What Does a Code Audit Include?
A professional code audit is more than running a linter. It is a comprehensive expert review of your application's source code, architecture, and infrastructure — with specific focus on the risks that AI-generated code introduces. Here is the complete breakdown of what a code audit covers.
Authentication & Authorization
We review every login, session, token, and permission check in your application. Common findings: JWT validation done wrong, session tokens not rotated after login, broken role-based access control that lets lower-privilege users access admin routes, missing re-authentication before high-value actions (transfers, account deletion, password change), and OAuth flows that can be replayed or hijacked.
API Security & Endpoint Review
We test every API endpoint for: missing authentication, missing authorization (can user A access user B's data?), over-permissive CORS, missing rate limiting, verbose error messages that leak stack traces or schema, and insecure direct object references (IDOR). AI-generated REST APIs frequently have IDOR vulnerabilities where changing a numeric ID in the URL returns another user's data.
Data Handling & Database Security
We audit all database queries for injection vulnerabilities (SQL injection, NoSQL injection), look for unparameterized queries, check whether sensitive data is encrypted at rest and in transit, verify that personally identifiable information (PII) is not logged or exposed in error messages, and review backup and deletion procedures.
Payment & Billing Logic
For apps using Stripe, Paddle, or other payment processors: we verify webhook signature validation, idempotency key implementation, subscription state machine correctness, refund and cancellation edge cases, race conditions in payment flows, and whether free-tier limits can be bypassed. Payment logic bugs are the single most expensive class of bug in vibe-coded SaaS.
Secrets & Credentials Management
We scan the entire codebase and git history for hardcoded API keys, database passwords, service tokens, and private keys. AI coding tools frequently suggest putting secrets directly in code or config files. We also review your environment variable handling, .gitignore configuration, and CI/CD secret injection.
AI & LLM Layer (for AI-native apps)
Apps built on OpenAI, Anthropic, or other LLM APIs get an additional layer of review: prompt injection vulnerabilities, data leakage across user contexts, system prompt exposure, unbounded token spend that can drain your API budget, unsafe tool execution in agentic workflows, and RAG pipeline data isolation.
Infrastructure & Deployment
We review your deployment configuration, cloud IAM roles and permissions, exposed ports and services, server hardening (SSH config, firewall rules), SSL/TLS configuration, and dependency versions for known CVEs.
What You Receive
At the end of the audit you receive a prioritized finding report with: severity classification (Critical / High / Medium / Low), exact file and line number references, explanation of the vulnerability and its exploit path, a concrete recommended fix, and an executive summary suitable for investors or enterprise procurement. Critical and High findings are patched directly in most engagements.