The Free AI Security Audit That Never Uploads Your Code

There's an uncomfortable irony in most security tools: to check whether your code is safe, they ask you to send all of it to their servers. Your proprietary logic, your architecture, and — more often than anyone admits — the secrets sitting in your repo all get copied to someone else's infrastructure, where they're subject to that vendor's breaches, retention policy, and access controls.

For a lot of teams that's a non-starter. Regulated industries can't do it. Startups guarding their edge don't want to. And anyone who's read enough breach post-mortems knows that "we uploaded our whole codebase to a third party" is a sentence that shows up in a lot of them.

You don't have to make that trade. Here's how to run a real AI security audit that stays entirely on your machine — free, and without your code ever leaving your control.

The idea: bring the audit to the code, not the code to the audit

The shift that makes this possible is that the AI is already on your side of the wall. You have a coding agent — Claude Code, Cursor, Codex — that already reads your repository locally, every day. The intelligence needed to audit code is right there, running where the code is.

So instead of shipping your code to a scanner, you give your local agent a scanner's instructions: a structured, expert prompt that tells it exactly what security weaknesses to look for. The agent reads your files in place, does the audit, and writes the report to your disk. Nothing leaves the machine.

That's the whole model. The code stays put; only the expertise travels — as a prompt.

How to run it

You need an AI agent that can read your repo, opened at the project root. Then:

npm install securenow

Go to /threat-modeling, which publishes a free threat-modeling prompt for each of 25 security categories — authentication, the OWASP API Top 10, injection, cloud/IAM, AI/LLM features, and more. Copy the prompt for the category that matters most to your app and paste it into your agent.

The agent inventories your code, enumerates the threats, audits your real files, and writes four files into a local threat/<category>/ folder:

• Two code-findings files (HTML + Markdown) — the audit, with every weakness pinned to a file:line.
• Two detection-and-mitigation files — the runtime rules that would catch each threat.

Open the HTML files by double-clicking them. They're self-contained — no server, no internet, no trackers — so they work offline. (Full walkthrough: how to audit your app's security with AI.)

What "local-first" actually guarantees here

It's worth being specific, because "private" is a word every vendor uses:

• No code upload. The agent reads your files where they are. SecureNow never receives your source.
• The reports are local and self-contained. The generated HTML has no external requests and no trackers — it renders from your disk.
• It audits, it doesn't edit. The prompt is read-only by design. It describes fixes; you decide what to change. Nothing is silently rewritten.
• The only optional network call is to your own account. If you run npx securenow login, the CLI talks to your SecureNow account to ground the detection rules in your real rule names and columns. That's optional, it's your account, and it never carries your source code.

If you skip the login entirely, the code-findings audit still runs — fully offline, fully free.

Free, and why that's not a catch

The prompts are free to copy and run. Generating the reports costs nothing beyond your own agent usage. There's no seat license, no per-scan fee, and no "book a demo" wall in front of the actual audit.

The honest business model: SecureNow makes money when you decide to turn the detections into always-on runtime rules — catching attacks in live traffic, blocking malicious IPs, rate-limiting abused endpoints. That platform has a free tier too. But the audit itself — the part that finds the vulnerabilities in your code — is free and local because there's no reason it shouldn't be.

When you'd still want a human

A local AI audit is a genuine first pass, not the last word. It's excellent at pattern-based vulnerabilities and at consistent coverage across every route, and it's fast enough to run on every release. It's weaker at deep business-logic flaws and multi-step exploit chains, and it can't confirm exploitability the way a penetration test can.

The right way to think about it: a local, free, private AI audit does the tireless 90% so that if you do bring in human expertise, it goes to the hard 10% — instead of to the SQL-injection-in-line-53 that a machine should have caught. And if you don't have a security team at all, this is the highest-value hour you can spend without one.

Start now, nothing to sign up for

• Install: npm install securenow
• Copy a prompt: /threat-modeling
• Paste it into your agent at your project root
• Open the report it writes to threat/<category>/

Your code never leaves your machine, and you'll have a real security audit before you've finished deciding whether you trust it. Browse the 25 free prompts →