Data loss prevention for AI tools — a complete guide
Every time a team member pastes data into ChatGPT or Claude, your organization risks exposing sensitive information. This guide explains why DLP for AI tools is essential, what to scan for, and how to implement protection today.
DLP Fundamentals
What effective AI DLP looks like
Every feature designed to help your team work smarter with AI.
Real-time prompt scanning
Every prompt is scanned for sensitive data patterns before it leaves the browser. Detection happens in milliseconds, providing protection without disrupting the user experience.
Auto-sanitization
Instead of simply blocking prompts, auto-sanitization replaces sensitive data with safe placeholders like {{SSN}} or {{PATIENT_NAME}}, preserving the prompt's intent while removing risk.
Credential detection
Detect API keys, access tokens, database connection strings, and other credentials that developers commonly paste into AI tools for debugging assistance.
Custom pattern rules
Define organization-specific sensitive data patterns using regex, keyword matching, or exact match rules. Cover internal project codes, customer identifiers, or proprietary data formats.
Violation logging
Every DLP scan result — clean or flagged — is logged with full details. Violation logs include the rule triggered, the action taken, and a redacted version of the matched content.
Cross-tool coverage
DLP scanning works across ChatGPT, Claude, Gemini, Microsoft Copilot, and Perplexity through a single browser extension, providing consistent protection everywhere.
Benefits
Why your team needs DLP for AI tools
16
Smart detection patterns
15
Built-in DLP rules
6
One-click compliance packs
FAQ
Frequently asked questions
What types of data should we scan for?
At minimum, scan for Social Security numbers, credit card numbers, API keys, and personal health information. TeamPrompt's compliance packs add framework-specific patterns for HIPAA, GDPR, PCI-DSS, and more.
Does DLP scanning see the full prompt text?
Scanning happens locally in the browser extension before data leaves the device. TeamPrompt does not store or transmit the full prompt text — only violation metadata is logged for audit purposes.
Should we block or warn on violations?
Start with warnings to understand your team's data handling patterns without disrupting productivity. Escalate high-risk patterns like PHI or credentials to block mode once your team is trained.
How do we roll this out to a large team?
Deploy the browser extension via your MDM or group policy, enable the compliance packs relevant to your industry, and start in warn mode. Review violation logs weekly and adjust rules based on what you see.
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