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By Cyberhaven
Clinicians are pasting patient summaries into ChatGPT to draft discharge instructions. Billing staff are uploading claim data to AI writing tools to speed up appeals letters. Nurses are using consumer AI assistants to look up drug interactions between patient visits. None of this was approved by the security team, and most of it would surprise the compliance officer.
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By Cyberhaven
AI agents are connecting to enterprise systems right now. Whether a developer wired up Claude to an internal Confluence instance, a vendor shipped an agentic workflow that calls the CRM, or an employee enabled a browser-based AI assistant that reads email, Model Context Protocol (MCP) is rapidly becoming the integration layer between large language models (LLMs) and corporate data. Most security teams have no visibility into any of it.
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By Cyberhaven
HR teams manage every stage of the employee lifecycle, from hiring and onboarding to performance management and offboarding. Security teams manage data access, behavioral monitoring, and incident response. Insider risk lives at the intersection of both. When HR and security operate independently, the gaps between them are exactly where data loss happens, and the moments of highest exposure are almost always HR events, such as a resignation submitted, a role change processed, a termination decision made.
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By Cyberhaven
Most enterprise security programs were built around a simple assumption, not invalid assumption that data moves when a person decides to move it. AI agents have broken that model, and now act autonomously, reading files, calling APIs, executing code, and transferring data across systems without waiting for a human to approve each step. Many of these agents were never sanctioned by IT or security.
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By Cyberhaven
Employees are feeding sensitive data into AI tools at a pace most security teams did not anticipate. Source code goes into coding assistants. Customer records get pasted into ChatGPT to draft emails. Confidential contracts land in Gemini for summarization. According to Cyberhaven Labs research, 39.7% of the data employees share with AI tools is sensitive, and the volume is accelerating as AI adoption spreads from individual contributors to entire workflows.
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By Cyberhaven
Most data security posture management (DSPM) programs don't fail because the technology is wrong. They fail because of execution gaps, from incomplete data inventory to misclassified data at scale to fragmented cloud environments and teams stretched too thin to act on findings. However, each of these problems is predictable, and each has a known fix.
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By Cyberhaven
Security architects who understood the large language model (LLM) risk two years ago are now confronting a more complex problem. The enterprise AI stack has split into two distinct architectural patterns, retrieval-augmented generation (RAG) and agentic AI, and the security posture required for each is fundamentally different. Conflating them is how programs end up with coverage gaps.
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By Cyberhaven
Most organizations have an acceptable use policy for AI tools. Very few have controls that actually enforce it. The gap between what the policy says and what security teams can detect is where insider risk lives when it comes to large language model (LLM) usage.
In an era where AI accelerates both innovation and adversarial capability, security leaders are confronting a difficult reality: traditional approaches to cyber defense are no longer sufficient. Cyberhaven’s Office of the CISO is responding with a forward-looking strategy designed not simply to keep pace with emerging threats, but to fundamentally redefine enterprise readiness in a post-Mythos world.
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By Cyberhaven
Security teams that deployed legacy DLP years ago built something real. The rules fire. The alerts go out. Compliance boxes get checked. The problem is not that those programs stopped working. It is that the threat moved, and the architecture did not. Agentic AI has introduced a class of data movement that legacy DLP was never designed to govern: autonomous, continuous, multi-step, and operating at machine speed across systems that static rules cannot enumerate in advance.
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By Cyberhaven
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.
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By Cyberhaven
In this video, you will learn why static domain-blocking strategies fail against the modern Shadow AI ecosystem, how Generative AI wrappers, browser extensions, and personal accounts bypass corporate firewalls without triggering an alert, and why network-layer inspection cannot distinguish proprietary code from public Stack Overflow snippets. We break down the limitations of traditional DLP at the clipboard layer, explain how data lineage replaces application allow-lists, and show how the "Glass House" model lets enterprises enable AI productivity while strictly gating sensitive data movement.
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By Cyberhaven
In this video, you will learn how lightweight OS-level instrumentation binds lineage metadata to clipboard content the moment data is copied, how that tag survives edits, reformatting, and translation across applications, and how provenance-based policy replaces pattern matching with precision rules tied to the actual source of the data. You will also learn how pairing network tools with a browser extension captures user intent before encryption, eliminating the alert fatigue that buries real risk in noise.
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By Cyberhaven
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.
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By Cyberhaven
In this video, you will learn why legacy DLP tools go blind when sensitive data is copy-pasted into generative AI tools, how Data Lineage fingerprints information at its origin to track it across transformation within an environment, and how operating system-level monitoring eliminates the encryption blindness that limits browsers and firewalls. You will also see how to build context-aware paste policies that allow productive AI use while blocking high-risk data flows from sources like source code repositories, Salesforce, and internal wikis.
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By Cyberhaven
Your developers are leaking IP into generative AI— and your DLP can't see it. This is the Shadow AI gap breaking legacy Data Loss Prevention's capabilities.
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By Cyberhaven
On this episode of Founder Stories, Nishant Doshi, Cyberhaven CEO, and Dr. Volodymyr Kuznetsov, Co-founder and Chief Technology Officer at Cyberhaven, join the show to discuss their transition from founder-led leadership.
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By Cyberhaven
AI is rewriting data risk. On Feb 3, see how to fight back. Every week, AI makes your team faster—and your data more exposed. Files jump between new tools, models train on sensitive inputs, and traditional DLP is blind to the context that matters most. On February 3 at 11:00 AM PST, we’re pulling back the curtain on Cyberhaven’s unified DSPM & DLP platform—and showing how a single, AI‑native platform can finally keep up with how data actually moves.
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By Cyberhaven
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.
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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.
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By Cyberhaven
Dive into our expertly curated DLP program checklist that will align with your organization's ambitious business and catapult them forward.
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By Cyberhaven
In this guide we demystify DLP to distill the basics of DLP program development. Learn the essentials required to create scalable data security and data protection programs.
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By Cyberhaven
Data is leaving your company in ways that didn't exist years ago-AirDrop, generative AI, and more. Legacy DLP hasn't kept up; now it's time to invest in more forward-looking solutions.
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By Cyberhaven
DDR makes it possible to stop data exfiltration across all channels with one product and one set of policies.
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Cyberhaven detects and stops the most critical insider risks to your most important data.
Let’s face it, data security products never lived up to our expectations and now that the way we work is changing they can’t keep up. Cyberhaven solves these challenges so companies can finally protect their data.
Data Detection and Response:
- Understand how data flows: See what systems store different types of data and how data moves within the company to new places and people.
- Stop data exfiltration anywhere: Block important data from leaving your control via cloud, web, email, removable storage, Bluetooth/AirDrop, and more.
- Accelerate internal investigations: Quickly understand an incident to determine user intent with a complete record of events before and during an incident.
- Detect and stop risky behavior: Instantly detect when a user handles important data in a risky way, stop them in real time, and coach them.
Trace your data to protect it like never before.