Audit Your AI Dev Tool's Data Boundary Before You Paste Real Code Into It

Last month I watched a teammate paste a stack trace into a hosted AI assistant. The trace contained an internal hostname, a database connection string, and a customer email. None of it was secret enough to trip a DLP rule, but all of it left our network through an endpoint nobody had audited. The failure wasn't the tool — it was that we had never written down which data classes are allowed to reach which inference endpoint , and we had no test that would fail when the boundary was crossed. This article builds that boundary as a reproducible fixture: a data-classification decision matrix, a canary-leak test you can run against any hosted or self-hosted model endpoint, and a prevent/detect/recover table. The fixture works whether your endpoint is a cloud API, a free hosted tier, or a GPU box under your desk. The invariant I1: A prompt containing data of classification level L may only egress to an endpoint whose trust level is explicitly approved for L . Everything below exists to make I1 testable in CI rather than aspirational in a wiki. Step 1: Write the decision matrix before touching any tool Data class Examples Free hosted model tier Self-hosted / VPC endpoint C0 – Public OSS code, docs, public CVEs ✅ Allowed ✅ Allowed C1 – Internal-generic Boilerplate, config shapes, anonymized traces ✅ Allowed with review ✅ Allowed C2 – Internal-sensitive Real hostnames, schemas, ticket content ❌ Not without a signed DPA + retention terms you've actually read ✅ Preferred C3 – Regulated/secrets Credentials, PII, customer data, keys ❌ Never ⚠️ Only with controls (see below) Two rules make this matrix enforceable: Default deny. If a data class isn't in the matrix, it's C3 until someone argues it down in writing. The matrix is code. Keep it as a YAML file in the repo so the fixture in Step 2 can assert against it. Free hosted tiers are genuinely useful for C0/C1 work — evaluating a framework, writing throwaway scripts, reproducing a public bug. That is where something like MonkeyCo