Govern AI at the Speed It Operates
AI use has moved beyond the browser tab. Agents like Claude Code, Codex, and Copilot now run on endpoints, open files, invoke tools, and complete multi-step tasks under an employee’s identity, often without oversight. This datasheet shows how Agentic Data Security, built on Cyberhaven Flow, discovers the AI apps and agents in use, traces the data they touch, and controls risky data flows at machine speed.
Source: Cyberhaven Labs.
What's inside
Why Agentic AI Creates Security Blind Spots
Agents like Claude Code, Codex, and Copilot run on endpoints, open files, and complete multi-step tasks under an employee’s identity, often without oversight.
A log entry showing that an AI app was used does not reveal what the agent read, what it did, or where the output went.
Teams struggle to tell governed corporate AI accounts from personal ones, while shadow agents and unmanaged Model Context Protocol (MCP) servers outpace any catalog.
How Cyberhaven Flow Governs AI Apps and Agents
Flow combines Data Lineage, AI content inspection, and an endpoint agent to show AI apps, agents, and data flows across cloud apps, endpoints, and developer environments.
Four steps cover discovery, monitoring, risk scoring, and control. AI Risk IQ scores apps and agents across five dimensions, from data sensitivity to security infrastructure.
Guardrails block, warn, or redact at the prompt and response level, with plain-English explanations in place of generic block pages.
Proven Capabilities, Now Extended to AI Agents
Agentic Data Security extends data loss prevention (DLP), data security posture management (DSPM), and insider risk management (IRM) to AI agents.
Security teams reduce AI blind spots, protect sensitive data before risk becomes loss, score risk automatically, and investigate 5x faster.
Coverage spans ChatGPT, Copilot, Gemini, Claude, Claude Code, Codex, MCP servers, and 300+ cloud apps including Google Drive, Slack, and Salesforce.