No all technical debt lives in your codebase. Some of it hides in your infrastructure, in your IAM roles, in Slack messages from engineers who no longer works at your company or in decisions made three re-orgs ago that nobody documented.

And that kind of debt, the kind you don't track, can't grep for, and only notice when something breaks, is the most dangerous kind of all.

We Think Debt Looks Like...

When most teams talk about technical debt, they're referring to code: duplicate logic, unrefactored files, a long-abandoned migration branch, or that comment that says // TODO: fix this later and never got revisited. This is the visible debt. You can find it in your version history, your backlog, your code review comments. It's annoying, sure but at least you know it exists.

But That's Just the Surface

The truly dangerous debt is buried deeper. It might be a cloud permission that was over-scoped during a sprint crunch, an API that's still public-facing because no one updated the ingress rules, or an auth system that assumes "internal IP equals trusted." It could be a CI/CD pipeline that pulls secrets from an unmonitored location, or a service that works, but no one remembers how or why it was built the way it was.

These things aren't tracked. they aren't tagged in Jira. No one writes postmortems about them until they explode. and by the time they do, they've already cost you far more than you saved by "moving fast."

The Cost of Invisible Tech Debt

Unlike code debt, invisible debt accumulates quietly. it slows down onboarding because nothing is documented. it causes outages when infrastructure doesn't behave as expected. it opens attack surfaces your security team never modeled. it kills velocity not in weeks, but in years as every decision becomes harder to make because no one fully understands the system anymore.

Security teams often feel this first. They inherit legacy decisions without context, get pulled into reviews for systems they've never seen, and are expected to secure code that was never built to secure in the first place. You don't notice this debt until you're in an incident call at 2 AM, trying to figure out why the backup system is failing or worse, who owns it.

Why This Kind of Debt Happens

Some causes are unavoidable: fast pivots to hit market timing, startups prioritizing MVPs over best practices, senior developers leaving without knowledge transfer. But more often, the problem isn't speed it''s silence. Teams don't talk about the tradeoffs they're making. No one keeps a ledger of "intentional shortcuts." And when those decisions get buried, they rot.

Making the Invisible Visible

Smart teams start to surface this kind of debt by tracking "non-code" debt just like feature work legacy infrastructure, weird IAM rules, duct-taped deployment scripts everything is logged. They encourage institutional curiosity so that asking "why does it work this way?" is a safe and welcomed question. Ownership is assigned even for the ugly things, so that someone is responsible for the legacy monolith of the outdated service, even if the plan is to sunset it. Security is included in architecture reviews not just to approve things, but to catch unspoken assumptions. Engineers are given space and time to document, diagram, and map the systems they work in.

This doesn't mean invisible debt disappears, but at least it becomes visible. And visibility is the first step toward control.

The most dangerous tech debt isn't dirty code it's unspoken assumptions. The things we think we understand but never documented. The systems that just "work" until they don't. The old access roles, unowned endpoints, ghosted services, and forgotten logic.

If your team only treats tech debt as a code cleanup problem, you're not solving the right problem. You're just polishing the surface while the foundation cracks below.

You can't fix what you can't see. So start looking.

Written by Jade Hutchinson, Founder of JAH Cybersecurity Consulting