TraceCyberhaven Engineering

With a Trace

Published date:
12/18/2025

Why Data, Not the Perimeter, Should Be the Core of Your Security Strategy

For decades, enterprise security strategy revolved around a simple assumption: if you could build a strong enough perimeter around your network, everything inside would remain safe. Firewalls, intrusion prevention systems, and VPNs became the bedrock of corporate defenses. The perimeter was the castle wall, and sensitive data lived safely inside.

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12/2/2025

How Generative AI is Changing the DLP Landscape

Generative AI has revolutionized productivity, but it has also introduced a new class of data risk that legacy DLP tools simply can’t see. From engineers pasting source code into ChatGPT to marketers rewriting strategy docs, sensitive IP is leaving the browser through "Shadow AI" channels daily. Learn why traditional pattern matching fails against LLMs and how a data lineage approach secures AI usage without halting innovation.

Security best practices
11/21/2025

How AI Companies Can Use Data Lineage To Stop IP Theft — And Win When It Goes To Court

11/20/2025

AI Is the Future of DLP—Here's What That Actually Means

Artificial intelligence (AI) has become the defining technology of our era, transforming industries from healthcare to finance to manufacturing. In the world of cybersecurity, AI is no longer just a buzzword—it's rapidly becoming the backbone of how organizations defend themselves against threats that evolve faster than human analysts can keep up. Nowhere is this more evident than in data loss prevention (DLP).

Security best practices
11/18/2025

Insider Threats in the Age of AI: What Security Teams Need to Know

Artificial intelligence has gone from buzzword to business tool almost overnight. Employees are rapidly adopting platforms like ChatGPT, Gemini, and Copilot to draft content, analyze data, brainstorm code, and accelerate productivity. But as AI becomes embedded in everyday workflows, a new category of insider threat is emerging—one that is harder to detect, harder to classify, and potentially more damaging than anything security teams have faced before.

Industry news
11/14/2025

AI-orchestrated espionage is here. Your data controls decide what happens next.

Anthropic has just disclosed what appears to be the first fully documented case of AI-orchestrated cyber espionage. A Chinese state-backed group used Claude Code to automate most of a campaign targeting approximately 30 organizations across the tech, finance, chemicals, and government sectors. In several cases, they got in and stole sensitive data.

Cyberhaven news
11/4/2025

Data Security Posture Management

Today's data sprawls across the cloud, on-prem, and endpoints. Data lives everywhere, but the biggest challenge isn't just knowing where data resides across the organization. Security teams must understand what the data represents, identify what’s at risk, and protect it in real time.

10/14/2025

Shadow AI and the New Data Defense Paradigm: Insights from Our Data Defense Forum

Last month, we brought together some of the brightest minds in cybersecurity for our Data Defense Forum event. As someone who's been in the trenches of data security for years, I walked away from these conversations with a renewed sense of urgency and optimism about where we're headed.

Industry news
10/9/2025

Pure‑Play DSPM Vendors: What’s their second act?

CSPM tools thrived by making cloud posture issues easy to find, but posture alone didn’t stop breaches. The market evolved into CNAPP – uniting posture, runtime, identity, and shift‑left – to deliver protection, not just visibility. DSPM is on the same trajectory: discovery and classification at rest are necessary but insufficient, especially as AI fragments data into shareable snippets that evade label‑centric controls. The next act for DSPM requires lineage‑driven protection anchored on proven endpoint telemetry, correlated across cloud and SaaS, with real‑time coaching for people and agents.

9/9/2025

What Every CISO Should Know About How DLP Actually Works

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. Understanding how these platforms actually work is critical for CISOs who need to make informed decisions about deploying, tuning, and operationalizing them across their organizations.

9/5/2025

The Hidden Risk in Enterprise AI, and the Smarter Way to Safeguard Data

AI exploded into the workplace overnight, reshaping how we work. Today, nearly every employee is experimenting with tools to move faster and think bigger. However, that acceleration comes with risk. According to Cyberhaven Labs’ latest research, nearly three-quarters of AI apps in use pose high or critical risks, and only 16% of enterprise data sent to AI ends up in enterprise-ready apps. The rest flows to personal or unvetted tools. This blog post distills the key insights from Cyberhaven’s on-demand session, featuring Cameron Galbraith (Senior Director of Product Marketing) and Dave Stuart (Director of Product Management), on how to enable AI safely without slowing innovation.

Product update
7/29/2025

Reimagining Data Security: Four New Capabilities That Make Protection Smarter, Faster, and Easier

Enterprise data has become nomadic. What once lived safely behind corporate firewalls now travels across dozens of cloud applications, gets copied into collaborative documents, flows through AI tools, and transforms as employees work from coffee shops, home offices, and airport lounges.

Cyberhaven news
7/14/2025

How Cyberhaven and Jamf Partner to Deliver Unmatched Data Security

Apple devices have become essential tools for the modern workforce. From engineers coding on MacBooks to designers creating campaigns on iMacs, macOS devices are embedded into daily workflows across industries. However, as Apple adoption continues to grow in the enterprise, so does the challenge of protecting sensitive data that moves across these devices every day.

7/11/2025

Fireside Chat: Breaking Free from Legacy DLP

There’s a silent frustration building inside security teams today. It’s the fatigue of defending critical data with tools that can’t keep up. The friction of investigating endless false positives. The anxiety of not knowing what sensitive data is actually doing across your environment. And the sinking realization that despite massive investments, DLP tools are failing at the one thing they were designed to do–prevent data loss.

7/9/2025

Lineage Over Labels: A Better Way to Protect Data

Labels don’t protect what they can’t see—especially in a world where data moves, morphs, and escapes traditional boundaries. Static tags and keyword scans fall apart as sensitive information flows across apps, devices, and formats. Data lineage solves this by tracing how data is created, modified, and shared—giving security teams the context to spot threats, reduce false positives, and enforce smarter, real-time protection without disrupting work.

7/8/2025

5 Reasons You Can’t Afford to Ignore False Positives

False positives are killing your DLP. In this overview, we reveal how legacy tools create noise, drain productivity, and leave real threats undetected. Discover the 5 hidden risks of outdated DLP—and why a smarter, context-aware approach is the key to protecting data without slowing down your business.

7/7/2025

How Legacy DLP Leaves You Exposed

Legacy DLP tools are blind to how data moves in today’s cloud-first world—leaving gaps attackers exploit. From shadow IT and SaaS sprawl to insider threats and misused personal devices, outdated solutions miss the subtle, high-risk behaviors that matter most. True protection requires context-aware visibility, behavioral insight, and data lineage that follows sensitive information everywhere it goes—not just where it started.

7/1/2025

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.

Cyberhaven news
5/13/2025

The Next Chapter in Cyberhaven's Journey

Today, I'm both honored and excited to share that I've stepped into the role of interim CEO at Cyberhaven, as Howard Ting transitions to our Board of Directors.

Product update
4/29/2025

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. Companies now face a critical challenge: how to capture the enormous potential of AI while managing the risks it can introduce to their data.

Industry news
4/23/2025

AI Usage at Work Is Exploding — But 71% of Tools Put Your Data at Risk

As AI becomes deeply integrated into critical business operations and adopted by increasing numbers of departments and employees, the volume and sensitivity of data flowing into these systems has grown exponentially. Companies now face a dual challenge: harnessing AI's potential while managing the substantial data risks it introduces.

Guide

The 15 Top Data Detection and Response UseCases

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