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Review AI-generated code as you would a change from an unfamiliar contributor: understand the complete diff and its intent, increase scrutiny at trust boundaries, run automated checks, test security properties independently, evaluate web accessibility with both tools and human judgment, and require a named human owner to approve and maintain the result.
Can you trust AI-generated code?
Trust is not a property that code receives because a model produced it. An AI assistant can generate useful implementation quickly, but it can also introduce an authorization gap, an unsafe dependency, an exposed secret, a misleading test, or an inaccessible interaction. The person who merges the change remains responsible for its correctness, security, accessibility, and maintenance.
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The OWASP DevSecOps Guideline states that generated code needs at least the same scrutiny as code from an unknown contributor. Its Secure Coding with AI Cheat Sheet makes the accountability requirement explicit: AI-generated code must have a human owner. Treat those statements as operating rules for every pull request, not as a special exception for large systems.
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Set the review target before reading the implementation
Define the requested behavior
Write down what the change is supposed to do and what it is explicitly not supposed to do. Use the issue, design note, acceptance criteria, or product requirement as the reference. This gives you a way to compare the implementation with its intent instead of judging whether the generated code merely looks plausible.
- Identify the user-visible behavior and the affected data.
- List the interfaces that may change, including APIs, events, command-line entry points, jobs, and administrative tools.
- Record assumptions about authentication, authorization, tenancy, deployment environment, and failure behavior.
- For web content, state the intended WCAG 2.2 conformance level and any additional project requirements before testing.
Establish the boundary of the change
Do not begin with only the source files named in a pull request description. Include dependency manifests and lockfiles, tests, configuration, scripts, CI workflows, container definitions, infrastructure, and deployment files. A generated implementation can alter behavior indirectly through any of these paths.
Compare the changed-file list with the stated task. Unrelated edits, new network access, unexplained permissions, disabled checks, or a new dependency without a clear reason are review findings even when the main feature works.
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Risk should determine who reviews the change and how much evidence is required. The following triage is a practical starting point; a project’s threat model can raise or lower the treatment.
| Change profile | Examples | Review treatment |
|---|---|---|
| Routine, isolated change | Presentation or internal refactoring with no new data flow or permissions | Read the full diff, run the repository’s checks, verify tests and accessibility impact, and obtain the normal human approval. |
| Data-handling change | New input parsing, output rendering, persistence, logging, or file handling | Trace data from entry to use, inspect validation and encoding, check error and logging behavior, and review dependency and configuration changes. |
| Trust-boundary change | Public endpoint, third-party integration, CORS change, network exposure, new data store, or cross-tenant operation | Require a deeper security review, explicit authorization and ownership checks, abuse-case testing, and review by a trained reviewer or security champion when available. |
| Critical security logic | Authentication, sessions, authorization, cryptography, deserialization, uploads, secrets, or rate limits | Independently verify the security properties and failure cases. Do not rely on generated tests or a clean scanner result; route the path to an appropriately skilled reviewer. |
Generated code that touches more than one trigger should be reviewed at the highest applicable level. Record why the chosen depth is appropriate so a later maintainer can understand the decision.
Step 1: Read the complete diff and reconstruct its intent
Read every changed line, including additions that appear unrelated to the feature. Then follow the execution path far enough to understand what happens at runtime. Look for behavior that is easy to miss in a line-by-line review:
- New permissions, roles, routes, environment variables, credentials, or service accounts.
- New network calls, redirects, webhooks, file-system access, subprocesses, or dynamic code loading.
- Changes to default-deny behavior, error handling, validation, timeouts, or rate limits.
- New dependencies, version changes, install scripts, container commands, CI steps, or deployment permissions.
- Tests or fixtures that weaken assertions, skip security cases, or encode the implementation rather than the requirement.
AI agents may process issue bodies, pull-request comments, README files, logs, or fetched pages. OWASP warns that those sources can contain indirect prompt-injection content. After an assistant has handled external text, inspect unexpected edits especially carefully; do not assume that an instruction embedded in a document was part of the authorized task.
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Ask a simple question for each change: “What new capability does this line give the program, and who can cause it to run?” If the answer is unclear, pause the approval and obtain clarification rather than inferring intent from the generated code.
Step 2: Trace security behavior from input to outcome
Follow untrusted input
Mark every value that can originate outside the trusted component: request parameters, headers, cookies, uploaded files, messages, imported records, environment-provided values, and third-party responses. Follow each value through parsing, validation, storage, queries, templates, commands, logs, and outbound requests.
Check that validation is applied at the correct boundary and that the code uses context-appropriate output encoding. A value validated for one use is not automatically safe for another. String-built queries, shell commands, template expressions, file paths, and redirects deserve explicit inspection rather than confidence based on variable names.
Verify authorization at every protected operation
Authentication establishes who a caller is; authorization decides what that caller may do. Check authorization at the operation that reads, changes, exports, or deletes the protected object, not only at the route or screen that leads to it. Confirm that tenant, account, ownership, role, and object identifiers are compared against the authenticated subject.
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Inspect secrets, cryptography, and errors
- Confirm that secrets are not committed, logged, returned in errors, or exposed to a client.
- Check that cryptography uses approved project APIs and algorithms rather than deprecated or improvised constructions.
- Ensure errors reveal enough information for legitimate diagnosis without disclosing credentials, tokens, stack traces, internal identifiers, or sensitive records.
- Check that rate limits, lockouts, replay protections, and session invalidation are present where the threat model requires them.
OWASP specifically identifies missing authorization and validation, weak or deprecated cryptography, and string-built queries as recurring concerns in generated code. Treat those patterns as prompts for a concrete trace and test, not as automatic proof of a vulnerability without understanding the surrounding controls.
Step 3: Examine dependencies and the build path
Review a generated dependency as a supply-chain change, even when it appears to solve a small problem. Confirm the package identity, provenance, supported version range, lockfile entry, transitive additions, and known advisories using the project’s approved sources. Do not rely on the model’s statement that a version is current or secure; version information changes.
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Inspect installation and build behavior as well as runtime code. Package scripts, container instructions, CI workflows, deployment manifests, and generated configuration can execute with broader permissions than the application itself. Look for:
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- Changes to CI tokens, deployment credentials, artifact publishing, or branch protections.
- New containers, base images, registries, service accounts, ports, or host mounts.
- Dependency upgrades that silently change parsers, authentication middleware, serialization, or cryptographic behavior.
Confirm that the lockfile and manifest agree, that the dependency is actually needed, and that unused or duplicated packages are removed. If the project has an established approval process for new dependencies, follow it rather than treating generated code as an exception.
Step 4: Run automated security checks, then interpret them
Run the checks that fit the repository on the pull request, with results visible to reviewers. A practical baseline includes static application security testing (SAST), software composition analysis (SCA), and secret scanning.
| Check | Useful for finding | What it cannot establish | Reviewer action |
|---|---|---|---|
| SAST | Recognizable insecure coding patterns, tainted data flows, and some configuration errors | That business rules, object ownership, or authorization semantics are correct | Validate each relevant finding in context, fix it or record a reasoned triage decision, and add a regression test when appropriate. |
| SCA and dependency auditing | Known issues, vulnerable versions, license or provenance signals, and transitive changes | That a package is trustworthy for the project’s use or that application code uses it safely | Confirm package identity and version constraints, assess exposure, and choose an approved update or mitigation. |
| Secret scanning | Credential-like strings and known token formats in code and history | That secrets are absent from every external system or that a detected value is harmless | Revoke and rotate exposed credentials, remove them from the correct locations, and investigate access logs as required. |
A clean scan narrows the search; it does not close it. Scanners can miss broken access control, flawed business logic, unsafe combinations of individually acceptable operations, and requirements they do not model. Resolve or consciously triage findings before approval, and record why a remaining finding does not block the change.
Choose tools by capability, not by reputation
For security automation, compare language and framework coverage, dependency ecosystems, secret detection, CI integration, finding explainability, triage workflow, and false-positive handling. Verify that the tool can analyze the repository’s generated files, templates, infrastructure, and build system rather than assuming broad coverage from a product label.
Step 5: Review tests as evidence, not as permission to skip review
Read generated tests independently from the implementation. A test that reproduces the code’s assumptions can pass while the behavior is unsafe. Prefer assertions about security properties and meaningful failures:
- An unauthorized user cannot read or modify another user’s or tenant’s object.
- Malformed, oversized, unexpected, or duplicate input is rejected or handled safely.
- Authentication, session expiry, logout, password or token changes, and recovery paths enforce the intended rules.
- Cryptographic failures, dependency errors, timeouts, and downstream outages fail closed where required.
- Uploads, deserialization, and external callbacks enforce type, size, origin, and authorization constraints.
For critical authentication, authorization, input-validation, and cryptographic logic, independently derive the expected threats and compare them with the test cases. Passing AI-written tests is not proof of security. Add tests for alternate routes, negative cases, boundary values, and failure recovery rather than only the example shown in the task description.
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Step 6: Review the AI agent’s permissions and context
The review includes the way the code was produced. Determine what the assistant could read, what it could send externally, which tools and credentials it could use, and whether sensitive files were excluded. Apply least privilege to repository access, shell commands, cloud roles, tokens, and network destinations.
- Give the agent only the files and context necessary for the task.
- Keep secrets, production data, private keys, and unrelated repositories outside its context whenever possible.
- Require approval before high-impact actions such as changing deployment settings, publishing artifacts, modifying access controls, or sending data to an external service.
- Retain an audit trail of prompts, tool calls, generated changes, approvals, and overrides appropriate to the project.
- Inspect the final diff for instructions or content that appears to have come from an untrusted issue, comment, log, or fetched page.
NIST SP 800-218A, the 2024 SSDF Community Profile for generative AI and dual-use foundation models, is a development-process reference. It can help structure these controls, but it does not replace the project’s threat model or the code review itself.
Step 7: Review web accessibility with WCAG 2.2 as the reference
This accessibility workflow applies to web content. Native applications, embedded devices, and jurisdiction-specific obligations may require different standards or additional evaluation. For a web project, identify the target WCAG 2.2 level—A, AA, or AAA—and any product requirements before judging the result. WCAG 2.2 organizes testable success criteria around four principles: perceivable, operable, understandable, and robust.
Check structure and headings
Inspect the rendered document, not only the component source. Confirm that headings communicate the content hierarchy, landmarks identify major regions, lists and tables use appropriate semantics, and the reading order remains meaningful when styling is removed or the content is navigated non-visually. Generated markup may look correct on screen while producing a confusing accessibility-tree structure.
Check text alternatives and non-text content
Every informative image needs an equivalent text alternative, while decorative images should not create noise for assistive technology. Check icons, charts, controls, canvas output, audio, video, and generated status graphics. The alternative should convey the purpose or information, not merely repeat a file name or visual label.
Check contrast, zoom, and visual meaning
Verify text and meaningful graphical elements against the project’s target criteria, including states such as hover, focus, disabled, selected, and error. Do not communicate information by color alone. Test the layout at increased text size and zoom so that content, controls, and error messages remain available without avoidable clipping or overlap.
Check keyboard operation and visible focus
Use the feature without a mouse. Every interactive control must be reachable in a logical order, operable with the keyboard, and free of traps. Focus should remain visible and should not be hidden behind sticky headers, dialogs, or other content. Custom widgets need correct names, roles, states, keyboard behavior, and focus management when they open, close, or update.
Check forms and error communication
Associate labels with their controls and make instructions, required status, formats, and constraints available before entry. When validation fails, identify the field, explain the problem in plain language, preserve valid input where appropriate, and make the message available to assistive technology. Check that dynamic updates, loading states, and success or failure announcements do not depend on sight or sound alone.
Check moving content and media
Review carousels, auto-updating regions, animations, time limits, and scrolling content for pause, stop, or extension mechanisms where the applicable criterion requires them. Provide captions, transcripts, audio descriptions, or other alternatives for multimedia according to the target level and content. Test reduced-motion preferences and interaction timing rather than assuming a static screenshot represents the experience.
Can an accessibility scanner prove a site is accessible?
No. W3C’s Web Accessibility Initiative states that accessibility evaluation tools cannot determine accessibility; they can only assist in doing so. Automated checks are valuable for repeatable, detectable conditions such as some missing names, structural errors, or contrast problems, but they may produce false or misleading results and cannot judge every aspect of meaning, interaction, or usability.
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Run an appropriate checker against the content it can actually reach, including authenticated or JavaScript-rendered states when supported. Then inspect the rendered interface manually with keyboard operation, focus movement, zoom, assistive technology where available, and the checks above. A page can pass automated rules while its heading hierarchy is confusing, its error recovery is unusable, or its custom widget cannot be completed without a pointer.
Compare accessibility tools by the task they support
| Selection question | Why it matters |
|---|---|
| What content types and WCAG versions are supported? | Coverage differs for static pages, component libraries, documents, mobile-sized layouts, multimedia, and newer success criteria. |
| Which criteria are automated and which require manual assistance? | The tool should make its limits visible rather than implying complete conformance. |
| What page and site scope is available? | Determine whether it can evaluate a single page, a crawl, a local build, a component story, or authenticated routes. |
| Can it analyze JavaScript-rendered and authenticated content? | Unreachable states cannot be assessed by a crawler that never sees them. |
| How does the team run it? | Browser, command-line, CI, and editor workflows have different setup and maintenance costs. |
| What reporting and remediation support is provided? | Actionable selectors, evidence, severity, trend history, and ownership can determine whether findings get fixed. |
| What operating systems, integrations, and license costs apply? | Choose for the team’s product, skills, and workflow; feature lists and prices vary. |
Use the tool as a consistent assistant to human evaluation, not as a certification stamp.
Step 8: Include usability evaluation when the flow warrants it
Conformance checks and usability are related but not identical. Evaluate early and throughout development instead of waiting for a final audit. For an important or complex flow—such as account recovery, checkout, data entry, or a multi-step administrative task—involve people with disabilities or experienced accessibility evaluators when feasible.
Give evaluators realistic tasks and observe where they encounter barriers. Combine their findings with automated results and code-level inspection. This can reveal issues that a rule checker cannot infer, such as unclear language, unexpected focus movement, a status message that arrives too late, or a control that is technically present but difficult to understand.
Step 9: Record a decision that another maintainer can audit
Before merging, create a review record proportionate to the risk. It should identify:
- The change scope, intended behavior, affected interfaces, and reviewer.
- The threat model or risk triggers that determined review depth.
- Security tools, accessibility tools, and versions used, plus the checks they covered.
- Manual security traces, negative tests, keyboard and focus checks, and other accessibility checks performed.
- Findings, fixes, accepted risks, owners, and due dates for anything deferred.
- The WCAG 2.2 target level and any project-specific requirements used for the web review.
- The named human maintainer and approver responsible for correctness, security, accessibility, and future changes.
An approval should mean that the reviewer understands the behavior and accepts the remaining risk, not merely that a pipeline turned green. If the evidence is incomplete, return the change for clarification or restrict its deployment until the missing review is complete.
Quick Recap
A repeatable pre-merge checklist
- Read the full diff, including dependencies, tests, configuration, scripts, CI, containers, and deployment files.
- Compare every changed file with the requested behavior and investigate unrelated edits, new permissions, network access, or weakened checks.
- Classify risk triggers and assign a reviewer with the necessary security and accessibility skills.
- Trace untrusted input to its use; verify validation, encoding, error behavior, secrets handling, rate limits, and cryptography.
- Verify authorization at each protected operation, including alternate routes, background jobs, exports, and bulk actions.
- Check package identity, provenance, version constraints, lockfile and transitive changes, advisories, and build or install scripts.
- Run SAST, dependency analysis, and secret scanning; resolve or document every finding.
- Read tests independently and add cases for unauthorized access, malformed input, failures, boundaries, and recovery.
- Review the agent’s context, permissions, credentials, external inputs, audit trail, and approval gates.
- For web content, test the stated WCAG 2.2 target with an automated checker and manual inspection of structure, alternatives, contrast, keyboard access, focus, forms, errors, motion, and media.
- Include users with disabilities or an experienced evaluator for important or complex flows when feasible.
- Record the evidence, residual risk, human owner, and final approval before merging.
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