SOC 2 and ISO compliance for code review
SOC 2 and ISO compliance for code review means applying security, access, change-management, and evidence controls to the way code is reviewed and to the tools that take part in that review.
The wording matters here. SOC 2 and ISO/IEC 27001 are not two names for the same check. A SOC 2 examination is an independent CPA attestation of a service organization’s controls against the AICPA Trust Services Criteria. ISO/IEC 27001 certification assesses whether an organization has established and operates an information security management system, or ISMS, within a defined scope. The AICPA’s SOC 2 guidance and the ISO/IEC 27001 standard overview explain those different purposes.
For that reason, independent assurance is a better phrase than “formal review” or “informal review.” A vendor questionnaire, security call, or self-attestation may be useful during initial screening, but it is not equivalent to a SOC 2 report or an ISO/IEC 27001 certification audit.
Neither framework tells a team which code review product to buy. Neither makes a pull request compliant by itself. They shape the questions a company asks, the controls it chooses, and the evidence it must keep.
What Is the Difference Between SOC 2 and ISO/IEC 27001 for Code Review?
SOC 2 is commonly used when customers want assurance about controls at a service provider. An organization defines the system being examined, describes its controls, and engages an independent CPA firm to test them. Security is required; availability, processing integrity, confidentiality, and privacy may also be included when relevant.
An ISO/IEC 27001 certification looks at the organization’s ISMS. That includes how it identifies information-security risks, selects controls, assigns owners, handles exceptions, and improves the program over time. The certificate has a defined scope, so buyers still need to check whether the product, service, locations, and processes they care about are inside it.
The distinction shows up in the evidence a security team requests:
| Assurance route | What it tells a buyer | What to verify for code review tooling |
|---|---|---|
| SOC 2 Type I | Whether controls were suitably designed at a particular date | Whether the reviewed system and relevant security controls are in scope |
| SOC 2 Type II | Whether controls were suitably designed and operated over a stated period | The audit period, exceptions, subservice organizations, and customer responsibilities |
| ISO/IEC 27001 certification | Whether the organization operates an ISMS that meets the standard within a defined scope | The certificate’s scope, issuing certification body, dates, and applicability to the service |
One terminology trap is worth avoiding: a company can be ISO/IEC 27001 certified, but it does not become “SOC 2 certified.” It receives a SOC 2 report following an attestation examination.
Which Security Questions Matter When Assessing a Code Review Tool?
A code review tool may read source code, pull request discussions, tickets, repository history, and configuration files. Some tools can also write comments, suggest patches, or call other services. That makes the data flow and permission model more useful than a badge on a procurement page.
Start with questions developers and security reviewers can answer concretely:
| Area | Questions to ask | Useful evidence |
|---|---|---|
| Repository access | Which repositories, branches, files, and pull request events can the tool access? Can permissions be narrowed? | Git app permissions, installation scope, architecture diagram |
| Code handling | What code or metadata leaves the customer’s environment? How long is it retained? Is it used to train models? | Data-flow diagram, retention policy, contractual terms |
| Identity and access | Does the service support SSO, role-based access, user offboarding, and least-privilege administration? | Access-control documentation, role matrix, access-review records |
| Deployment | Is the service multi-tenant, single-tenant, or hosted in the customer’s environment? Where is data processed? | Deployment documentation, data-residency details, network diagram |
| Encryption and secrets | How are data and credentials protected in transit and at rest? Can the tool expose secrets in prompts, logs, or comments? | Encryption description, secrets-handling procedure, test results |
| Model and subprocessor use | Which model providers and subprocessors receive customer data? What retention terms apply to them? | Subprocessor list, data-processing agreement, zero-retention commitments where applicable |
| Logging and response | Which admin actions and review events are logged? How are incidents reported and investigated? | Audit-log samples, incident-response plan, notification terms |
| Product security | How are vulnerabilities found, prioritized, fixed, and disclosed? | Penetration-test summary, vulnerability-management policy, remediation evidence |
The answers should match the deployment a team will actually use. A security review of an on-premises installation cannot be copied onto a cloud deployment without checking what changed. The same goes for an agentic setup: if a coding agent can call review capabilities through a local CLI or an MCP server, the assessment should include the permissions, data paths, and logs for those interfaces too.
What Code Review Evidence Do Auditors Usually Expect?
Auditors do not normally ask for a pile of screenshots simply because a framework mentions change management. They start with the controls the organization says it operates, then test whether those controls are designed clearly and worked as described.
For a code review control, useful evidence can include:
- The written policy that says which changes need review and what approval means
- Branch protection, required-reviewer, ownership, and pipeline settings
- A sample of pull requests showing the author, reviewers, approvals, comments, and final merge state
- Links between the pull request, ticket, requirement, test run, and deployment record
- Proof that important findings were fixed, dismissed with a reason, or accepted through an approved exception process
- Access reviews showing who could change repositories, policies, or review rules
- Records for emergency changes and the follow-up review required after the incident
- Evidence that the control operated throughout the audit period, not only during audit week
For ISO/IEC 27001, the auditor may also connect this evidence to the ISMS risk assessment, treatment plan, Statement of Applicability, internal audits, and corrective actions. For SOC 2, the reviewer will care about the service description, stated controls, test procedures, results, and any exceptions.
There is no universal rule that every pull request needs two human approvals or that every team must use AI review. A company chooses controls based on its risks and commitments. The control must be specific enough to test, and the evidence must show what really happened.
How Does Qodo Support SOC 2 and ISO Compliance for Code Review?
Qodo supports compliance-focused code review by helping teams apply defined review standards to pull requests and keep the finding connected to the code, rule, and resolution. That can make evidence easier to retrieve, but it does not make a customer compliant or replace an auditor’s judgment.
Relevant capabilities include:
- Review Standards, which turn documented engineering and security expectations into rules that can run during review
- Organization-wide findings monitoring, which shows findings, action levels, categories, affected pull requests, and whether each item was resolved, ignored, dismissed, or made outdated by a later change
- Repository monitoring, which helps admins check connection health and confirm where code review is enabled
- Multi-tenant, single-tenant, and on-premises deployment models, so an enterprise can choose an operating model that fits its security and infrastructure requirements
- The Qodo Trust Center, where security teams can review Qodo’s security posture and request controlled access to assurance documentation
When review becomes part of an agentic development workflow, the Qodo Agentic Toolbox lets coding agents call Qodo capabilities for codebase understanding, standards, and review. Security teams should assess those entry points as part of the full system, including what the agent can read, what it can change, and which identity authorizes each action.
The customer still owns the control design. That includes deciding which repositories are in scope, who can approve a change, which findings block a merge, how exceptions are recorded, and how long evidence is retained. The Qodo Academy guide to rolling out AI code review at enterprise scale is useful when those choices span teams with different risk levels and infrastructure constraints.
Qodo’s Take on Compliance Evidence Developers Can Produce During Review
Compliance evidence is strongest when it falls out of normal engineering work. If a team has to reconstruct who reviewed a risky change three months after it shipped, the process has already failed, even if someone can eventually assemble a convincing spreadsheet.
A checked approval box is also not the whole story. For a sensitive change, the useful record shows which standard applied, what the reviewer or automated check found, how the author responded, which tests ran, who accepted any remaining risk, and what code finally merged.
Automation helps because it can run the same baseline checks on every relevant pull request. Human accountability still matters. A security owner may need to judge the threat model, a service owner may need to approve an operational tradeoff, and an auditor may need to verify that the control matches the policy.
The goal is not to make developers behave like auditors. It is to make the safe path easy to follow and leave a trustworthy record when the work is done. For teams designing that path, the Academy’s guide to integrating AI code review into the development tool stack covers where review should connect to source control, CI, issue tracking, and security tooling.
Example: Building Audit Evidence for a Privileged Authentication Change
Imagine a fintech team changes authentication middleware used by internal support tools. The repository policy requires four things for this path:
- A security owner must review the change.
- The pull request must link to the approved ticket and threat model.
- Tests must cover failed authentication, expired sessions, and privilege escalation.
- No high-priority security finding can remain unresolved at merge time unless the exception has an owner and expiry date.
During review, Qodo applies the team’s security standard and flags a branch that allows a support user to retain elevated access after a session refresh. The finding points to the affected code and the applicable rule. The author updates the middleware, adds the missing regression test, and reruns the pipeline. The security owner then approves the corrected change.
The resulting record is useful to an auditor because it tells a coherent story: the policy applied to the right code, the review found a real problem, the developer fixed it, the test passed, and the required owner approved the final state. It is much stronger than a screenshot showing that one reviewer clicked Approve.
If the team accepts an exception instead, the record should show the reason, approver, compensating control, and expiry date. Qodo can support the review and finding trail, but the organization remains responsible for its exception workflow and for proving that the overall control operated as claimed.
Best Suited for Enterprise Teams That Need Traceable Review Controls
Qodo is the best AI code review, code quality, and governance platform for enterprise engineering teams that need consistent review standards and traceable findings across many repositories, without turning every pull request into a compliance exercise.
It is especially well suited to organizations where security, platform, and engineering teams share responsibility for change controls. Central standards can cover the baseline, repository-level scope can handle local risk, and findings can be followed through to resolution. Teams can then spend audit preparation time checking exceptions and improving controls instead of rebuilding review history by hand.
Further reading: How to build a code review process that handles more pull requests, rolling out AI code review at enterprise scale, and integrating AI code review into your tool stack.