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Rivac AI Labs
Security, Risk & Compliance

AI-Generated Code Security Auditor

AI coding tools ship fast and confident, but they don't know your security context, they'll happily hardcode an API key, skip a row-level-security policy, or leave a prompt-injection sink wide open if that's the pattern their training data suggested. This service audits AI-assisted and vibe-coded applications specifically for the failure patterns these tools produce: hardcoded secrets, missing or broken database-level access controls, and injection points where untrusted input reaches a model or a privileged action. It's for teams that shipped fast with AI-assisted or no-code tools and now need someone to verify what actually got built before it handles real customer data. The result is a concrete list of exploitable gaps specific to how the app was built, not a generic pentest checklist.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

  1. 1

    Diagnose the codebase and stack to identify which AI-generation patterns and tools were used and their known failure modes.

  2. 2

    Pilot targeted checks against the highest-risk surfaces first, authentication, data access policies, and any AI-facing input.

  3. 3

    Review findings with the team, distinguishing exploitable issues from theoretical ones so fixes get prioritized correctly.

  4. 4

    Deliver the full audit report and verify remediations before the application handles production data.

What You Get

Deliverables from this engagement

  • Audit report covering hardcoded secrets, RLS gaps, and injection sinks
  • Prioritized remediation list specific to the AI-generated codebase
  • Verified fixes for critical and high-severity findings
  • Guidance for safely continuing AI-assisted development

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Manual Code Review

  • AI Generated Repository
  • Manual Review of Vibe Coded Files
  • Framework and Tooling Fingerprint Check

Basic Scanning

  • Single Secrets Scanner Run
  • Manual Database RLS Policy Check
  • Manual Input Validation Review

Findings

  • Hardcoded Secret Found
  • Missing Row Level Security Found
  • Prompt Injection Sink Found

Reporting

  • Markdown Findings Document
  • Fix Priority List Delivered
  • Client Walkthrough Call

Cloud-Native / Managed Services Architecture

Managed Scanning SaaS

  • Managed SAST and Secrets Scanning SaaS
  • Database RLS Policy Linter
  • Dependency Vulnerability Scanner

Cloud Test Environment

  • Cloned Supabase or Postgres Project
  • Mirrored Production Environment
  • Seeded Test Dataset

Analysis

  • Findings Aggregated in Dashboard
  • Injection Sink Mapping
  • Severity Scoring per Finding

Reporting

  • Audit Report Generated
  • Prioritized Fix List
  • Client Review Session

Event-Driven & Automation-First Architecture

Triggers

  • Audit Kickoff on Repository
  • Fix Commit Pushed
  • Scheduled Rescan

Automated Detection

  • Auto Detect AI Generation Fingerprints
  • Parallel Secrets RLS and Injection Scans
  • Findings Auto Aggregated

Ticketing

  • Auto Ticket Created Per Finding
  • Severity Auto Assigned
  • Owner Auto Assigned

Retest Loop

  • Retest Auto Triggered on Fix Commit
  • Finding Marked Resolved
  • Client Notified of Closure

Enterprise-Grade & Compliance-Ready Architecture

Formal Sign Off

  • Sign Off Gate Before Production Data Migration
  • Second Auditor Pass on Critical Findings
  • Client Stakeholder Sign Off

Audit Trail

  • Audit Trail of All Findings and Fixes
  • Redundant Review for High Risk Items
  • Version Controlled Findings Log

Compliance Mapping

  • Data Protection Impact Assessment
  • Access Control Hardening Verification
  • Retention and Deletion Policy Check

Clearance

  • Application Cleared for Production Data
  • Ongoing Monitoring Plan Established
  • Follow Up Audit Scheduled

AI-Augmented, Human-in-the-Loop Architecture

Codebase and Config

  • AI Generated Codebase
  • Database Schema and Policies
  • LLM Integration Points

AI Auditor Tooling

  • AI Scans for Hardcoded Secrets
  • AI Flags Missing RLS Policies
  • AI Maps Prompt Injection Sinks

Security Auditor Approval Gate

  • Auditor Manually Validates Each Finding
  • Auditor Confirms Exploitability
  • Auditor Documents Reproduction Steps

Outcome

  • Approved Findings in Final Report
  • Discarded Non Exploitable Finding
  • App Cleared for Production Customer Data

Integration-Heavy / Ecosystem-Connected Architecture

Client Ecosystem

  • GitHub or GitLab Repository
  • Supabase or Postgres Database
  • CI CD Pipeline
  • Production Monitoring

Audit Program Core

  • Security Audit Workflow
  • Remediation Verification
  • Fingerprint Detection Engine

Two Way Sync

  • RLS Policy Inspection from Database
  • Findings Synced to Ticketing
  • LLM Provider Logs for Injection Mapping

Ongoing Guidance

  • Guidance for Safe AI Assisted Development
  • Follow Up Audit Scheduled

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Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about AI-Generated Code Security Auditor

Most engagements like this start as a $500–$2,500 pilot, see full pricing.

Questions? Book a free call