Vibe Code Rescue: Hardening an AI-Generated MVP
Auditing and hardening an AI-generated application before launch, from security review to go-live readiness.
Representative scenario based on the kinds of projects AWZ handles. Client names and proof are private. Targets are agreed and measured per project — published figures are not audited outcomes.
Representative client profile
Startup founder
Understanding the Problem
Non-technical founders built an MVP with AI coding tools. It worked locally but had security and correctness concerns — leaked credentials, missing validation — that needed review before launch.
How We Solved It
We ran a scoped code review and hardening pass: environment handling, input validation, authorization checks, and CI scanning. Specific findings and timelines are captured per project, not generalized.
What We Measure
These are the measures we would define and validate with the client. They are not published client results.
Findings
The number and severity of findings depend entirely on the codebase delivered; never a fixed count.
Time to readiness
Depends on scope and the state of the starting code; not a fixed-day commitment.
Security posture
Tested controls and residual gaps are documented per project; no blanket rating or certification claim.
Incidents post-launch
Monitoring runs over time; zero incidents cannot be promised for any software.
Technologies Used
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