Prompts leak sensitive data
Employees paste customer information, finance data, and internal documents into AI chats, moving sensitive data beyond enterprise boundaries.











































































Employees use AI every day, but these risks can remain invisible
Employees paste customer information, finance data, and internal documents into AI chats, moving sensitive data beyond enterprise boundaries.
Employees use unapproved AI tools, leaving security teams unable to see who is using what and what data is being sent.
When developers use tools such as Copilot or Cursor, source code, API keys, and architecture details may be sent to third-party models.
Agents use MCP and skills to automate actions. If poisoned or prompt-injected, legitimate automation can be abused for data theft and privilege misuse.
Discover, record, inspect, mask, and block risky AI interactions across employees, developers, agents, and self-built AI applications.
Identifies and governs all AI tool usage within the enterprise across web, client, and browser extension entry points. Eliminates Shadow AI blind spots with real-time interception and masking of sensitive prompts.

Protects against security risks when developers use Copilot, Cursor, and other AI coding tools. Automatically identifies and masks source code, API keys, and internal architecture information before it is sent to third-party models.

Full-chain security monitoring tracks every automated operation executed by AI agents via MCP protocol and Skills in real time. Precisely identifies and intercepts prompt injection attacks, data poisoning, and privilege escalation attempts.

Builds full input and output protection for enterprise-built AI applications. Blocks prompt injection and jailbreak attacks on the input side. Filters sensitive data leakage on the output side. Ensures AI apps run within secure boundaries.

Find unsanctioned AI tools, classify risk levels, and bring usage into policy control.


Covers employee AI tool use, AI coding, and AI agent scenarios. Eliminates Shadow AI blind spots so every AI interaction is auditable.
Three-layer protection: prompt semantic detection, dynamic masking, and real-time interception, handling sensitive data before it leaves the enterprise boundary.
Full MCP call chain monitoring and anomaly blocking prevents AI agents from becoming attack entry points or data leakage channels.
Leading customers in intelligent manufacturing, fintech, internet, and global business are building future-ready, efficient, and secure workplace platforms with Eagle Cloud.
Assess AI usage visibility, permission governance, and sensitive data protection maturity.