Stop AI Data Leakage

Stop Sensitive Data Leaking Into AI

Netra finds source code, secrets, customer data, and labeled files in AI prompts, uploads, attachments, responses, and agent tool calls, then blocks what shouldn’t leave.

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The Challenge

AI Is Now a Data Exit Path

Sensitive data moves through AI in both directions, often with no file involved.

01

Sensitive Data Hides in Plain Prompts

Employees paste customer records, source code, and credentials straight into prompts to get work done. No file is attached, so file-based controls never see it.

02

Agents Move Data Without a Prompt

Coding and desktop agents read local files and call tools and MCP servers with the user’s permissions. Data can leave through a tool call no one typed.

03

AI Answers Can Overshare

AI assistants answer from everything they can reach. A response can hand credentials, ID numbers, or a confidential file link to someone who never had access.

Protection

Detect It, Grade It, Stop It

Data-centric controls on everything that flows into and out of AI tools.

01Classification

Know What’s Sensitive Before It Moves

Content classifiers grade data from S1 to S4, least to most sensitive. Use hundreds of built-in classifiers and 580 built-in identifiers, add your own, and reuse your Microsoft Information Protection (MIP) labels. The Simulator tests text or a file without writing to audit logs.

02Guardrails

Catch the Leaks Simple Matching Misses

Guardrails group their patterns into six families, from data leakage to prompt injection, each scoped to the input, the output, or the whole multi-turn session. The data leakage family looks for credentials and one-time passcodes, card and national ID numbers, and PII that can reconstruct an identity, among other leak patterns, including data that builds up across a session.

03Uploads & Attachments

Grade Every File Sent to AI

The Uploads view grades each file sent to AI from S1 to S4, with user and channel. Data policies block attachments sent through AI chat. Rules can differ by account type, so a personal account and the corporate workspace on the same tool get different rules.

04Agents & Tool Calls

Data That Moves Without a Prompt

Agents read files and call tools on their own. The File Access view shows which AI agent processes opened MIP-labeled files. Tool Calls and MCP Activity have Observe and Block views, and AI Review gives a per-rule verdict with confidence and reason, so analysts can clear false positives fast. For agent inventory and controls, see Secure AI Coding and Secure MCP & AI Supply Chain.

05Data Exfiltration Prevention

Block Sensitive Content on Its Way Out

Content policies in Protection › Data decide what happens when sensitive content heads to an AI tool. Choose the content to act on, from S1 to S4 classifiers to MIP labels, and the AI channels a policy covers. Set the effect to Block or Allow, show a pop-up that tells the user why, and log every match. Scope each policy by user, department, device ownership, or device label, and set its priority against your other policies.

Investigation

Evidence Without Reading Every Chat

Conversation content stays masked by default until a reviewer reveals it.

Alerts by Risk Pattern

Alerts rank conversations High, Medium, or Low, with risk pattern, topic, user, and treatment status, so the worst cases go first.

AI Summarize

Summarize gives a short AI summary of any conversation, so reviewers can triage without reading every message.

Agent Trace

From a data event in Activity, Agent Trace opens the task, channel, user intent, messages, and tool calls behind it.

Next Steps

Protect the Rest of the AI Stack

Data protection works best alongside discovery, agent controls, and insider risk.

Discover Shadow AI

Find every AI app, agent, and account in use before you write policy.

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Secure AI Coding

Control coding agents like Claude Code, Cursor, and Codex on developer machines.

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Manage Insider Risk

Score risky behavior against each user’s baseline and see who needs a closer look.

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Replace Legacy DLP

Protect AI, email, cloud storage, and USB from one platform and one policy set.

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FAQ

Common Questions

What data does Netra stop from reaching AI tools?

Whatever your classifiers define as sensitive: source code, secrets and credentials, customer and employee PII, financial data, and files with Microsoft Information Protection (MIP) labels. Content is graded S1 to S4, and policies can act on classifiers or MIP labels.

Does Netra block, or only monitor?

Both, by policy. Prompts, tool calls, and MCP activity each have Observe and Block views. You can audit first, then block specific content, attachments sent through AI chat, or uploads to personal AI accounts.

Does Netra check AI responses as well as prompts?

Yes. Guardrails check the input, the output, or the whole multi-turn session, so sensitive data in an AI response is caught as well as data in a prompt, including confidential data that builds up over a conversation.

How does Netra handle employee privacy?

Conversation content is masked by default, and a reviewer must click to reveal it. Reviewers can start from an AI summary instead of the full conversation. The Gateway is cloud-hosted by default and can run on-premises.

See What Your Teams Send to AI

Run a proof of value on your own endpoints and see which sensitive data reaches AI tools, and which policies would stop it.

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