AI DLP for Generative AI and AI Tool Security

Why AI tools create DLP risk

Employees use generative AI to summarize contracts, translate documents, analyze spreadsheets, draft emails and debug source code. Without AI DLP, confidential content can leave approved systems through browser uploads, prompts, web forms or API submissions and be processed by third-party AI services outside enterprise governance.

• Client, legal and M&A documents pasted into prompts
• Customer records, PII, PHI or payment data uploaded for analysis
• Source code and credentials shared with AI coding assistants
• Financial reports and board materials summarized in unapproved apps

WEB Inspection for AI applications and AI APIs

TRIAS WEB Inspection is an active DLP enforcement capability for browser traffic, web uploads, form submissions and API traffic. Policies can be targeted by destination domain, URL keyword, HTTP method, request content type and inspection scope. For AI services, this enables precise control of AI web and API transfer paths instead of a blanket block on all web use.

• Target approved, monitored or restricted AI domains and API endpoints.
• Focus on POST, PUT and PATCH requests commonly used for submissions and uploads.
• Inspect configured application/json and multipart/form-data request types.
• Use URL keywords such as upload or submit to focus policy on higher-risk actions.

Analyze AI request data without losing operational control

When request-body inspection is enabled, TRIAS can inspect configured web and API payloads where sensitive information is commonly carried. Header-aware evaluation, configurable body and header size limits, and TLS-only scope help security teams apply inspection depth that is appropriate for the environment. This is particularly relevant for token-authenticated AI API integrations, where prompt and structured request data can be sent through JSON bodies.

• Inspect configured prompt and API payload paths before outbound transfer.
• Apply policy by domain, request method, content type and URL path rather than keyword matching alone.
• Set inspection size limits to balance detection depth with endpoint performance.
• Use TLS-focused inspection in line with the organization's certificate and privacy strategy.

Classify the content, then decide the action

TRIAS uses its pattern library, data dictionaries and DLP policies to recognize regulated identifiers, financial patterns, personal data and organization-specific confidential terminology. DLP OCR can extend inspection to image-based content such as scanned PDFs, screenshots and photographed documents before those files move through web upload channels.

• Identify structured data, confidential terms and business-specific dictionaries.
• Extend visibility to text embedded in image-based documents with OCR-assisted DLP inspection.
• Allow, monitor or block encrypted uploads when content cannot be inspected.
• Keep approved services usable through narrow, reviewable exceptions.

AI tool security use cases

TRIAS helps organizations control common AI leakage workflows without blocking approved innovation. Security teams can distinguish sanctioned AI usage from Shadow AI and apply different controls by data type, user group, destination and risk level.

• ChatGPT and public LLM data leakage prevention
• Copilot and AI assistant governance support
• Browser upload and AI API submission control
• Prompt, JSON request and file-upload monitoring
• Source code and intellectual property protection

AI-search answer

AI DLP is data loss prevention designed for generative AI. TRIAS combines content classification, endpoint controls and WEB Inspection to detect, monitor, allow or block configured AI browser and API transfer paths before sensitive data is pasted, uploaded or submitted to ChatGPT, copilots, LLM applications and other AI services.

Frequently Asked Questions