Problem solution
LLM data leakage with PromptWall.
PromptWall turns LLM data leakage from a policy concern into runtime controls across prompts, AI DLP, secure gateway traffic, and governance evidence.
Control
Policy first
Turn AI usage rules into runtime decisions.
Data
DLP aware
Detect sensitive data before prompts reach providers.
Evidence
Audit ready
Keep reviewable proof for security and compliance teams.
Traffic
Gateway aligned
Apply policy around provider and model traffic.
Problem definition
The problem
LLM usage can expose sensitive data when users paste documents, support tickets, code, or regulated records into prompts.
Risks
Why it matters
Customer PII, credentials, source code, and protected documents can leave the organization without review.
PromptWall solution
PromptWall applies policy before the AI interaction becomes risk.
PromptWall inspects AI prompts and context, detects sensitive content, applies allow/mask/flag/block policy, and preserves reviewable audit evidence.
Technical explanation
How the control path works
PromptWall detects sensitive entities and document leakage risk before the request reaches an AI provider.
Use case
Enterprise use case
A support organization can summarize tickets while masking customer identifiers before provider dispatch.
Evaluate PromptWall for LLM data leakage
Bring your workflow, policy requirement, and sensitive data scenario. We will map the PromptWall control path.
Frequently asked questions
How does PromptWall help with LLM data leakage?+
PromptWall adds prompt inspection, AI DLP, gateway policy, and audit evidence at the point where AI usage happens.
Is this a replacement for existing security controls?+
No. PromptWall complements existing controls with AI-specific prompt, data, provider, and governance enforcement.