Ecommerce Platform Audit Requirements

E-Commerce Platform Audit Requirements

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, +256 784 464178.

Overview

Use this skill to define a requirements-level audit protocol for e-commerce platforms. It gives the audit a standard, scope, evidence model, legal table, payment scope, integration review, AI review, and remediation backlog so the output is actionable and defensible.

Use When

• Auditing or scoping an audit of an e-commerce website, app, marketplace presence, payment integration, logistics integration, API, data flow, or AI feature.
• Producing remediation requirements for SMEs in a donor or technical assistance programme.
• Reviewing cross-border readiness involving payment, data protection, consent, consumer trust, and platform security.

Do Not Use When

• The task is only visual UX feedback or marketing copy.
• You cannot access enough system, process, or owner interview evidence to support findings.
• Legal advice is required. This skill identifies compliance issues and escalation needs; it does not replace counsel.

Required Inputs

• Platform URLs/apps, architecture notes, payment/logistics providers, data flows, user journeys, admin roles, and support workflows.
• Countries where customers, operations, data processing, or partners are located.
• Known AI/recommendation/fraud/personalisation tools.
• Existing policies: privacy notice, terms, returns, consent, security, incident handling.

Workflow

1. Define audit scope and evidence access.
2. Set standards baseline: OWASP Top 10, OWASP API Security Top 10, OWASP ASVS, CVSS, PCI-DSS where payment card scope exists, and NIST AI RMF for AI use.
3. Map architecture, integrations, data flows, roles, permissions, and third-party dependencies.
4. Scope payment security. Identify hosted redirect, embedded checkout, card data exposure, mobile money/gateway flows, reconciliation, settlement, refunds, and chargebacks.
5. Map privacy and consumer-protection obligations by jurisdiction using the verified EAC data-protection table and escalate uncertain legal questions.
6. Review AI use for data provenance, human oversight, bias, explainability, security, and EU AI Act exposure where relevant.
7. Produce a remediation backlog with severity, business impact, owner, effort, dependency, and acceptance criteria.
8. Write a founder-readable executive summary and a technical appendix.

Quality Standards

• Every finding maps to a named standard, law/regime, policy, or observed evidence.
• PCI scope matches the real payment architecture.
• Country legal statuses use the verified table and are dated.
• AI review states whether AI exists, what data it uses, and what risk class/escalation applies.
• The remediation backlog is prioritised, owned, and testable.

Anti-Patterns

• Vibes-based security review with no standard.
• Over-scoping PCI for a company that never touches card data.
• Using stale data-protection-law status.
• Proposing a payment rail without country coverage and reconciliation checks.
• Findings with no severity, owner, or acceptance criteria.

Outputs

• Audit scope and evidence request list.
• Security, API, payment, integration, privacy, AI, and data-flow audit checklist.
• Verified EAC data-protection table reference.
• Remediation backlog.
• Founder executive summary and technical appendix requirements.

References

• references/audit-scope-and-standards.md: Scope, standards, evidence, and payment/AI review.
• references/eac-data-protection-table.md: Verified EAC data-protection status table and legal-use rules.
• references/remediation-backlog-template.md: Backlog fields, severity, business impact, and acceptance criteria.

Inputs

Decision rules

Degraded mode

If systems or evidence are unavailable, issue a document-only gap assessment with untested controls separated from findings; do not provide compliance assurance.