2 posts tagged with "dlp"

Your AI team treats the system prompt as proprietary IP. The deployment pipeline strips it from every customer-readable surface. The runbook for production debugging tells engineers to grep it out of any incident artifact before that artifact leaves the war room. Your last security review caught and closed three different paths the prompt could escape through: an over-verbose API response, a debug header that shipped to the wrong tier, a stack-trace endpoint that interpolated the prompt into its message.

None of that mattered the morning an engineer joined a vendor support call about an unrelated billing dispute, screen-shared their terminal to walk through a stack trace, and the trace included a single verbose log line that printed the fully resolved prompt — every injected variable substituted in, including the customer-specific business rules and the internal model-routing hints. The vendor's support engineer recorded the call as part of their standard support workflow. The recording landed in the vendor's case management system. The prompt was now legibly stored in a third-party SaaS your security review had no contract with, no DPA against, and no audit rights over.

The first internal LLM gateway is almost always built for the boring reasons: cost attribution so finance can answer "which team spent the inference budget," rate limiting so one runaway script doesn't burn the monthly quota, provider failover so an OpenAI hiccup doesn't take down the assistant. Data loss prevention shows up on the slide deck, but it ships as "each app team should redact sensitive fields before they call the model." Six months later there are nine apps in production, three half-maintained redaction libraries with subtly different regex sets, two prototypes that bypass the gateway entirely "just for testing," and a customer-data-in-prompt incident that everyone's middleware was supposed to prevent because nobody's middleware was the canonical egress point.

This is not a tooling problem. It is an architectural mistake. DLP is an egress control, and egress controls only work when the path is mandatory. The moment you let app teams own redaction, you've ceded the property that makes DLP function — that there is exactly one place sensitive data can leave, and you can prove what crossed it. The 2025 LayerX Security report puts the scale of the problem in numbers most teams haven't internalized: GenAI-related DLP incidents more than doubled in early 2025 and now make up 14% of all data-security incidents across SaaS traffic, with employees averaging 6.8 pastes into GenAI tools per day, more than half of which contain corporate information. The shadow path is winning by default.