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AI App Production Readiness Review

Replace “it worked in the preview” with a review that records what passed, what failed, what remains unknown and why a check does not apply. Select the app features, attach concise evidence references, then export a review for the release discussion.

Boundary: this tool does not scan your app, certify security, perform a penetration test, assess legal compliance or approve a deployment. It organizes human review evidence. Unknown release blockers remain blockers.

Build the release evidence record

Inputs stay in this browser and are not stored by EasyTool.

NO SIGNUP · NO UPLOAD
Keep secrets out. Record a ticket, test run, commit, dashboard or owner—not tokens, passwords, personal data, raw logs or private payloads.

1. Choose the app surface

The profile changes which checks apply. Start with a preset, then adjust it.

RELEASE DECISION SUPPORT

Calculating review…

0/0 · 0%evidence coverage, not a security score
0Pass
0Fail
0Unknown
0N/A

Current blockers or next evidence

  • Choose a profile to start.

2. Record the evidence

Pass means verified evidence exists. Fail means the control is not met. Unknown means it was not tested or evidence is missing. N/A resolves only when a reason is recorded.

3. Export for review

Read the report before sharing it; your notes may refer to internal systems.

No report exported yet.

Why preview success is not production evidence

AI-generated apps can reach a convincing happy path very quickly. That preview proves only that one path worked with one set of data and permissions. Production adds hostile input, multiple identities, concurrent requests, expiring credentials, migrations, provider failures, support duties and irreversible user impact. A generated interface can hide a client-only authorization check, a permissive database rule or a fabricated dependency just as easily as it can produce a useful component.

A defensible release review therefore asks for observable evidence. “The framework handles it” is an assumption. A dated negative-path test, reviewed policy, restore exercise or exact deployed revision is evidence. This checklist intentionally has no weighted readiness score: averaging unrelated controls can let ten cosmetic passes conceal one missing authorization boundary.

Four complementary layers

Technical verification

OWASP ASVS 5.0.0 provides a basis for testing application security controls and for stating secure-development requirements. This review borrows its evidence-first mindset across authentication, authorization, validation, data protection, APIs, configuration and logging; it is not an ASVS assessment.

Secure development

NIST SSDF 1.1 describes high-level practices that can be integrated into a development lifecycle. Ownership, protected source, vulnerability response and root-cause improvement matter even when generated code passes a test today.

Supply-chain traceability

SLSA 1.2 separates source and build tracks and uses provenance to increase confidence about how an artifact was produced. A lockfile alone does not prove that the deployed artifact came from reviewed source through a protected build.

Secure-by-design ownership

CISA Secure by Design emphasizes responsibility for customer security outcomes, transparency and safe defaults. Users should not need to discover that a generated app shipped broad permissions or dangerous defaults.

How to use Pass, Fail, Unknown and N/A

Mark Pass only after the stated behavior was verified in a production-like context. Mark Fail when a requirement is missing or a test demonstrates unsafe behavior; the report then recommends holding the release. Leave Unknown when nobody has run the check or when evidence cannot be located. Unknown is honest and useful—it prevents an assumption from silently becoming approval.

Use N/A only when the selected app genuinely has no relevant surface, and write the reason. For example, a static documentation site without identity does not need account-session tests. “The AI said this is handled” is not an N/A reason. The tool counts an unexplained N/A as unresolved.

Release blockers versus important checks

Release blockers cover failures that can invalidate the basic safety of the launch: authorization, secret exposure, unverified generated dependencies, destructive data changes, recovery, critical testing, incident ownership and rollback. Important checks still deserve owners and evidence, but teams may make a documented, time-bounded risk decision about them. This distinction is editorial guidance, not a universal standard; change the final decision to match the app, threat model, contractual duties and regulatory context.

Feature profiles prevent generic checklist theater

A static public site, authenticated SaaS product, payment service and tool-using AI agent do not have identical attack surfaces. Selecting accounts adds session and authorization checks. Databases add migration and restore evidence. Payments and webhooks add authenticity, replay, idempotency and reconciliation. AI features add prompt-injection boundaries, provider data handling, output validation, tool allowlists and versioned evaluations. Always-on checks—such as human review, secrets, generated packages, testing and rollback—remain relevant even for a small app.

AI-generated code needs a provenance habit

Generated code often embeds unstated assumptions: an endpoint may trust a browser-provided role, a package name may be nonexistent or impersonated, or an agent tool may inherit permissions broader than its task. Review each new dependency against an authoritative registry and repository. Inspect the exact diff, record acceptance criteria, require tests across trust boundaries and keep the deployed artifact traceable to a reviewed revision. For consequential AI actions, constrain tools and arguments and add human approval where the impact cannot be safely reversed.

Privacy, storage and export limits

The checklist is assembled in your browser. EasyTool does not receive or store the project name, selected features, statuses or evidence notes. Refreshing the page clears the review unless the browser restores form state. Markdown and JSON exports are created locally. Because downloaded files can still leave the device when you share them, use references rather than copying secrets, customer data, access tokens or sensitive logs.

The exported verdict describes checklist evidence completeness at that moment. It does not guarantee the absence of vulnerabilities, continuing control effectiveness or legal compliance. Re-run the review when code, infrastructure, data flow, dependencies, model, prompt, permissions or deployment process changes.

Primary sources and review date

Editorial review: 2026-08-02. Standards and guidance evolve; verify the current source and use qualified security, privacy and legal reviewers where the impact warrants it.