Organisations should start by locating where cardholder data and other sensitive records actually reside across structured and unstructured systems. PCI compliance depends on knowing what data exists, where it is stored, and who can reach it. Without discovery and classification, remediation is guesswork, audit evidence is weak, and protection controls may miss the most exposed repositories.
Start with data discovery, not controls
Before any PCI workstream can be credible, organisations need a current view of where payment data lives, how it flows, and which stores are actually in scope. That means checking databases, file shares, object storage, logs, exports, backups, endpoints, and downstream SaaS or integration layers. Classification should distinguish cardholder data from other sensitive payment records, then tie each repository to an owner and a business process.
The practical aim is to shrink the unknowns that make compliance expensive. If teams only harden the systems they already know about, hidden copies of sensitive payment data remain outside the control perimeter and can undermine both scope reduction and evidence collection.
Find the systems that create shadow copies
Payment data rarely stays in one place. Reporting jobs, support workflows, troubleshooting logs, test datasets, and file transfers often create secondary copies that outlive the original business transaction. Those copies can be harder to inventory than the primary payment platform, yet they are often the places where exposure grows fastest.
Discovery should therefore include structured search for fixed patterns, data sampling, and review of application behaviour that writes or transforms records. It is also important to look for adjacent data that may not be card data itself but still carries enough context to increase exposure when combined with other records.
That is why disciplined classification matters before remediation begins. The first question is not which control to deploy, but whether a repository should exist at all with this data type inside it.
Use classification to drive scope, ownership, and removal
Once sensitive payment data is identified, the next step is to decide whether each location is necessary, can be tokenised or truncated, or should be purged entirely. This is where discovery becomes a scoping exercise: the smaller the retained footprint, the less remediation, testing, and evidence collection the PCI programme must support.
Classification also establishes accountability. If a team cannot name the business owner, the data purpose, and the approved retention period, it is usually a sign that the data is lingering by accident rather than by design. In practice, that is where compliance gaps persist longest.
Risk and Threat Considerations
Unidentified payment data creates both compliance and exposure risk because controls can only protect what teams know exists. Hidden repositories are especially dangerous when they sit in logs, exports, backups, or non-production environments, where access is broader and monitoring is weaker.
Failure mechanism: Sensitive records evade discovery, so scoping, segmentation, retention, masking, and access controls are applied inconsistently or not at all. That leaves residual copies available to insiders, attackers, or accidental disclosure.
Impact: Organisations can overstate their PCI readiness, miss the highest-value cleanup targets, and discover sensitive records only after an audit request, incident, or data subject inquiry.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
NIST CSF 2.0, NIST SP 800-53 Rev 5 and CIS Controls v8 set the technical controls, while PCI DSS v4.0 and ISO/IEC 27001:2022 define the regulatory obligations.
| Framework | Control / Reference | Relevance |
|---|---|---|
| PCI DSS v4.0 | PCI DSS v4.0 | PCI compliance depends on identifying card data scope before control deployment. |
| Recommendation — Map all payment-data repositories before selecting compensating PCI controls. | ||
| NIST CSF 2.0 | ID.AM-01 — Physical devices and systems within the organization are inventoried | Discovery and classification require an inventory of systems that may store payment data. |
| ID.AM-05 — Resources are prioritized based on classification, criticality, and business value | Classification of payment data determines which repositories need the strongest protection first. | |
| Recommendation — Inventory systems that may hold payment data before scoping safeguards. Prioritize protection of repositories holding the most sensitive payment data. | ||
| NIST SP 800-53 Rev 5 | CM-8 — System Component Inventory | Locating sensitive data relies on knowing which systems, stores, and exports exist. |
| MP-6 — Media Sanitization | Removal and disposal decisions matter once sensitive payment data is found in unnecessary stores. | |
| Recommendation — Maintain an inventory of systems and data stores that could contain payment data. Sanitize media and repositories that no longer need to retain payment data. | ||
| ISO/IEC 27001:2022 | A.5.12 — Classification of information | Payment data must be classified before teams can decide retention, handling, and protection. |
| A.5.9 — Inventory of information and other associated assets | Discovery of payment data depends on knowing where information assets are stored. | |
| Recommendation — Classify payment data before defining storage and handling rules. Build and maintain an inventory of information assets that may contain payment data. | ||
| CIS Controls v8 | CIS-1 — Inventory and Control of Enterprise Assets | Asset inventory is a prerequisite for finding where payment data resides. |
| Recommendation — Inventory assets that may store or process payment data. | ||
Practitioner Guidance
What to prioritise: Start with repositories that are easiest to overlook but hardest to defend, especially logs, backups, exports, shared folders, analytics stores, and test environments. These areas often determine whether the PCI scope can be reduced materially.
What to verify: Confirm that discovery output is traceable to a named owner, a business purpose, and a disposition decision for each repository. If a system contains payment data but no one can justify why it exists, treat removal or containment as the default outcome.
Practitioner takeaway: PCI readiness starts with evidence of where the data is, not with evidence of how many controls have already been deployed.
Related resources from NHI Mgmt Group
- What should organisations do before connecting AI agents to sensitive BigQuery data?
- What breaks when organisations do not classify and redress sensitive data before fine-tuning or retrieval?
- What breaks when organisations cannot identify sensitive data inside old backups?
- Why do organisations need PCI data discovery before they can reduce cardholder data risk?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 27, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
