Cyberhaven alternative: from data lineage to masked prompts

Some text looks harmless on its own. A paragraph with no ID in it might be from next quarter's board pack. Content inspection can't tell, but lineage can, because it knows where that paragraph was copied from. That's Cyberhaven's insight, and it's a good one. It answers a different question from the one masking answers, though.

Maskflare wrote this page. Cyberhaven solves problems we don't, so we've tried to be clear about where it's the better product.

What is Cyberhaven?

Cyberhaven is a data security platform covering DLP, insider risk and DSPM, built around data lineage. Its GenAI leakage article explains that its endpoint agent observes both a file's origin and its destination, so a policy can depend on where data came from. Its site says it blocks uploads to unsanctioned web, SaaS and AI apps, and governs coding agents like Claude Code and Cursor.

For AI use, its secure AI usage page describes discovering AI apps, agents and MCP servers, and coaching employees with plain-English explanations of policy. In May 2026 it announced a standalone browser extension for contractor devices and ChromeOS. Its trust center lists SOC 2 Type 2, several ISO certifications including ISO 27001 and ISO 42001, and PCI DSS.

We looked for masking and redaction on four of its pages and didn't find them. That doesn't prove it can't, so ask them.

Who should choose Cyberhaven?

• Your worry is what data is, not just what it looks like. Unreleased financials, source code and design files often have no pattern to match. Lineage catches those, and Maskflare's detectors won't.
• Insider risk is a program at your company. Lineage gives investigators a full history of where data went.
• You need channels beyond AI. USB, cloud drives, email and SaaS uploads are part of the same policy.
• You need finished certifications. Its trust center lists a wide set, while Maskflare's audits are in progress.
• Coaching and blocking fit your culture. Plain-English explanations can change behavior over time, without letting data through at all.

Who should choose Maskflare?

1. The work needs to continue. A block stops the prompt. Masking lets it through with values replaced, and restores them in the answer.
2. Your data has recognizable identifiers. Customer names, national IDs, IBANs, health data and credentials are what Maskflare finds, with 574 detectors, 47 country packs and checksum validation.
3. You build with AI. We didn't find an LLM gateway in Cyberhaven's public docs. Maskflare covers your own apps by changing one base URL, and adds SDKs and a LiteLLM guardrail.
4. Agents need masking, not only governance. Hooks for Claude Code, OpenAI Codex, Cursor, GitHub Copilot CLI and VS Code agent mode mask tool input and output, and the MCP route masks tool-call arguments and results. Cyberhaven documents discovery of MCP servers; we didn't find inline masking.
5. You'd like something small to roll out. Maskflare is a focused tool. A pilot needs an enrollment token, ten laptops and a week.
6. EU hosting matters. Maskflare is EU-hosted by default, with on-premises for enterprise. We couldn't find regions for Cyberhaven's service.

Cyberhaven vs Maskflare, feature by feature

Lineage and masking solve different problems

That's why this isn't always a choice between them. A company with serious insider-risk concerns could reasonably run both: lineage for confidential business data and masking for personal data in everyday AI work.

A useful way to decide is to look at the last month of blocked AI events. If most involve personal data and identifiers, masking would let that work continue. If most involve confidential documents with no identifiers, lineage is doing a job masking can't, so weigh it more heavily. Many teams will find a mix, which is why the steps below move only identifier-based rules.

How do you add Maskflare to a Cyberhaven setup, or replace it for AI?

1. List the blocks people complain about. Export your most-triggered AI policies, and note which ones are about identifiers rather than confidential documents.
2. Move only those. Identifier-based rules become mask rules in Maskflare, and source-based rules stay where they are.
3. Check the endpoint overlap. You'd be adding a second agent on the same device, so test on a small group first. We haven't published a tested joint configuration.
4. Add your own apps. Point one internal AI feature at the gateway.
5. Measure it. Track blocked prompts and completed tasks before and after the pilot.

What Maskflare doesn't do

• It has no data lineage. It looks at the content of AI traffic, so confidential text without identifiers can get through unless you add dictionaries or Exact Data Match.
• It isn't an insider-risk tool, and it doesn't cover USB, email or cloud-drive uploads.
• AI app discovery and coaching dialogs need the desktop agent on managed devices; personal phones and unmanaged laptops are out of reach.
• Prompt-injection detection runs on MCP tool results and tool listings, not on chat prompts, and there's no topic filtering.
• SOC 2 Type II and ISO 27001 audits are in progress. If you need a finished report today, factor that in.

Sources and how we checked

Based on public information as of November 3, 2026. Maskflare wrote this page, and vendors change their products, so check anything that matters with the vendor. “Not publicly documented” means we couldn't find it, not that the product lacks it. If something here is wrong, tell us and we'll correct it.

• cyberhaven.com/blog/prevent-genai-data-leakage
• cyberhaven.com
• cyberhaven.com/use-cases/secure-ai-usage
• cyberhaven.com/press-releases/cyberhaven-solves-the-surge-in-shadow-ai
• trust.cyberhaven.com