Risk type: Data Leakage
Sensitive information in AI prompts
Sensitive information in AI prompts is the most common GenAI failure mode: employees paste private data into a prompt to get work done faster.
Quick answer
The fastest way to reduce AI risk is to control what can be typed, pasted, and uploaded in the browser. Combine governance (approved tools and data boundaries) with browser-layer enforcement. When users browse unknown destinations as part of AI workflows, isolation reduces endpoint exposure by running web content in an isolated container and streaming only rendered output; sessions are deleted after use.
When you need this
- Employees paste internal data into AI prompts to move faster.
- You need policy enforcement in the browser, not just training and documents.
- You want to allow AI productivity while preventing sensitive data loss.
Last updated
2026-01-29
Affected tools
- ChatGPT
- Microsoft Copilot
- Google Gemini
- Claude
How it usually happens in the browser
- Users paste credentials, tokens, or configuration snippets to troubleshoot errors faster.
- Support teams paste customer tickets, logs, and screenshots into AI tools for summaries.
- Finance teams paste invoices, bank details, and reconciliation data to extract fields.
- Employees upload files (contracts, CSVs) directly into browser-based AI tools.
- Teams copy outputs into other tools, propagating sensitive data across systems.
What traditional defenses miss
- Most security controls were designed for email, endpoints, and storage—not interactive prompt boxes in the browser.
- Encrypted web traffic makes it hard to classify content without endpoint/browser context.
- Policies exist on paper, but the workflow is too fast for humans to self-enforce consistently.
- Sensitive data often appears in “normal looking” text (logs, stack traces) that users don’t recognize as sensitive.
Mitigation checklist
- Create a classification checklist: what counts as sensitive in your org (examples, not just categories).
- Block or warn on pasting sensitive patterns into unapproved AI prompts (keys, secrets, PII).
- Use approved AI tools with enterprise controls; restrict or isolate unapproved tools.
- Redact logs and error payloads to reduce the chance that secrets appear in the first place.
- Add audit trails and escalation paths for teams that must use AI with sensitive contexts.
How isolation helps
- Isolation can be used to enforce “approved vs unapproved” AI usage paths by controlling where browsing sessions run.
- Isolated sessions are disposable, reducing persistent tracking and browser residue around risky tooling.
- Combined with policy controls, isolation helps reduce accidental cross-tab leakage from untrusted destinations.
FAQs
What data should never go into prompts?
Credentials and secrets, regulated personal data, and proprietary source code are common “never paste” categories for most organizations.
Is using AI for logs always unsafe?
Not always, but logs often contain secrets and internal endpoints. Redact first and use approved tools with guardrails.
How do we enforce this without slowing teams?
Use browser-layer guardrails that prevent obvious sensitive data patterns from being pasted and guide users to approved tools.
Does this apply to AI in other web apps?
Yes. Many SaaS apps embed AI copilots. The browser is still the user’s interaction layer and needs controls.