DLP for
Google Gemini
Gemini sits inside the browser, across Google Workspace, and in Google AI search. Without DLP controls, confidential data flows freely into all of them. Aona detects, redacts, and hard-blocks sensitive data in real time, across Gemini on the web, Gemini in Google Workspace, and Google AI search.
What Gets Leaked into Gemini
These four data types appear most frequently in Gemini prompts and uploads, and create the most significant compliance and competitive risk.
Customer PII
Names, email addresses, phone numbers, account details, pasted into Gemini during customer service, sales, or data analysis tasks.
Financial Records
Revenue data, forecasts, earnings reports, payment card numbers, and budget documents shared with Gemini before public disclosure.
Source Code
Proprietary algorithms, API keys, database credentials, and internal codebases submitted to Gemini without restriction.
Internal Strategy Docs
Board minutes, M&A information, competitive strategy, and legal correspondence dropped into Gemini for drafting or summarisation.
How Aona DLP Works
Three-stage pipeline from prompt to protection, all in real time, before data leaves your environment.
Real-Time Prompt Inspection
Aona intercepts every prompt and file upload before it is submitted to Gemini, on the web and inside Google Workspace. The content is inspected in milliseconds, with no latency impact on the employee experience.
Classification
Aona classifies the prompt content server-side against your data policies, identifying PII, financial data, source code, and custom data types using AI-native pattern recognition.
Block or Redact
Depending on your policy, Aona hard-blocks the prompt or automatically redacts the sensitive portion, in real time. There is no acknowledge-and-continue override.
Where Aona Covers Gemini
Aona DLP works across every surface Gemini runs on, from the standalone web app to Gemini inside Google Workspace and Google AI search.
Gemini (web)
Gemini in Workspace
Google AI search
ChatGPT
OpenAI
Microsoft Copilot
Microsoft
Claude
Anthropic
Perplexity
Search AI
+ 5,600 more
All AI tools
How Aona DLP for Google Gemini Works
Real-time prompt and file inspection across the web, Google Workspace, and Google AI search, protecting data before it ever leaves your organisation.
Deploy Across Gemini
The Aona browser plugin (Chrome, Edge, Firefox) covers Gemini on the web, Gemini in Google Workspace, and Google AI search. One policy, every Gemini surface, with no firewall changes.
Inspect Every Prompt and Upload
Aona intercepts prompts and file uploads before they reach Gemini. Every prompt is scanned server-side for PII, financial data, source code, healthcare records, and custom data types, in real time, with zero latency impact.
Hard-Block or Redact
Depending on your policy, Aona hard-blocks sensitive prompts with no acknowledge-and-continue override, or redacts the sensitive portion of an uploaded DOCX or Excel file while preserving layout. Full audit log captured for every event.
of employees use unsanctioned AI tools
Gartner, 2025
average cost of an AI data breach
IBM Cost of a Data Breach Report, 2024
Gemini is everywhere your team already works
Gemini is woven into Docs, Sheets, Gmail, and search, so employees reach for it without thinking of it as a separate AI tool. That makes accidental data exposure more likely, not less. Aona applies the same hard-block and redaction policy across Gemini on the web, Gemini in Google Workspace, and Google AI search, so the control follows the employee wherever Gemini appears.
Gemini in Workspace turns everyday Docs, Gmail, and Sheets into AI prompts
Gemini is built directly into Google Workspace, so the act of using it does not feel like sending data to an AI tool. That is precisely why sensitive content slips out without anyone noticing.
Gemini inside Docs, Gmail, and Sheets
An employee asks Gemini to redraft a paragraph in Docs, summarise a thread in Gmail, or analyse a range in Sheets. Each of those actions sends the underlying content, which is often customer data, revenue figures, or confidential correspondence, to the model. Aona inspects that content on submit, so the same hard-block and redaction policy applies inside the Workspace apps as on the standalone Gemini app.
Workspace data boundaries
Google describes data protections for Gemini inside paid Workspace editions, but those boundaries only cover the domain your organisation administers. They do nothing about an employee on a personal Google account using consumer Gemini in the same browser. Aona enforces one policy regardless of which account the employee is signed into.
The Gemini web app and Google AI Overviews are two more exits
Beyond Workspace, employees reach Gemini through the standalone web app and encounter Google AI directly in search results. Both are easy to forget when scoping AI data risk.
The Gemini web app
The standalone Gemini web app accepts long prompts and file uploads, and staff use it for exactly the tasks that involve sensitive material: drafting, analysis, and summarising documents they have to hand. Aona's browser plugin for Chrome, Edge, and Firefox inspects every prompt and upload before it reaches Gemini.
Google AI Overviews in search
Google now answers many searches with AI Overviews, so employees increasingly type detailed, context-rich queries into the search bar expecting a generated answer. Those queries can carry internal detail that should never leave the organisation. Aona covers Google AI search alongside Gemini, so the search box is not an unmonitored gap.
DLP for other AI assistants
Aona applies the same real-time, server-side DLP across every major assistant your team uses. Explore the tool-specific guides.
DLP for ChatGPT
Cover ChatGPT Enterprise, Team, and free, plus custom GPTs and memory, with one consistent policy.
DLP for Microsoft Copilot
Cover Microsoft 365 Copilot, Copilot in the browser, and the Copilot desktop app intercepted by Aona's native endpoint.
DLP for Claude
Cover Claude on the web and the Claude desktop app intercepted natively, including Projects and MCP connectors.
Turn DLP policy into a real AI governance program
Use these templates and resources to define what data can reach AI tools, document controls, and create the audit trail security reviewers expect.
AI Security Audit Checklist
Audit AI tool usage, data flows, prompt controls, and governance gaps before sensitive data leaves your organisation.
AI Incident Response Playbook
Give security teams a repeatable process for investigating AI data leakage, prompt abuse, and policy violations.
AI Security Statistics 2026
Use current benchmarks on AI risk, leakage, and adoption to build urgency with leadership and procurement teams.
Frequently Asked Questions
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