Local-first
Core detection runs on each machine. Prompts and files are scanned in place — no cloud round-trip to protect them.
GPT-Shield is built for the most sensitive data in your company. The whole design rests on one idea: we protect your data by never holding it. Here's exactly how that works.
Core detection runs on each machine. Prompts and files are scanned in place — no cloud round-trip to protect them.
The sensitive value itself is never written to a log, audit event, lineage edge, or the vault by default. Only salted hashes and token references.
Anything that is persisted — like reversible pseudonymization maps, when enabled — is AES-GCM encrypted, backed by the OS keychain.
The same input, policy, and version always produce the same result — identical on every surface, and provable from the audit trail.
Detection, classification, and transformation all happen on the device or in your own infrastructure. There is no required cloud dependency for protection.
The browser extension and desktop agent run the engine locally; the gateway is self-hostable and OpenAI/Anthropic-compatible. Nothing sensitive leaves the boundary you control.
If you turn on hosted features (like a shared data-flow graph), they receive only de-identified signal — classifications, counts, and hashes — never raw values.
By never storing the raw value and keeping processing local, GPT-Shield removes the riskiest part of the data-handling equation. Formal attestations are on the way.
On our roadmap. We're building toward a formal attestation; ask us where we are today.
Designed for it: local processing and never storing raw values keeps sensitive data out of scope wherever possible.
Need a data-processing agreement or a security questionnaire completed? We're happy to.
Read our Privacy and Terms, or email noah@gpt-shield.com.
Bring your security questions to a 20-minute walkthrough — we'll show you exactly what crosses the boundary and what never does.
No raw data leaves your machine. Ever.