Introducing DeployReady: Catch Production Risks Before You Ship

Most security and reliability problems are not discovered in code review. They are discovered in production, after a misconfigured CORS policy, a hardcoded key, or an unprotected route has already shipped. We have inherited enough of these systems to know the pattern — and to know that the fix is to catch them before deploy, not after.

So we built a tool for it. DeployReady is a local-first, AI-optional production-readiness scanner. You point it at your app, it runs more than 30 structured tests against both your source code and your running application, and it gives you a single 0–100 readiness score with a clear breakdown of what is critical, what is a warning, and what is just worth knowing.

It is free, open-source, and MIT-licensed. You can run it right now with a single command.

“Ship with confidence.”

What it actually checks

DeployReady combines static analysis of your code with dynamic testing of your running app. That combination matters: some risks are only visible in the source, and some are only visible when the application is actually serving requests.

• →Secrets detection — hardcoded API keys, tokens, and credentials
• →OWASP Top 10 patterns, weak cryptography, and XSS-prone code
• →Dynamic probes against localhost: auth bypass, exposed routes, missing security headers, permissive CORS
• →Architecture and performance signals, including slow endpoints
• →A 0–100 readiness score with critical / warning / info breakdown

Run it in one command

There is nothing to install. Point it at your project and it detects your stack, maps your routes, and runs the full scan.

• →No install: npx deployready@latest ./my-app
• →Global install: npm install -g deployready
• →CI/CD: run in GitHub Actions and fail the build on critical issues with --fail-on critical
• →Offline: run with --no-ai for fully local analysis, or use Ollama

Local-first and privacy-respecting by design

All static analysis runs entirely on your machine. The AI layer is optional — and when you enable it, DeployReady sends only structured findings with secrets redacted, never your raw source. It works with Claude, OpenAI, or a fully offline local model through Ollama. API keys are stored with restricted file permissions, and dynamic testing is limited to loopback by default.

Fixes you approve, not magic you trust blindly

When AI analysis is enabled, DeployReady suggests concrete before-and-after code changes. You review and approve each one before anything is applied. That reflects how we think about AI in engineering generally: it accelerates the work, but a human stays in control of what actually ships.

Why we built it

Security-first engineering is core to how Belsoft builds software. Every project we deliver follows a baseline of input validation, managed authentication, secrets hygiene, dependency auditing, and security headers. DeployReady is that discipline packaged into a tool — so any team can apply the same pre-deployment checks we run on our own work.

Frequently Asked Questions

Is DeployReady free?

Yes. It is open-source and MIT-licensed, available on npm. The AI-assisted analysis is optional and uses your own model provider or a local model.

What languages and frameworks does it support?

It supports JavaScript and TypeScript applications, including Python codebases, and detects your stack automatically. It runs on Node.js 18 or later.

Does it send my code to the cloud?

No. Static analysis runs locally. The optional AI layer sends only structured findings with secrets redacted — or you can run it fully offline with a local model.

Can I use it in CI/CD?

Yes. DeployReady integrates with GitHub Actions and supports one-shot commands and flags like --fail-on critical to block deployments when serious issues are found.

Try it today

DeployReady is live now. Run npx deployready@latest ./my-app against your project, or explore the source on GitHub. We are actively developing it and welcome issues, feedback, and contributions.

“The cheapest production incident is the one you caught on your laptop before deploy.”