Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

he video outlines how Cyberhaven's Data Security Posture Management (DSPM) provides a continuously updated, context-aware inventory of data at rest.

AI changed work, Cyberhaven protects it. Cyberhaven exists to protect the way enterprises actually work today: with AI agents accessing, moving, and acting on data across every workflow. In this video, we share Cyberhaven's mission and our stance on data security for the agentic enterprise.Traditional data security, built for files at rest, wasn't built for AI agents acting at machine speed. Cyberhaven traces data through its full lifecycle and adapts protection as context changes, so security keeps pace with how work actually happens.

Turn every analyst into a power user. Security investigations shouldn't take 45 minutes of tab-switching and manual querying. In this 20-minute walkthrough, Cyberhaven Director of Product Management Dave Stuart demos the Analyst Plugin, and shows how a single conversation replaces the queue.

In this video, you will learn the five questions every data leak investigation must answer to be defensible — what the data is, where it originated, who accessed it, where it spread, and the fastest containment step — and why the visibility gap in most security stacks makes those questions impossible to answer instantly. You will also learn how combining DSPM baseline inventory with real-time data lineage replaces the high-stress scramble with surgical containment and audit-ready proof, so you move from "I think we're safe" to "here is the proof.".

In this video, you will learn why locking down source systems like your CRM, HR database, and S3 buckets leaves your real risk surface exposed, how one regulated file fragments into CSV exports, screenshots, scripts, and AI prompts that shed their security context at every hop, and why both legacy DLP and traditional DSPM fail to act on these invisible derivatives. You will also learn how lineage-focused DSPM tracks the provenance of the data payload itself — every copy, paste, and save — so you can enforce policy on fragments instead of guessing from patterns.

Autonomous AI agents are running on enterprise endpoints right now, accessing files, processing sensitive data, and executing actions outside the visibility of most security programs. This is Part 1 of Cyberhaven's four-part AI Security product launch series. What this video covers: Most AI security tools were built for browsers and SaaS apps. They cannot see agents operating at the OS level, coding assistants running in IDEs and CLIs, or MCP servers executing in the background. Cyberhaven's AI Security platform was built to close that gap.

Security teams cannot govern what they cannot see. This is Part 2 of Cyberhaven's four-part AI Security product launch series, focused on Shadow AI Discovery and how Cyberhaven automatically inventories every AI app and agent running across your organization.

Visibility without enforcement is just an alert backlog. This is Part 4 of Cyberhaven's four-part AI Security product launch series, covering how Cyberhaven enforces risk-based controls at the data level, not the tool level, using Data Lineage as the foundation.

Knowing an AI tool exists is not the same as knowing what it did with your data. This is Part 3 of Cyberhaven's 4-part AI Security product launch series, covering Agentic AI Visibility and AI Risk IQ, Cyberhaven's evidence-based risk scoring system for every AI app and agent in your environment.

In this video, you will learn why agentic browsers like ChatGPT Atlas, Perplexity Comet, and Arc have turned the browser into a double agent inside your enterprise, how shadow adoption is bypassing MDM and endpoint controls in days, and why indirect prompt injection creates an attack surface your file-based DLP cannot see. You will also learn how data lineage replaces noisy content inspection with origin-and-destination tracking, so you can stop the leak without blocking the tools your business depends on.