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Use PCI DSS v4.0.1 as the payment-security baseline and an AI verification framework such as OWASP AISVS 1.0 as a complement. The result is an evidence-based risk decision, not an automatic certification; scope and assessment duties must be confirmed with your PCI owner or a qualified assessor.
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What the audit must establish
Your audit should answer five questions with evidence:
- What cardholder data or sensitive authentication data can the agent read, transform, transmit, or cause another system to use?
- Which identities, credentials, tools, and permissions make that access possible, and can each action be tied to the agent and a responsible human?
- Are exposure, storage, retention, and transmission limited to what the use case requires?
- Can investigators reconstruct successful and denied access, tool calls, approvals, payment attempts, configuration changes, and control failures from protected records?
- Can the organization detect malicious instructions, revoke credentials, disable the agent, and respond without losing evidence or disrupting unrelated controls?
PCI DSS applies to entities that store, process, or transmit payment account data, and to systems that could affect the security of the cardholder data environment (CDE). Consequently, the model provider is only one possible component in scope. An orchestration service, retrieval store, secrets manager, observability platform, payment gateway, administrator console, or backup system may also matter.
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Phase 1: map scope and the complete architecture
Define the business use case and accountability
Record the agent’s business purpose, name, version, deployment environment, model provider or hosting arrangement, orchestration layer, connected tools, payment services, approval points, operating schedule, and accountable human owner. Include an escalation path for security and payment incidents. A generic statement such as “customer-support agent” is not enough; state whether it can view transaction history, issue refunds, create payment intents, change billing details, or merely answer questions from masked records.
Draw data-flow and trust-boundary diagrams
Trace each data type through ingestion, retrieval, prompting, inference, tool execution, output handling, storage, monitoring, and deletion. Label primary account number (PAN), expiration data, cardholder name, sensitive authentication data, payment tokens, single-use PANs, prompts, retrieved context, tool responses, generated outputs, traces, backups, and audit logs. Mark every point where the agent can read, transform, transmit, cache, or trigger an action.
Show trust boundaries between the model runtime, agent framework, plug-ins, databases, payment APIs, employee interfaces, third-party services, and the CDE. Record whether data is sent outside the organization, whether a provider retains prompts, and which systems can influence tool authorization. Include systems that cannot read PAN but could alter security controls, routing, permissions, or logging.
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Use the architecture to identify CDE components, connected-to systems, and systems that can impact CDE security. Do not assume that tokenization automatically removes an environment from PCI scope; that conclusion depends on implementation and must be validated by the organization’s PCI owner or assessor. Capture assumptions and unresolved dependencies in the audit plan so they are tested rather than silently accepted.
Phase 2: inventory identities, credentials, and permissions
Create an identity register
For every agent component and tool connection, record:
- Principal or service identity and the component that uses it.
- Credential type, storage location, owner, creation date, expiration, rotation interval, and emergency revocation method.
- Granted roles, API scopes, database privileges, network paths, and administrative capabilities.
- Intended operations, permitted data classes, transaction limits, and required human approval.
- Evidence that the identity is distinguishable from human users and unrelated services.
PCI SSC’s AI guidance states: “AI systems should be provided with their own credentials, which can be easily tracked and revoked if necessary (as per the principle for disabling systems if required).” Treat that as an operational requirement for attribution and containment. Shared administrator keys, credentials embedded in prompts, and long-lived tokens make both accountability and emergency shutdown harder.
Compare privilege with the use case
For each permission, ask what specific task requires it and what would happen if the agent were manipulated. Remove read access to full PAN when a masked value or token supports the task. Separate read, refund, payment-initiation, and configuration permissions. Use distinct credentials for development, testing, production, and support. Limit network destinations and tool methods, not only broad application roles.
Inspect policy paths in the model runtime, orchestration platform, secrets manager, database, payment processor, and administrative plane. Check for inherited roles, wildcard scopes, fallback credentials, and tools that bypass the normal approval service. Verify that denied requests are actually denied and that a revoked credential cannot be reused from a cached session.
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Assign human responsibility
Name the person or function responsible for the agent, the payment workflow, credential administration, and monitoring findings. A technically correct service identity is not enough if no one owns an alert or approves a high-risk action. Document who can authorize emergency disablement and who confirms that unrelated payment controls remain available afterward.
Phase 3: minimize, protect, and retain payment data
Determine the minimum data set
Follow a representative transaction and inspect the exact values delivered to the agent. Decide whether the use case truly needs full PAN, or whether it can use a payment token, single-use PAN, truncated PAN, or encrypted value. A support agent may need the last four digits and status; a payment orchestration agent may need a short-lived token; neither assumption should be accepted without testing the actual workflow.
PCI SSC identifies tokens and single-use PANs as ways to limit exposure and impact. It also notes that transaction limits and bounded credential lifetimes can provide additional risk reduction, while those enhancements are beyond PCI requirements. Record the selected control, its lifetime, and the failure behavior when the value expires.
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Inspect every exposure point
Search prompts, retrieved context, tool responses, generated text, error messages, application logs, traces, analytics events, support exports, crash dumps, backups, and test fixtures for live account data. Confirm that redaction occurs before data reaches model telemetry or a general-purpose observability system. Check whether an agent can echo a secret in a response, store it in a memory feature, or pass it to an unapproved tool.
Protect account data at rest and in transit using the organization’s approved cryptographic controls. Verify certificate validation, key ownership, rotation, and access to decryption functions. Ensure test and demonstration environments use synthetic values rather than live cardholder data. Record retention and deletion behavior for prompts, context, tool results, caches, traces, and backups; deletion should include replicas and exported datasets where applicable.
Set explicit output rules
Define which fields may appear in an agent response, which must be masked, and which actions require a structured tool call rather than free-form text. Test both normal and error paths. A policy that masks PAN in the user interface is incomplete if the same value is written unmasked to a trace or returned through an administrative API.
Phase 4: make the evidence trail complete and resilient
Collect representative events
Obtain records for successful and denied data access, privileged actions, tool calls, payment attempts, approval decisions, credential and permission changes, access to logs, logging-configuration changes, and security-control failures. Include at least one event from each relevant component and one end-to-end transaction.
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Audit prompts and tool sequences where feasible
PCI SSC’s AI principles say: “Where possible, logging should be sufficient to audit the prompt inputs and reasoning process used by the AI system that led to the output provided.” Implement this without creating a new card-data repository. Log prompt and retrieval identifiers, policy decisions, tool calls, and relevant step transitions; redact unnecessary PAN and sensitive authentication data. If internal reasoning is not retained, document what observable evidence is available to reconstruct the decision.
Protect, review, and retain logs
Apply controls that prevent unauthorized reading, deletion, and modification. Centralize copies, monitor exported records, restrict log-administration privileges, and test integrity alerts. Synchronize clocks across the agent, tools, payment systems, and logging platform so an investigator can order events reliably.
Microsoft Learn’s explanation of PCI DSS Requirement 10 describes capturing individual access and administrative actions, recording event details, protecting logs, reviewing critical logs at least daily, retaining history for at least 12 months, and keeping at least the most recent three months immediately available for analysis. It is implementation guidance rather than the controlling PCI standard, so verify the applicable requirement and assessment method for your environment.
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Test failure handling
Disable logging, monitoring, or time synchronization in an authorized test and observe the response. The system should alert the responsible team, fail closed for high-risk actions where designed, preserve available evidence, and prevent silent continuation of payment operations. Confirm that a logging outage does not cause agents to fall back to an unprotected local file or unrestricted execution mode.
Phase 5: challenge the agent and its surrounding controls
Design authorized adversarial scenarios
Use a written test plan with scope, test accounts, rollback steps, and approval from the system owner. Attempt to make the agent:
- Reveal full PAN, sensitive authentication data, credentials, or hidden context.
- Use a tool outside its stated purpose or call an administrative endpoint.
- Elevate privileges, bypass an approval gate, or reuse a revoked credential.
- Initiate, alter, or refund a payment without the required authorization.
- Ignore transaction limits or continue after a policy, logging, or monitoring failure.
Test prompt injection and untrusted retrieval content
Place malicious instructions in realistic email, ticket, document, web, and retrieval locations. Test whether the agent treats those instructions as data, refuses unauthorized tool calls, preserves system and developer policies, and requests human approval for sensitive actions. Include indirect injection, conflicting instructions, encoded text, and content that attempts to exfiltrate prior conversation or tool results.
PCI SSC identifies prompt injection and data poisoning as risks. Test poisoning paths in retrieval indexes, training or fine-tuning data, configuration files, and tool metadata. Verify validation before content is trusted and monitor for changes that were not approved.
Verify authorization at the tool boundary
Do not rely solely on the model’s refusal behavior. Send direct requests to each tool and API using the agent identity, with and without required approval context. Confirm that the server enforces scope, resource ownership, amount limits, rate limits, and freshness of approval. Check that a forged or replayed tool call cannot execute a payment.
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Exercise shutdown and recovery
Revoke the agent’s credentials, terminate active sessions, disable tool routes, and place the agent in a known-safe state. Measure whether the procedure works within the organization’s target response time and whether queued actions are canceled or reviewed. Restore service only after validating configuration, credentials, logs, and pending transactions. PCI SSC calls for a clear process to disable AI operation; a documented button that has never been tested is not evidence.
Phase 6: review lifecycle, change, and governance evidence
Inspect the change trail
Review records for model updates, prompts, retrieval sources, tool definitions, permissions, payment-flow logic, policy rules, and monitoring changes. Each change should have an approver, affected environment, test evidence, deployment time, rollback method, and resulting version identifier. Confirm that emergency changes receive retrospective review.
Validate before and after deployment
Look for pre-deployment security testing and ongoing validation against representative transactions and adversarial cases. Re-run high-risk tests after a model, tool, prompt, permission, or payment-provider change. Keep evidence that findings were resolved or formally accepted by an accountable owner.
Connect governance to incident response
Walk through scenarios involving an external attacker, malicious employee, compromised tool, poisoned retrieval source, leaked credential, and unavailable logging. Confirm notification paths, evidence preservation, payment-processor coordination, credential rotation, customer-impact assessment, and decisions about disabling the agent. PCI SSC links these practices to PCI DSS Requirements 6, 10, 11, and 12 in its AI guidance.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Use OWASP AISVS to supplement PCI testing
PCI DSS remains the payment-security baseline. OWASP AISVS 1.0 is a separate, vendor-neutral verification checklist for AI-enabled systems; OWASP describes it as useful for assessment, penetration testing, red-team exercises, and procurement. The June 2026 release contains 191 requirements across 12 chapters and three appendices, with verification levels.
Map relevant AISVS requirement IDs to your architecture, model-development process, deployment controls, orchestration, monitoring, and retirement procedures. Record the framework version with every ID because identifiers can change. AISVS does not replace PCI DSS or determine your legal, contractual, or jurisdiction-specific obligations.
OWASP’s AI Agent Payments guidance offers additional ideas for agent identity verification, audit trails, and fail-closed enforcement in regulated payments. It also notes that obligations depend on the institution’s role, transaction, customer relationship, and jurisdiction. Use those ideas to expand tests, then have compliance owners confirm which duties apply.
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Evidence package and auditor checklist
Assemble one indexed package so another reviewer can reproduce your conclusions:
- Current architecture and data-flow diagrams showing data types, trust boundaries, CDE connections, and human approvals.
- Agent inventory with versions, owners, tools, credentials, permissions, expiration, rotation, and revocation evidence.
- Transaction observations showing what the agent receives and what appears in prompts, context, outputs, traces, logs, backups, and downstream systems.
- Access-control configurations plus evidence of both successful and denied actions.
- Representative audit events, integrity controls, log-access permissions, backups, retention settings, time-synchronization results, review records, and alert handling.
- Authorized adversarial test cases and results for prompt injection, data disclosure, tool misuse, approval bypass, poisoned content, revoked credentials, and shutdown.
- Change-management records, validation results, incident-response walkthroughs, named accountability, and unresolved-risk approvals.
For each control, preserve the configuration snapshot, test date, tester, environment, expected result, observed result, and remediation owner. Keep sensitive evidence in a restricted repository; the audit package itself should not become an unnecessary PAN store.
Compare agent designs using consistent risk axes
When choosing between designs, score each one against the same questions rather than comparing model features. The following archetypes are analytical categories, not claims about a particular product or deployment.
| Risk axis | Isolated, token-based agent | Shared service with limited tools | Agent with direct CDE access | Questions to document |
|---|---|---|---|---|
| Card-data exposure | Usually limited to tokens or masked values | Depends on filtering and shared stores | May include full PAN and broader records | What exact fields enter prompts, tools, traces, and backups? |
| Credential breadth and lifetime | Short-lived, use-case-specific scopes are feasible | Shared roles can widen impact | Privileged, long-lived access creates the highest containment burden | Can every credential be attributed, rotated, and revoked independently? |
| Isolation from the CDE | Separate network and policy boundaries | Partial separation through a gateway | Direct connectivity and more trust relationships | Which component can alter CDE security or bypass the gateway? |
| Auditability | Centralized events and bounded workflows | Multiple owners and log sources | More events, tools, and failure paths to correlate | Can an investigator reconstruct prompts, approvals, tool calls, and outcomes? |
| Human approval and transaction limits | Can be enforced before token use | Depends on shared policy services | Must protect every privileged path | What blocks an unauthorized amount, payee, refund, or replay? |
| Testing and disablement | Credential revocation and isolation are simpler to exercise | Disabling one tenant may affect others | Shutdown can have wider operational consequences | How fast can the agent be stopped without disabling unrelated controls? |
| PCI assessment evidence | Clearer boundaries when validated | Requires evidence across shared components | Broadest evidence and scope analysis | Which assumptions must the PCI owner or assessor confirm? |
Common findings and corrective actions
Shared credentials
Finding: The agent uses a human administrator key or a service account shared by several automations. Correction: issue a dedicated, least-privilege identity; record its owner, lifetime, rotation, and emergency revocation; then test attribution in logs.
Unmasked data in telemetry
Finding: PAN appears in traces, error messages, or support exports even though the user interface masks it. Correction: redact before telemetry, restrict diagnostic fields, purge existing copies according to retention policy, and add regression tests for failures and retries.
Model-only authorization
Finding: The agent is instructed not to refund payments, but the payment API accepts a direct call without an approval token. Correction: enforce authorization, limits, freshness, and ownership at the tool or server boundary; test forged, replayed, and out-of-order calls.
Unverifiable actions
Finding: Logs show a payment result but not which agent, prompt, tool, approval, or policy version led to it. Correction: add correlation identifiers and structured events while excluding unnecessary PAN; protect and review the resulting records.
Untested emergency disablement
Finding: A runbook says to revoke credentials, but no one has exercised it. Correction: perform an authorized drill, measure containment, verify queued-action handling, preserve evidence, and update the runbook with observed dependencies.
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This method can show how an agent accesses card data, whether controls operate as designed, and what evidence supports a risk decision. It cannot, by itself, determine whether a specific implementation is in PCI scope, whether a tokenization design changes scope, which formal validation route applies, or whether additional financial-crime duties arise. Those conclusions depend on architecture, entity role, contracts, and jurisdiction.
Use the completed evidence package with the organization’s PCI owner and, when needed, an independent PCI SSC Qualified Security Assessor. Treat unresolved assumptions as risks requiring a named decision, not as implicit exclusions.
Final decision criteria
Approve the agent for its stated payment use only when the organization can demonstrate all of the following: a documented end-to-end data flow; dedicated, revocable, least-privilege identities; minimized and protected card data; resilient, attributable logs; enforced tool and transaction authorization; successful adversarial and shutdown tests; controlled lifecycle changes; and an accountable owner who can respond to findings. If any of those proofs is missing, restrict the use case, remove unnecessary card-data access, or keep the agent outside payment operations until the gap is resolved.
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