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Security Review Checklist

Interactive AI safety tool

Security Review Checklist

Review secrets, permissions, dependencies, data, auth, payments, testing, deployment, monitoring, rollback, and human approval before asking Codex or another AI coding agent to change real projects.

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Short answer

What should an AI coding security review include?

A useful security review checklist covers prompt scope, inspect-first workflow, secrets, environment variables, data collection, privacy, dependencies, permissions, auth, payments, API keys, tests, deployment, monitoring, rollback, and human approval. It should produce evidence, not just confidence.

Risk profiler

Choose the review depth before Codex edits anything

Risk readout

Select the surfaces this task touches

The deeper review is for work involving secrets, users, payments, auth, production, dependencies, or agent permissions.

Guided checklist

Run the review by phase

Each item includes the why, a pass/fail example, and a direct way to ask Codex for evidence.

Before Prompting

A safer AI task starts with scope, context, and limits before any code changes happen.

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Before Editing

Inspection-first work keeps AI from fixing the wrong layer.

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Secrets & Environment

Most beginner security failures are exposed keys, copied credentials, or mixed environments.

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Data & Privacy

AI-built forms and tools often collect more data than the job requires.

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Dependencies

Packages and snippets can add supply-chain, licensing, speed, and maintenance risk.

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Auth & Permissions

Authentication, roles, and admin access are high-impact even when the UI change looks small.

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Payments/API Keys

Money flows and external APIs need explicit test mode, secrets handling, and failure states.

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Testing & QA

Security review is incomplete until the actual risky paths are exercised.

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Deployment

Deployments can change environment, caching, indexes, routes, and public exposure.

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Monitoring

Some problems only appear when real visitors, crawlers, and integrations arrive.

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Rollback

A rollback path turns a bad release into a controlled recovery.

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Human Approval

AI can assist review, but people own claims, risk, privacy, money, and publishing.

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Safe Codex prompt builder

Turn the review into a scoped task prompt

Red flags

Unsafe requests and safer rewrites

Red flagSafer move
Pasting secrets into a promptUse placeholder names and ask for env variable wiring without sharing values.
Editing production directlyUse a branch, preview, staging copy, backup, or copied snippet first.
“Fix security” with no scopeName the exact system, files, risks, tests, and approval gate.
Broad rewrite for a small riskAsk for inspection, smallest safe fix, and a rollback note.
Fake links, pricing, stats, or testimonialsOnly publish verified claims or label unknowns for human review.
Unreviewed package installRequire reason, source, version, alternatives, audit, and removal path.
Auth changes without role testsTest allowed, denied, logged-in, logged-out, and expired-session states.
No rollback planWrite the exact restore, revert, disable, or removal path before publish.

Role paths

Use the right checklist lens for your job

Copyable templates

Mini-prompts for safer AI review

Pre-edit inspection

Before editing, inspect the relevant files, URLs, settings, dependencies, and recent errors for [TASK]. Summarize the current behavior, likely files, security risks, unknowns, and what you will not change. Do not edit yet.

Dependency review

Review the proposed dependency or external script: [NAME]. Explain why it is needed, safer alternatives, permissions, bundle impact, supply-chain risk, license concerns, failure states, and how to remove it if it causes trouble.

Secrets audit

Audit this change for exposed secrets without printing secret values. Check commits, diffs, browser bundles, page source, env usage, logs, screenshots, docs, and examples. Report locations and remediation steps.

PR review

Review this PR for security, privacy, auth, data handling, dependency, deployment, test coverage, and rollback risks. Lead with blockers and high-risk issues, then summarize checks passed and remaining questions.

QA pass

Run the available lint, test, build, and browser checks for this change. Verify desktop, mobile, keyboard basics, forms/buttons, copy states, error states, and console output. Summarize evidence and gaps.

Rollback

Create a rollback plan for this change. Include triggers, exact revert/restore steps, owner, affected services, cache or deployment steps, data concerns, and post-rollback checks.

Human approval

Prepare a human approval note: outcome, changed files/settings, security/privacy risks, tests run, links verified, secrets check, deployment target, rollback plan, and any claims that need manual verification.

Examples

What good looks like before you ship

Safe request

Inspect the lead magnet page and related form code. Do not edit yet. Tell me if any secrets, privacy mismatches, broken mobile states, fake claims, or rollback gaps exist.

Risky request rewritten

Instead of “fix auth and deploy,” ask for an auth inspection, role matrix, test plan, branch-only fix, and human approval summary before production.

Filled-out review sample

Branch: security-review. Files: form template, env docs, analytics script. Must not change: pricing or auth. Tests: lint, form submit, mobile, console. Rollback: revert commit and restore previous form block.

Printable version

Compact approval checklist

  1. Safe workspace, branch, backup, or preview exists.
  2. Scope, allowed changes, forbidden changes, and done-when criteria are written.
  3. No secrets, private data, credentials, or unsupported claims are in prompts or commits.
  4. Dependencies, auth, payments, data, and API surfaces are reviewed if touched.
  5. Tests, QA, deployment checks, monitoring, rollback, and human approval are documented.

Resources

Keep security review connected to the build workflow

FAQ

Security review checklist questions

Can I trust AI-generated code after this checklist?

No. Treat AI output as a draft. The checklist helps you scope, inspect, test, and approve work, but humans still own security, privacy, claims, and production release decisions.

What is the most important AI coding agent security rule?

Do not share secrets and do not let the agent edit production without a recoverable path. Use placeholders, environment variables, branches, previews, backups, and human approval.

Should beginners let Codex change authentication or payments?

Only with extra review. Auth, payments, API keys, private data, webhooks, and admin permissions are high-risk surfaces that need tests, logs, sandbox mode, and human approval.

How is this different from a website launch checklist?

A launch checklist checks whether the site works. This security review focuses on AI-assisted change safety: prompts, permissions, secrets, dependencies, data handling, production risk, approval, and rollback.

Can I use this for client work?

Yes, but client projects need written scope, approval, data boundaries, backups, and a rollback path. Do not paste client secrets, private records, credentials, or confidential strategy into AI prompts.

When do I need professional security help?

Get qualified help for regulated data, healthcare, finance, children’s data, enterprise SSO, complex permissions, payment architecture, incident response, or any launch where a breach would cause serious harm.