MemoryMap AI is a local-first, single-user app that runs on your own machine. It binds to 127.0.0.1 (localhost only), never exposes itself to the network, and never sends your notes to the cloud. Your data lives in a folder on your disk (data/), and access to the app is gated behind a password you choose on first run (bcrypt-hashed, stored locally).

Because of this design, the most important protections for your notes are the ones your operating system already provides:

• Encryption at rest. The database is a plain SQLite file. If your notes are sensitive, enable full-disk encryption (BitLocker on Windows, FileVault on macOS, LUKS on Linux). SQLCipher is deliberately not bundled: it needs a native dependency on every platform for a single-user local file, and disk encryption covers the same threat more simply. See docs/PRIVACY.md for what the app encrypts on its own (private notes).
• Backups. The app takes a daily local snapshot into your data folder. Those snapshots are as sensitive as the database, keep them somewhere you trust.

This is an actively developed 0.x project; security fixes land on main. Please run the latest main.

Please do not open a public issue for security problems.

Instead, report privately using GitHub's private vulnerability reporting: go to the repository's Security tab, then Report a vulnerability.

When you report, please include:

• what the issue is and where in the code it lives, if you know;
• steps to reproduce; and
• the impact you think it has.

You'll get an acknowledgement, and we'll work with you on a fix and disclosure timeline. Thanks for helping keep MemoryMap AI safe.

Since the app is localhost-only and single-user, classic web-app threats (CORS, cross-site attacks from other origins, multi-tenant data leaks) largely don't apply. The areas most worth scrutiny are: the unlock and auth flow, file upload handling, the opt-in web-search path (the only outbound network feature), and anything that could let the agent's tools act without the required confirmation.