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A build that compiles has passed a functional checkpoint, not a security review. Before launch, spend an afternoon tracing the app’s most sensitive data and actions, checking its highest-risk code and delivery paths, and recording what still needs fixing. Treat that as focused triage—not a guarantee that every flaw has been found or a substitute for deeper review when the stakes are high.
Why a working build still needs a security review
AI-generated code deserves the same scrutiny as code from an unfamiliar contributor. The reviewer needs to understand what the code does before approving it; in particular, check for missing authorization and inadequate input validation. OWASP’s Secure Coding with AI Cheat Sheet and Secure Code Review Cheat Sheet offer guidance for reviewing AI-assisted work and code generally.
Automated checks can reveal known vulnerable dependencies, suspicious code patterns, or possible secrets. Passing them does not prove that the app is safe: a scanner cannot reliably determine whether a user should be allowed to perform a particular business action or access a particular record. Pair automated checks with a human review of the code paths and the app’s intended behavior.
There is no established universal rule that an afternoon is enough. Use the time to find and prioritize meaningful risks, then decide whether the evidence supports release or requires more work.
#1 Best Overall
Choose what to inspect by risk
Start with what the app exposes and what could be harmed. The following lenses are a practical way to rank review effort, not a formal scoring formula.
| Risk lens | Ask | Why it changes priority |
|---|---|---|
| Exposure | Is the route or component public, or limited to a private environment? | A reachable public entry point can be attacked by anyone who can access it. |
| Data sensitivity | Does it handle ordinary content, personal data, credentials, payment information, or regulated data? | More sensitive data raises the potential harm from disclosure or misuse. |
| Privilege | What can the user, service, coding agent, CI job, or deployment identity do? | Broad permissions can turn a small flaw into a larger compromise. |
| Trust boundary | Where does data or authority cross between browser and API, app and database, app and provider, repository and agent, or CI and deployment? | Boundary crossings are places where assumptions about input, identity, and permission can fail. |
| Blast radius | Could an error affect one record, all tenants, or production infrastructure? | The potential scope of harm helps determine whether a finding blocks release. |
Make a quick data-flow sketch: note the app’s public entry points, identity provider, storage, third-party services, AI components and tools, and deployment boundary. Mark data that comes from users, external services, repositories, or other untrusted sources. Threat modeling is among the verification techniques described in NISTIR 8397.
Work through the review in a deliberate order
This sequence is a practical afternoon plan, not a schedule prescribed or validated by NIST or OWASP. Adapt it to the app’s size, data sensitivity, and exposure. If the critical paths cannot be understood or checked in the available time, record that as unresolved work rather than treating the deadline as evidence of safety.
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List the important data and actions: for example, reading another user’s record, changing account settings, exporting information, or triggering a payment or administrative operation. Identify which routes and components can reach them. Include AI features and tools if the app has them, and note which inputs or instructions they may receive.
This gives the review a concrete target: the route, identity, data, and permission involved in each sensitive action. It also helps you choose which paths to trace first if time is limited.
2. Run broad, low-cost checks
- Inspect the dependency manifest and lockfile. Confirm that each newly added package is the intended package, is needed, and is not a similarly named or otherwise unintended dependency.
- Run the language-appropriate dependency audit, static analysis, and secret-detection checks available to the project. Review findings rather than assuming every alert is exploitable or every clean result is proof of safety.
- Inspect configuration and deployment definitions for unintended public exposure, excessive permissions, or secrets forwarded into places that do not need them.
OWASP specifically flags hallucinated or outdated dependencies as a concern in AI-assisted work. Dependency checks can identify known issues; they do not establish whether a package is appropriate for the app’s use.
3. Trace login, authorization, and sensitive paths by hand
Follow the route from request to action, paying special attention to authentication and authorization. For each sensitive route or object, ask:
- Is the identity established correctly, and are sessions and credentials stored, protected, and invalidated safely?
- Does the server check that this specific user may perform this specific action on this specific object? Being logged in alone is not authorization.
- Are sensitive actions re-authenticated where appropriate?
- Does external input get validated at the boundary? Are database queries parameterized and output encoded for its context?
- Are file paths, URLs, and deserialized data constrained so input cannot redirect the app into unintended resources or operations?
- Could credentials, tokens, or personal data appear in source, logs, or error messages?
Prioritize paths that combine public exposure, sensitive data, or broad privileges. A check in the browser interface is not a substitute for a server-side permission check. OWASP’s secure code review guidance describes review as an examination of code and its security-relevant behavior.
4. Inspect the coding-agent and delivery boundary
Review changes beyond application source code: package scripts, build and release scripts, Dockerfiles, CI workflows, agent instructions, hooks, and tool configuration. Ask whether a change introduces network access, downloads and executes external content, forwards secrets, widens permissions, or enables automatic approval.
Rank #4
Keep the coding agent’s permissions, credentials, network access, and tool access limited to what it needs. Treat repository instructions, external content, and tool responses as untrusted input; they may influence an agent that can act on files or services. OWASP’s IDE and AI-Assisted Development Security guidance addresses these risks, which are separate from defects in generated application code.
5. Record findings so someone can act on them
For each issue, write down the affected route or component, the evidence observed, the potential impact, a fix owner, and how the change will be retested. Separate confirmed problems from questions that could not be resolved during the review. A finding without a clear location or reproduction path is harder to verify and fix.
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Use standards as checklists, not safety certificates
NISTIR 8397, Guidelines on Minimum Standards for Developer Verification of Software, was published by the National Institute of Standards and Technology in 2021. It presents a broad menu of verification techniques, including threat modeling, automated testing, static code scanning, heuristic secret detection, built-in checks, black-box and structural test cases, historical cases, fuzzing, web-application scanning when applicable, and review of included libraries, packages, and services. Not every technique fits every small app; use the guidance to identify relevant checks rather than implying that a short review satisfies them all.
Best Value
For an app that includes AI or agents, OWASP AISVS 1.0 was released in June 2026. OWASP describes it as 191 requirements across 12 chapters and three appendices, with verification levels 1, 2, and 3. Its areas include input validation, deployment security, access control, model supply chain, output control, vector database security, agent orchestration, MCP security, adversarial robustness, monitoring, and AI-assisted coding controls. AISVS is intended to complement general application, infrastructure, and supply-chain checks—not replace them. See the OWASP AISVS documentation for the standard.
Decide whether the app is ready to ship
End with a written outcome that names unresolved risks and who owns them. Block release or escalate for a deeper review if you find unresolved high-risk problems involving authentication, authorization, exposed secrets, unintended public access, or a compromised delivery path. A human who understands the code should approve it; do not treat a successful build, a clean scanner run, or the end of the afternoon as that approval.
No reliable prevalence figure is established here for how often AI-built applications contain vulnerabilities. A percentage without its study population, task, model or tool, review method, and publication date would not tell you the risk in this app. Base the release decision on the evidence in the app’s own code, configuration, and data flows.
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