Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Fall 2025 Product Launch Teaser

Cyberhaven is excited to introduce Data Security Posture Management, now in Early Access. Existing DSPMs helped security teams inventory sensitive data across cloud repositories, but they stop short of delivering meaningful protection. They identify what data organizations have and where it resides, but not who owns it, where it came from, or how it’s being used. As data moves through modern organizations, copied between applications, repos, and endpoints, summarized into AI tools, and shared externally, those systems lose visibility and therefore their ability to protect data.

Introduction to Linea AI by Cyberhaven

Resolve incidents 5x faster, detect 40% more critical incidents, and reduce future incidents by 90% with Linea AI by Cyberhaven. Linea AI thinks like the smartest security analyst, precisely spotting insider risks across billions of workflows and every piece of data. It understands how people work the way a human would, but it never loses focus and can apply human-like insight at an incredible scale.

Data Security Posture Management, Early Access

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.

Browser Agent Security Risk - ChatGPT Atlas Corporate Adoption Trends

Last Tuesday, October 21st, OpenAI released ChatGPT Atlas, an AI-powered browser that allows users to interact with ChatGPT directly from any browser tab. Throughout last week, the Cyberhaven Labs team tracked its adoption in corporate environments and actively investigated its security vulnerabilities.

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.

PurePlay 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.

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.

What is Data Lineage?

In this video, we break down the concept of data lineage — a way to track how data moves, changes, and is used across your organization. Data lineage provides visibility into the lifecycle of sensitive information, from where it originates to where it flows, and who interacts with it. Understanding data lineage helps organizations improve security, ensure compliance, and reduce insider risk. Watch now to learn what data lineage is, why it matters, and how it helps protect your most valuable data.

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.