HeimWall

HeimWall is a macOS security application that monitors AI coding prompts for sensitive data exposure before they reach cloud services. It runs entirely on your Mac, flagging secrets and personally identifiable information in prompts sent to Cursor, Claude Code, Copilot, and other AI coding tools. The detection happens locally using deterministic regex matching, which means it's instant, explainable, and works completely offline without any network dependency. Nothing you type ever gets transmitted anywhere, and no account creation or sign in is required to use the free individual version. The application simply watches what you're about to send and warns you if something sensitive appears in your prompt before it leaves your machine.

The detection engine identifies forty seven different credential types including AWS keys, GitHub tokens, private SSH keys, JWTs, database connection URLs, Stripe API keys, Twilio credentials, and various other API secrets that developers regularly paste into prompts while debugging or asking for code help. Beyond credentials, it catches personally identifiable information like social security numbers, credit card numbers, phone numbers, and email addresses that might appear in sample data or test fixtures. A single background agent monitors multiple AI tools simultaneously, so you don't need separate watchers for each coding assistant you use. The regex patterns are deterministic rather than ML based, which means you can understand exactly why something triggered and there's no model making probabilistic guesses about what looks sensitive. When something fires, you know exactly which pattern matched and why.

The technical implementation keeps the application lightweight at just over four megabytes, built with Rust and Tauri for native performance without the bloated overhead of Electron based alternatives. It requires macOS 13 or later and supports Apple Silicon natively with good battery efficiency. When HeimWall detects sensitive content in a prompt, it displays a notification before the prompt reaches the AI service, giving you a chance to redact the sensitive portion or reconsider before sending credentials to a cloud provider you don't control. The scanning happens in the capture pipeline rather than after transmission, which is the only point where interception actually helps prevent exposure. Once data leaves your machine, it's out of your control regardless of what monitoring you have in place afterward.

The free version remains perpetually free for individual developers with no feature gates, trial periods, usage limits, or artificial limitations designed to push you toward paid tiers. If you're a solo developer who wants to avoid accidentally leaking secrets to AI providers, the tool does exactly that at no cost and with no strings attached. A paid team product is under development that will allow managers to see redacted security metrics across their organization while preserving prompt privacy for individual developers. The team tier addresses compliance and audit requirements without compromising the core privacy model since managers see aggregate statistics about detection events rather than actual prompt content or any ability to reconstruct what developers were working on. That balance matters for organizations that need oversight for compliance purposes without implementing invasive surveillance of their engineers.

HeimWall fills a specific gap in the AI coding workflow that other tools don't address well. Developers routinely paste error messages, configuration files, stack traces, environment variable dumps, and debug output into AI prompts, and those snippets often contain credentials or connection strings that shouldn't leave the local machine. Traditional secret scanning happens in CI/CD pipelines or pre commit hooks, but that's too late when the secret already went to an AI provider during development. Pre commit hooks don't run when you're just asking Claude how to fix a bug or pasting a stack trace to understand an exception. By intercepting prompts at the source, HeimWall prevents exposure rather than detecting it after the fact when the damage is already done. The audited architecture and fully local processing model distinguish it from alternatives that analyze prompts server side, where you'd have to trust their infrastructure not to log, retain, or mine your data. For developers who take data hygiene seriously, work under compliance requirements that restrict where sensitive data can flow, or simply prefer tools that respect privacy by design rather than by policy, that distinction matters considerably more than saving a few megabytes on application size.