Insider Risk Management That Doesn’t Stop at Detection

Cyberhaven scores each user on the actions they take and the sensitivity of the data involved. Scores also incorporate watchlist membership, role context, and risk groups defined by your organization.

An engineer who uploads an archive of public documentation scores differently from one who uploads unreleased product IP.

Data Lineage follows sensitive data from origin through every copy, rename, transformation, and user interaction. Each behavioral signal carries the context to show whether an incident occurred and how far the data spread.

Cyberhaven flags when a user changes the name or extension of a file that contains sensitive data, and can block the exfiltration that follows. It also records the source of data entering the organization, which surfaces external-origin files that arrive with new hires, contractors, and personal devices.

Cyberhaven retains a continuous record of behavior and data movement and correlates events across days, weeks, and months. A Snowflake export on day 2, a ZIP file on day 22, and an AirDrop on day 27 appear in one timeline as the risk score rises.

Analysts can intervene before the final step, and no investigation starts from scratch.

Add users with a history of risky behavior to watchlists that apply elevated response, such as blocking an upload to an unapproved destination without allowing the user to override.

Integration with on-premises and cloud-based directories pulls department, manager, and departure date, so enforcement dynamically tightens for employees in their notice period.

Match the response to the risk. High-sensitivity data moving to a personal account is blocked with a plain-language explanation, lower-risk behavior triggers a real-time coaching popup, and suspected incidents are silently escalated to the security team.

Responses are configured by data sensitivity, user risk tier, and policy context, which reduces employee friction without reducing protection.

Cyberhaven tracks data through clipboard, browser, and AI tool submission events, and connects each paste back to the source file and its classification. Policy applies at the point of AI interaction, covering generative and agentic AI usage that leaves no file transfer event. For AI agents acting on a user’s behalf, Agentic Data Security extends the same Data Lineage and policies to agent actions.

When a developer pastes restricted source code into an unsanctioned AI tool, Cyberhaven blocks the submission with a plain-language explanation and redirects the user to the approved enterprise AI tool.

Cyberhaven captures forensic-level events remotely and stores them in the cloud, so post-incident investigation does not require physical possession of a device. Optional screenshot capture records the user's screen in the seconds leading up to an incident, stored in the customer's cloud.

Incidents for content-based policies include a highlighted excerpt showing what triggered the policy. Linea AI agents analyze workflows and data to find and report on insider risk.

Built-in capabilities include user behavior collection across cloud, devices, messaging, email, and apps, tracking of sharing permissions for individual users and anyone-with-the-link access, and separation of corporate and personal instances of the same application.

Built-in dashboards and a customizable reporting engine support analytics. Native SIEM integration with tools such as Splunk and an incident API pass findings to any third-party security tool, and role-based access control supports standard or custom roles.