of AI security incidents involve systems with no proper access controls in place.
IBM · Cost of a Data Breach 2025MMCPS sits between your team and any external AI — anonymizing sensitive data before it leaves, validating every prompt, and restoring responses on the way back. The LLM never sees the real data.
— The Problem
Most security teams have neither visibility nor control over what their employees paste into a chat box. Three numbers explain why that's a problem.
of AI security incidents involve systems with no proper access controls in place.
IBM · Cost of a Data Breach 2025extra average loss per shadow AI incident compared to traditional breaches.
Reco · Shadow AI Report 2025average time to detect and contain a leak — by then, the data has been seen.
Mean time to detectOrganizations that ban LLM tools lose visibility — employees move to personal devices. Those that allow unrestricted access risk GDPR and HIPAA violations. MMCPS is the third option: let your team work, while sensitive data never leaves the network.
— How it works
Four steps. No model fine-tuning, no prompt-injection tricks, no trust required of the LLM provider — sensitive data simply never reaches them.
A user types a request into the MMCPS web UI, or an internal app forwards one through the proxy endpoint.
Names, emails, IDs, locations, custom entities — replaced with consistent placeholder tags. The mapping stays in your machine.
Guard rules run on the anonymized prompt — block forbidden topics, enforce limits, redact secrets — then send.
The reply is scanned for any reconstructed sensitive data. Tags are swapped back to the originals — only the user ever sees them.
// Before anonymization "John Smith at [email protected] needs help with invoice #A-4471..." // After anonymization → sent to LLM "[PERSON] at [EMAIL] needs help with invoice [ID]..." // Response restored → returned to user "John Smith, here's what you need to do for #A-4471..."
↳ mapping table is held in-memory, scoped to the request, never persisted.
— Why MMCPS
A focused tool: a proxy, a UI, a small set of well-chosen guarantees. No telemetry, no upsell, no dashboard you'll never log into.
Microsoft Presidio detects and replaces PII — names, emails, IDs, locations, plus your own custom entities.
Guard rules block forbidden topics, secrets, and policy violations before any token leaves the network.
Every reply is scanned for reconstructed PII, hallucinated identifiers, or leakage before reaching the user.
A clean chat UI — anyone on your team can use it without learning a CLI or installing anything.
Run it on a laptop, a VPS, or your private cloud. Data never leaves the machine you control.
MIT licensed. Read the source, audit the rules, fork what you need. No black boxes between you and your data.
— Ready when you are
No setup required. Try anonymized chat and image processing instantly in your browser.
Keep everything on-premises. Run MMCPS on your own machine. Data never leaves.
MMCPS is free, open source, and ready to deploy. Spin it up in five minutes — keep it running for as long as your team uses AI.