We are drowning in code.
It used to be that a Senior Engineer could keep a mental model of the entire codebase in their head. They knew where the skeletons were buried. They knew that if you touched the UserSession class, you had to check the AuthMiddleware.
Then came the AI.
Now, a junior developer with Cursor can generate 500 lines of boilerplate in seconds. It compiles. It passes the unit tests. It looks perfect.
And it is completely insecure.
The Illusion of Safety
For the last decade, we relied on SAST (Static Application Security Testing). Tools that grep your code for patterns. They look for eval() or unparameterized SQL queries.
SAST is great for catching typos. It is terrible for catching logic.
An AI doesn’t make typos. It writes syntactically perfect code that accidentally exposes your admin routes to the public because it hallucinated a middleware configuration. SAST looks at that valid configuration object and says, “Looks like valid JSON to me. LGTM.”
You cannot grep for hallucinations.
The “Shift Left” Lie
We tell Security Engineers to “Shift Left.” We tell them to catch bugs earlier.
But how?
You can’t run a penetration test on a markdown file. You can’t run an OWASP ZAP scan on a diff. To find behavioral vulnerabilities—the kind AI generates—you need a running application.
Historically, you only got a running application in Staging. By then, the code has already been merged. It’s mixed with twenty other commits. Untangling the vulnerability takes days.
So the Security Engineer becomes the “Blocker.” They are the ones saying “No” at the end of the sprint because they finally got a chance to scan the app and found a critical issue.
Evidence Over Text
We need to stop treating security reviews as code reviews. They are behavior reviews.
If you suspect a vulnerability, you shouldn’t be staring at lines of text trying to simulate the runtime in your brain. You should be sending a malicious payload to a real endpoint and seeing what comes back.
This is the missing link in the AI era: Dynamic Verification per PR.
Imagine this workflow:
- A developer (or their AI agent) opens a Pull Request.
- Instantly, a fully isolated environment spins up. It has a real database, real API, real network.
- Your security pipeline automatically runs a lightweight DAST scan against that specific URL.
- If the scanner gets a 200 OK on
/admin/delete-users, the PR is blocked.
No humans involved. No arguments about “false positives.” Just a red X and a log file showing the exploit worked.
The Sandbox is the Shield
This is why we built PrevHQ.
We didn’t just build it so designers could check pixel padding. We built it so Security Engineers could sleep at night.
PrevHQ gives you a Security Sandbox for every single change. It turns your Pull Request from a text file into a target.
In the age of AI, you cannot trust the code. You can only trust the behavior.
Don’t just read the diff. Attack it.