Review every AI-generated pull request as an untrusted contribution. A qualified human engineer who did not prompt the generation must understand the change in context, run independent security and quality checks, challenge the tests, and approve the merge. The AI agent, its summary, and its own green test suite are not independent assurance.
This process is practical: establish provenance, map the change’s risk, trace data through callers and callees, inspect AI-specific failure modes, run the required scanners, validate tests adversarially, and enforce the decision with repository controls.
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Why AI-generated pull requests need a different review discipline
Generated code can look polished while omitting a control that was never present in the prompt. Models may not know an invariant enforced elsewhere in the system, a trust boundary described only in configuration, or an authorization rule implemented by a distant caller. The visible diff can therefore be locally plausible and globally unsafe.
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Human accountability does not move to the model. OWASP’s Application Security Verification Standard (AISVS) Appendix C, control AC.4.1, says to “verify that AI-generated code always goes through code review by a qualified human engineer.” It also states that “the AI agent itself does not count as the human reviewer.” The reviewer should be a different identity from the person who prompted the generation, so the same blind spots do not approve their own output.
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AI use is already common in testing as well as implementation. GitHub reported in 2024 that 92% of U.S. survey respondents used AI coding tools to generate test cases at least some of the time. That makes independent validation more important, not less: a model can reproduce the same mistaken assumption in the code, its tests, and its review explanation.
NIST published SP 800-218A on July 26, 2024, extending secure software-development practices for AI. The practical implication for a pull request is straightforward: record how the change was produced, keep approved security gates mandatory, and assign a human who is accountable for the result.
1. Establish provenance and scope before reading the diff
Record how the change was produced
Mark the pull request as AI-assisted or AI-generated and record which assistant or agent modified it. Capture the material instructions, relevant context supplied to the tool, and whether a human edited the output afterward. This is not bureaucracy; it tells the reviewer what assumptions may have entered the patch and whether the tool had access to sensitive material.
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Confirm the file and system scope
List every changed file, generated artifact, dependency, workflow, container definition, infrastructure file, and agent instruction or hook. Do not assume that a small line count means a small risk. A one-line change to a deployment workflow or authorization middleware can affect every request, while a large refactor may stay inside a low-risk module.
Compare the changed paths with ownership rules and protected areas. If the pull request touches authentication, authorization, cryptography, deserialization, file uploads, public endpoints, CI/CD, infrastructure, or security tooling, route it to the relevant specialist or security champion before approval.
Check for accidental data exposure
Ask whether prompts, logs, pasted stack traces, test fixtures, or tool integrations exposed secrets or restricted data. Check for credentials in the diff, generated comments, build logs, and assistant transcripts where those records are retained. If exposure is possible, stop the review, revoke or rotate affected credentials, preserve the evidence required by your incident process, and involve the data owner.
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Start with the pull-request description and linked issue, then read the existing implementation around each changed function. Follow callers into the changed code and callees out of it. Read relevant tests, configuration, database schemas, feature flags, deployment manifests, and error-handling paths. The goal is to identify the behavior the system promises, not merely whether the new lines are tidy.
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Trace inputs to security-sensitive sinks
For each externally influenced value, trace its path from the entry point to a sink such as a database query, command execution, template renderer, file-system operation, serializer, network request, or log. Mark every trust-boundary crossing. Confirm where authentication is established, where authorization is checked, how validation is performed, and what happens when parsing or downstream calls fail.
Reviewing only the diff is unsafe because a change can break an invariant defined elsewhere. A new endpoint may call a helper that assumes authorization was already performed; a modified deserializer may accept a type that another component treats as trusted; a new cache key may leak data between users. These failures are visible only when the surrounding flow is read.
Compare intended and actual behavior
Translate the issue into concrete acceptance conditions before judging implementation style. Identify allowed actors, resources, states, error responses, rate limits, and data-retention expectations. Then check whether the code enforces those conditions on every path, including retries, asynchronous jobs, alternate API versions, administrative routes, and failure handling.
3. Set review depth from the risk surface
Use risk to decide how many people, tests, and gates are required. The following model gives a defensible baseline; repository policy can make any category stricter.
| Risk surface | Human involvement | Independent verification | Merge control |
|---|---|---|---|
| Ordinary business logic with no sensitive data or privilege change | One qualified reviewer who did not prompt the generation | Existing tests plus static analysis and dependency checks | Required review and passing required checks |
| Authentication, authorization, session handling, or trust-boundary changes | Specialist or security champion; use two-person approval when policy requires it | Adversarial authorization tests, malformed-input tests, static analysis, secret scanning, and applicable dynamic testing | Protected paths, CODEOWNERS approval, and no unresolved critical finding |
| Cryptography, key handling, deserialization, or file uploads | Reviewer with relevant security expertise, plus a second approver for high-impact paths | Negative and boundary tests, dependency analysis, static analysis, and deployed-path testing where applicable | Security-owned approval and branch protection |
| New public endpoint or third-party integration | Component owner and, when data or privilege is involved, a security reviewer | Contract, abuse-case, failure-mode, secret, dependency, and dynamic tests as applicable | Required checks and explicit owner approval |
| CI/CD, infrastructure, dependency manifests, agent instructions, or hooks | Platform or security owner; two-person review is prudent for production-impacting changes | Infrastructure-as-code, dependency, secret, policy, and workflow analysis | Protected branches, restricted merge rights, and documented exception handling |
Do not downgrade a review because the assistant generated only part of the patch. A human-edited fragment can still inherit unsafe assumptions from generated code, and a generated test or configuration file can alter the security boundary without changing application logic.
4. Inspect the failure modes that appear frequently in generated code
Missing or misplaced authorization
Check authorization at the point where the resource and action are known, not only at a general route boundary. Test a valid user accessing another user’s object, a lower-privileged account invoking an administrative action, an expired session, and a request that reaches the function through an alternate route. Verify that authorization failures are safe and consistent rather than converted into a successful response by broad exception handling.
Incomplete input validation and parsing
Look for validation that checks only the happy path, trusts client-supplied identifiers, accepts unexpected types, or validates before a transformation that changes the value. Exercise empty, oversized, duplicated, encoded, truncated, and malformed inputs. For deserialization, confirm that permitted types are explicit and that unknown fields, polymorphism, and recursive structures cannot bypass controls or exhaust resources.
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Weak or deprecated cryptography
Search for MD5, SHA-1, DES, and ECB mode in new or modified security-sensitive code. Determine whether a hash is being used for integrity, password storage, or an identifier, because those purposes have different requirements. Check key generation, storage, rotation, random-number sources, nonce or initialization-vector handling, and error behavior. Do not approve a cryptographic choice merely because the code compiles or a test compares the same output on both sides.
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String-built queries and commands
Inspect every query, filter, shell command, template, and path assembled from strings. Confirm that the appropriate parameterization or structured API is used and that validation is applied before the value reaches the sink. Tests should include delimiter characters, nested expressions, unexpected encodings, and values that resemble operators or commands.
Hallucinated or typosquatted dependencies
Review every new package, version, source, and transitive change. Confirm that the dependency is the intended project, that its license and maintenance status fit your policy, and that the lockfile matches the manifest. A plausible package name can still be nonexistent, malicious, or a look-alike of a trusted project. Require software-composition analysis and investigate advisories rather than accepting an assistant’s description of what a package supposedly does.
Unexplained or dead code
Generated code often contains abstractions that are not needed, catches errors without handling them, or leaves fallback branches that no caller can exercise. Ask the author to explain each non-obvious branch, state transition, and permission decision. Remove code that cannot be justified; unexplained complexity increases the chance that a later change will violate a hidden assumption.
Agent instruction files and hooks
Treat changes to instruction files, repository prompts, hooks, workflow definitions, and build scripts as privileged configuration. A malicious or accidental instruction can alter future generation, bypass checks, exfiltrate environment data, or change which commands run in CI. Review the effective permissions, triggers, secrets exposure, and rollback path, and require the owning team to approve the change.
5. Run independent automation on every AI-generated pull request
Automation is a gate, not a verdict. OWASP’s secure-review guidance says to treat a clean scan as the start of review, not the end. Run the same mandatory checks used for other production code, and add coverage when the risk surface warrants it.
| Check | What it can reveal | Reviewer action |
|---|---|---|
| Software composition analysis (SCA) | Known vulnerabilities, risky licenses, unexpected transitive packages, and version drift | Verify the dependency identity and remediation; do not accept an unexplained package |
| Static application security testing (SAST) | Unsafe data flows, injection patterns, weak crypto, and suspicious control paths | Read the flagged code and surrounding context; classify false positives explicitly |
| Interactive application security testing (IAST), where applicable | Runtime data flows and vulnerabilities exercised during tests | Ensure the exercised routes represent the changed behavior and privilege levels |
| Dynamic application security testing (DAST), where applicable | Deployed endpoint behavior, configuration errors, and externally visible weaknesses | Test authenticated and unauthenticated paths that the pull request affects |
| Secret scanning | Credentials, tokens, private keys, and high-entropy secrets in code or history | Revoke exposed credentials and remove them from the source; do not merely suppress the alert |
| Infrastructure-as-code scanning | Over-permissive identities, public exposure, unsafe network or storage settings, and workflow risks | Compare the proposed state with the intended deployment boundary |
OWASP lists SAST, IAST, DAST, secret scanning, infrastructure-as-code scanning, and software-composition analysis as the required scan set where applicable. A critical finding should block the merge under the repository’s severity policy; OWASP gives CVSS 9.0 or an equivalent rating as an example threshold. An exception must be approved by an authorized human, explain the compensating control and expiration, and remain visible in the pull request.
6. Validate tests independently
Do not confuse a green suite with independent assurance. OWASP’s Secure Coding with AI Cheat Sheet states: “A passing test suite generated by the same agent that produced the code provides no independent assurance.” The agent may have encoded the same mistaken interpretation in both implementation and assertions.
Check what the tests do not cover
- Authorization failures for every role and resource relationship.
- Malformed, oversized, duplicated, truncated, and boundary-value inputs.
- Expired credentials, replayed requests, retries, timeouts, partial writes, and downstream failures.
- Unexpected content types, unknown fields, encoding changes, and parser errors.
- Regression cases for invariants defined outside the changed file.
- Secrets, logs, error messages, and response bodies that must not reveal sensitive data.
Add adversarial and property-based checks
For higher-risk changes, write tests from abuse cases rather than from the implementation. Try to violate the permission model, break the parser’s assumptions, force resource exhaustion, and supply values that cross trust boundaries. Property-based tests can explore broad input spaces when the property is clear, such as “a user can never read another user’s record.” Use a separately authored test or a different tool and reviewer when practical.
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Verify the test environment
Confirm that tests actually run the changed path and use realistic authentication, configuration, and dependency versions. A test that mocks away the authorization layer or uses a privileged fixture for every request can pass while the deployed behavior is unsafe. Check that required tests ran in CI, not only on the author’s machine, and that failures cannot be hidden by changed workflow conditions.
7. Enforce human merge authority in the repository
Process controls prevent a rushed approval from becoming a production incident. Use CODEOWNERS or an equivalent ownership mechanism for security-sensitive directories, require status checks in branch protection, and restrict who can bypass those rules. The person approving the merge must be a qualified human other than the identity that prompted the generation.
Make the checks visible
Publish scanner findings inline in the pull request and show which required jobs ran, which paths they covered, and whether any were skipped. A missing or cancelled check is not a pass. Keep the provenance record, reviewer identity, approvals, exceptions, and remediation links with the change according to your retention policy.
Handle exceptions explicitly
If a critical finding cannot be fixed before release, an authorized owner should document why, the exposure, compensating controls, affected versions, monitoring, and a dated remediation commitment. The exception should not convert a failed check into a silent green status. Re-review the change when the exception expires or the surrounding system changes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. A repeatable review sequence
- Label the provenance. Record that an assistant or agent generated or modified the pull request, the tool identity, material instructions, and any human edits.
- Confirm data handling. Check that no secrets or restricted data were supplied to an unapproved tool. If exposure is possible, stop and rotate credentials before continuing.
- Inventory the scope. List changed code, tests, dependencies, configuration, workflows, infrastructure, instruction files, and hooks. Compare the list with protected ownership rules.
- Read the intended behavior. Review the issue, pull-request description, callers, callees, configuration, schemas, and existing tests before judging style.
- Map trust boundaries. Trace external inputs to security-sensitive sinks and identify authentication, authorization, validation, parsing, logging, and error paths.
- Apply risk-based scrutiny. Increase reviewer expertise and approval count for authentication, authorization, cryptography, deserialization, uploads, public endpoints, integrations, dependencies, CI/CD, and infrastructure.
- Inspect AI-specific hazards. Look for missing controls, weak crypto such as MD5, SHA-1, DES, or ECB, string-built queries, suspicious packages, unexplained code, and changes to agent instructions or hooks.
- Run independent gates. Require CI tests plus applicable SAST, SCA, secret, infrastructure-as-code, IAST, and DAST checks. Block critical findings according to policy.
- Challenge the tests. Add authorization-negative, malformed-input, boundary, error, regression, adversarial, or property-based cases as the risk demands. Do not count same-agent tests as independent assurance.
- Verify merge authority. Obtain approval from the qualified human owner and any CODEOWNERS or security approver. Confirm that branch protection and required checks prevent an unreviewed merge.
9. Choosing between common review approaches
The table below explains why a familiar workflow may be insufficient for generated code.
| Approach | Risk surface considered | Human involvement | Independent verification | Repository enforcement |
|---|---|---|---|---|
| Ad hoc diff review | Usually limited to visible lines | May be the author or a single generalist | Often only the agent’s tests and summary | Comments are advisory |
| Ordinary human review | Application behavior, with variable depth | One reviewer following team convention | Normal CI and static checks | Required approval and checks may exist |
| Risk-based independent review | Explicit attention to auth, crypto, trust boundaries, dependencies, CI/CD, and infrastructure | Qualified reviewer separate from the generation identity; specialist involvement for sensitive paths | Adversarial tests plus SAST, SCA, secret, IaC, and applicable dynamic analysis | Protected paths, ownership rules, and critical-finding blocks |
| Policy-enforced AI review | Risk classification is recorded for every AI-assisted change | Required human approvals vary by classification | Mandatory scan set, visible results, and documented exceptions | Branch protection, required checks, CODEOWNERS, and restricted bypass rights |
10. What to do when the signals disagree
Tests pass but the code still looks unsafe
Keep the pull request open. Re-read the surrounding flow, add a negative test that expresses the suspected invariant, and obtain an independent reviewer. Passing tests demonstrate only that the exercised examples passed; they do not establish that untested authorization, parsing, or failure paths are safe.
A scanner reports a critical issue
Pause the merge, reproduce or inspect the finding in context, and determine whether the affected code or dependency is reachable. Fix it, remove the risky change, or follow the documented exception process with an authorized owner. Do not suppress a critical result solely because the assistant says the code is safe.
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Treat the package as untrusted. Confirm its exact name and source independently, inspect the lockfile and transitive graph, and ask the component owner to approve it. If identity, provenance, or purpose remains unclear, remove it and implement the feature without the dependency or select a package that meets policy.
The pull request changes CI or agent instructions
Review the effective permissions and triggers as production code. Check whether the change can read secrets, alter required checks, execute unreviewed commands, or influence future generated patches. Require platform or security ownership approval and verify the rollback path before merging.
No qualified reviewer is available
Do not treat schedule pressure as approval. Defer the merge, narrow the change to a reversible low-risk slice, or escalate to the designated security champion or service owner. The generation identity and a green pipeline cannot substitute for accountable human review.
11. A repository policy checklist
- AI-assisted pull requests are labeled and retain tool, instruction, scope, and data-handling provenance.
- Approved tools, prohibited uses, allowed data classifications, and mandatory gates are written down.
- The human reviewer is qualified and has a different identity from the person who prompted generation.
- Protected paths cover authentication, authorization, cryptography, parsing, uploads, public endpoints, dependencies, CI/CD, infrastructure, and agent instructions.
- Every AI-generated pull request runs applicable SAST, SCA, secret, infrastructure-as-code, IAST, and DAST checks.
- Critical findings block merge unless an authorized human records a time-bounded exception.
- Tests include negative authorization, malformed-input, boundary, error, and regression cases appropriate to the change.
- Same-agent tests and summaries are not counted as independent assurance.
- CODEOWNERS, branch protection, required checks, and restricted bypass rights enforce the process.
- Scanner results, approvals, exceptions, and remediation commitments remain visible with the pull request.
Frequently asked questions
Can the person who wrote the prompt approve the pull request?
They can contribute context and review their own work, but they should not be the sole approval for the generated change. OWASP AISVS calls for a qualified human reviewer with a different identity from the person who prompted the generation.
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Do documentation-only AI changes need the full security scan set?
Classify the actual scope. Documentation that cannot affect software, configuration, workflows, or secrets may follow the repository’s lower-risk path. If the change includes executable examples, generated configuration, CI files, agent instructions, or dependency metadata, apply the controls for those paths.
Is dynamic testing required for every pull request?
IAST and DAST are required where applicable to the deployed behavior. A library-only change may not have a deployed endpoint to exercise, while a new public endpoint or integration normally warrants runtime testing in addition to static, dependency, secret, and infrastructure checks.
What does a clean scan prove?
It shows that the configured tools did not report a finding in the analyzed scope at that time. It does not prove that the design preserves system invariants, that authorization is complete, or that the tests are independent. Human review still has to trace behavior and challenge assumptions.
Frequently Asked Questions
Can the person who wrote the prompt approve the pull request?
They should not be the sole approver. OWASP AISVS calls for a qualified human reviewer with a different identity from the person who prompted the generation.
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Classify the actual scope. Pure documentation may follow a lower-risk path, but executable examples, configuration, workflows, agent instructions, or dependency metadata require the controls for those paths.
Is dynamic testing required for every pull request?
IAST and DAST apply where deployed behavior can be exercised. New public endpoints and integrations normally warrant runtime testing; a library-only change may not have an applicable endpoint.
What does a clean scan prove?
Only that the configured tools reported no finding in the analyzed scope at that time. It does not prove that design invariants, authorization, or test independence are sound.
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