Risk type: Tool Risk
Claude security
Claude security is about preventing sensitive data leakage through prompts and uploads and managing the browser workflows that make it easy to share secrets with AI tools.
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
- Claude
- Claude Team/Enterprise
- Browser-based AI chat tools
- AI extensions
How it usually happens in the browser
- Employees paste internal documents, customer data, and code into prompts to draft emails or summarize tickets.
- Users upload files (logs, CSV exports) via browser-based AI UIs.
- Teams copy outputs into other tools without review, spreading sensitive context.
- Unapproved AI tools and extensions proliferate, creating inconsistent enforcement across teams.
- Users follow AI-suggested links to unknown web destinations during research.
What traditional defenses miss
- Classic DLP focuses on email/storage, not interactive AI prompt boxes.
- Network inspection struggles with encrypted sessions and lacks tab-level context.
- Employees don’t consistently identify sensitive information in logs and internal notes.
- Without browser-layer controls, governance policies are hard to enforce consistently.
Mitigation checklist
- Define and enforce “never in prompts” data categories and provide team-specific examples.
- Restrict paste/upload into unapproved AI tools; allowlist approved destinations.
- Restrict AI-related extensions and enforce a strict allowlist for browser add-ons.
- Require human review for outputs that impact customers, compliance, or security decisions.
- Continuously monitor and update AI usage policy based on real behavior and exceptions.
How isolation helps
- Isolation reduces endpoint exposure when users browse unknown destinations as part of AI-assisted workflows.
- It provides a disposable environment for risky exploration and supports policy boundaries for unapproved sites.
- Isolation complements browser-layer controls that prevent accidental data leakage across tabs and destinations.
FAQs
Is this risk unique to Claude?
No. The core problem is browser-based AI usage: prompts, uploads, and untrusted links. It applies across tools.
What’s the most common failure mode?
Sensitive data pasted into prompts under deadline pressure—especially logs, customer tickets, contracts, and code.
How do we keep AI productivity without leaks?
Allowlist approved tools and enforce browser-layer guardrails for sensitive paste/upload actions, plus clear policy and examples.
Does isolation stop prompt leakage?
Isolation helps control risky browsing, but prompt leakage is best addressed by content-aware guardrails and governance alongside isolation.