AI Security for the Age of Autonomous Agents
Cyberhaven Agentic Data Security provides unprecedented visibility into AI usage and enforces risk-based controls, enabling AI adoption while keeping data safe.
Agents changed data security
Why Existing AI Security Tools Fall Short
AI changed work, but most AI security products focus on tooling, like the AI models or apps being used, and miss the critical context about the data itself. As AI agents act on data, securing it becomes more challenging than ever.
AI Keeps Evolving
Endpoint-based agents, local models, MCP servers, and background processes increase complexity and risk while remaining largely invisible.
Machine-Speed Data
As AI continues to read, transform, and act on data, Legacy DLPs, built for human-speed actions, can't keep up.
Controls Stop at the Browser
Existing AI security approaches have no visibility into agents that operate at the OS level and bypass network controls entirely.
How Agentic Adoption Is Evolving
Growth of endpoint-based AI agents in 2025
Of developers use AI coding assistants
Of all AI interactions involve sensitive data
How it works
Discovery, Observability, and Control for AI Agents
Cyberhaven gives security teams real-time visibility into AI apps, agents, and data flows, across SaaS, endpoints, and developer environments. Policies are enforced based on behavior and data context, not assumptions.
Find Agents
Discover AI tools and agents running across endpoints, browsers, and the cloud, including unsanctioned apps, and score each for risk.
See What Agents Do
Capture prompts, tool calls, file reads, and responses, along with the data involved in each step, for a step-by-step record of agent activity.
Know Who Sent What
Tie each action to the person or system behind it, with humans and agents in one view for faster investigations and audit-ready records.
Stop Data Before It Leaves
Apply the policies you already use for humans to agent actions, and contain sensitive data in real time without blocking teams from adopting AI.
The Power of Data Lineage
Cyberhaven pioneered Data Lineage to map data from its origin through every location it reaches. It captures every move, copy, edit, and share, creating a complete map of how sensitive information flows across your enterprise.
Proven Data Security, Extended to Agentic Workflows
Cyberhaven’s DLP, DSPM, and insider risk capabilities extend to AI agents, providing end-to-end visibility and control for data.
Agentic DLP
Stop sensitive data and credentials from leaving through sanctioned and unsanctioned AI agents. Lineage-aware policies follow data across endpoints, browsers, and the cloud, so protection holds even when an agent copies, summarizes, or fragments the original.
Agentic Data Security Posture
Discover and inventory AI agents, MCP servers, and tools, then enforce allow-lists and block shadow servers. Trace AI-generated content to its originating agent, session, and source data, and find sensitive data in past agent activity.
Agentic IRM
AI agents are the new insider risk. Agents act with the access of the people they serve, at machine speed. Investigate any agent session step by step, with data lineage, identity attribution, and sensitivity context at each step, and see agent behavior alongside the people behind it.
Key capabilities
Data Security for the Agentic Enterprise
Cyberhaven Flow traces the full lifecycle of data and adapts protection to changing context
Key capabilities
The AI Security Features Data Security Teams Need
Shadow AI Discovery
Continuously inventories AI agents running across endpoints, browsers, CLIs, and IDEs, including tools that cloud-only security solutions cannot see.
Agentic AI Visibility
Reconstructs the full execution lifecycle of every agent interaction, capturing tool calls, data access, and multi-turn conversation context in a single view.
MCP Server Monitoring
Discovers and monitors Model Context Protocol servers and AI connectors across the enterprise, surfacing risk from integrations that operate outside traditional security controls.
AI Risk IQ Scoring
Assigns risk scores across five dimensions to every AI application and agent in your environment. Scores are maintained quarterly by Cyberhaven, with no customer configuration required.
AI Data Flow Control
Enforces runtime guardrails at the prompt and response level, blocking high-risk data movement, redirecting users to sanctioned tools, and coaching employees with plain-English policy explanations.
Data Lineage for AI Interactions
Connects every agent action to the data it touched, showing where that data originated and where it went next, so alerts become investigations.
Real-Time Enforcement
Stops unsafe or high-risk agent actions before they cause damage, with block, warn, and redact controls that operate across the full agentic workflow.
Usage and Adoption Insights
Surfaces AI adoption trends across the enterprise, categorizing applications as Sanctioned, Unsanctioned, Tolerated, or Restricted to support governance decisions.
Compliance Audit Readiness
Provides a comprehensive record of AI agent activity, data access, and policy enforcement actions to support audit workflows and regulatory reporting.
Unified Console and Reporting
Manages AI security policy, alerts, and reporting from the same console used for DLP and IRM, with no additional policy engine for existing customers to learn.
Our customers
Why Teams Choose Cyberhaven to Secure Their Agentic Workflows
“Cyberhaven created a transformational difference. We now have really substantial visibility.”
Compare Cyberhaven With Other Data Security Solutions
Frequently Asked Questions
How Does Cyberhaven Detect AI Tools on Endpoints?
Cyberhaven uses an endpoint agent to continuously inventory AI tools as they appear across the organization, including mainstream SaaS generative AI applications, coding assistants running in IDEs and CLIs, open-source agent frameworks, and Model Context Protocol (MCP) servers.
What Is an AI Risk Score?
Cyberhaven's AI Risk IQ scores every AI application and agent across five dimensions: data sensitivity, model integrity, compliance adherence, user access controls, and security infrastructure. Scores are maintained quarterly by Cyberhaven's research team, with no configuration required from customers. This gives security teams an evidence-based risk posture they can act on and defend during audits.
How Does Cyberhaven Enforce Policies on AI-Generated Data?
Cyberhaven enforces policies at the data level, not the tool level, using Data Lineage to trace where sensitive data originated and how it has moved. When an AI agent accesses a regulated file or a developer pastes PII into a coding assistant, Cyberhaven can block, warn, or redact in real time based on data context and the risk score of the tool involved. Enforcement operates across the full agentic workflow, including prompts, responses, and downstream data flows, without disrupting legitimate work.
Can Cyberhaven Secure Agentic AI like Claude Code or Copilot?
Yes. Cyberhaven's endpoint agent monitors agentic AI tools including coding assistants like Claude Code and Copilot, reconstructing the full execution lifecycle of each agent interaction: tool calls, data access, and multi-turn conversation context. Security teams can see what data each agent ingests, set risk-based policies on how sensitive data can be used within those workflows, and enforce controls in real time before data leaves the environment.
How does Cyberhaven prevent enterprise AI data exfiltration?
Preventing AI data exfiltration starts with knowing where sensitive data came from, which agent or person is moving it, and where it is going. Cyberhaven traces the full lifecycle of your data, adapting protection to changing context, and acts in real time when an AI agent or generative AI tool tries to move sensitive data. Data lineage supplies the origin, identity attribution ties each action to the person or system behind it, and controls on MCP connections govern which tools and data sources agents can reach.
What should enterprises look for when evaluating an agentic AI data security vendor?
Evaluate an agentic AI data security vendor on four criteria. First, whether it traces data lineage from origin through each agent action. Second, whether it understands context, including where data came from and how an agent is using it. Third, whether it acts in real time where agents operate. Fourth, whether it protects people and agents in one platform, with one set of policies. Cyberhaven meets all four, applying Data Lineage and Linea AI to people and agents together on a single platform.
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