AU-3(3): Limit Personally Identifiable Information Elements

To meet the au-3(3): limit personally identifiable information elements requirement, you must ensure audit logs contain only the specific PII elements your privacy risk assessment says are necessary, and remove or mask everything else. Operationally, this means defining an “allowed PII in logs” list, updating logging configurations and schemas to enforce it, and proving it through log samples, configuration evidence, and governance records. ¹

Key takeaways:

• Maintain an explicit allowlist of PII elements permitted in audit records, based on your privacy risk assessment. ¹
• Enforce the allowlist technically (logging config, field filtering, tokenization/masking) and procedurally (SDLC and change control). ²
• Keep assessor-ready evidence: privacy risk assessment outputs, logging standards, configurations, and representative log extracts showing minimization. ¹

AU-3(3) is one of those controls that looks small but becomes painful during an assessment if you treat logging as a pure security domain. Most environments log “whatever is available” (request bodies, headers, identity claims, error context) because it helps engineers debug quickly. AU-3(3) forces a different posture: audit records may contain PII only when you have a stated, assessed need for that specific element, and you can point to the privacy risk assessment that justified it. ¹

For a CCO, GRC lead, or compliance officer, the fastest path is to convert the requirement into an enforceable specification: a short allowlist of PII fields permitted in audit logs for each system boundary (apps, APIs, infrastructure, SaaS), plus technical controls that block everything else by default. Your goal is not “no PII in logs ever.” Your goal is “only the minimum necessary PII in logs, demonstrably tied to privacy risk decisions, consistently implemented.” ²

This page gives you requirement-level implementation guidance you can hand to engineering and still defend to auditors.

Regulatory text

Requirement (AU-3(3)): “Limit personally identifiable information contained in audit records to the following elements identified in the privacy risk assessment: {{ insert: param, au-03.03_odp }}.” ¹

What the operator must do

1. Run or reference a privacy risk assessment that identifies which PII elements are necessary to appear in audit records for defined purposes (for example, non-repudiation, fraud investigation, privileged access traceability). ¹
2. Translate that assessment into a concrete allowlist: the exact PII elements permitted in logs (and in which systems). ¹
3. Implement technical and procedural controls so audit record generation and downstream log pipelines do not capture additional PII beyond the allowlist. ²

Plain-English interpretation

AU-3(3) requires data minimization for audit logs. If a log entry includes PII, you must be able to answer two questions quickly:

• Which PII elements are allowed to appear in audit records?
• Where did that decision come from (privacy risk assessment), and how is it enforced? ¹

Common practical reading for assessors: “Show me your approved PII-in-logs list, show me how logging is configured to meet it, and show me real log data that matches the policy.”

Who it applies to (entity and operational context)

Typical in-scope entities

• Federal information systems and programs operating under NIST SP 800-53 controls. ²
• Contractors and other third parties handling federal data where 800-53 controls are flowed down (for example, via contract, system security plan requirements, or authorization boundary expectations). ²

Operational contexts where AU-3(3) shows up

• Centralized logging (SIEM), audit trails, and security event telemetry.
• Application logs, API gateway logs, and identity provider logs.
• Administrative activity logging (privileged access, configuration changes).
• Third-party logging/monitoring tools where logs leave your boundary (hosted SIEM, APM, ticketing systems that ingest logs). ²

What you actually need to do (step-by-step)

Step 1: Name an owner and define the control boundary

Assign a control owner who can coordinate Security Engineering, Privacy, and application/platform teams. Document the systems in scope: where audit records are generated, transformed, stored, and exported. ²

Deliverable: “AU-3(3) system inventory for audit logging” (table listing systems, log sources, destinations, and third parties).

Step 2: Produce a PII-in-audit-records allowlist from the privacy risk assessment

AU-3(3) explicitly ties permitted PII elements to the privacy risk assessment output. You need a crisp artifact that an engineer can implement and an auditor can test. ¹

Recommended format (policy-grade) Create a matrix like:

System / log type	Purpose of audit record	Allowed PII elements	Prohibited examples	Masking/tokenization rule	Approval (Privacy)

Keep the “allowed PII elements” list specific (examples: internal user UUID; last 4 digits of employee ID; pseudonymous customer token). Avoid vague entries like “user info.”

Decision rule: If you can’t justify a PII field’s presence in audit records, it does not belong there. ¹

Step 3: Standardize logging requirements for engineering (secure logging standard)

Write a short “Audit Logging Data Standard” that engineering can follow. Include:

• Approved identity fields (prefer pseudonymous identifiers over direct identifiers where feasible).
• Explicit prohibitions (passwords, secrets, full payment data, raw request bodies by default, session tokens).
• Handling rules for free-text fields (error messages, stack traces) that can accidentally embed PII.
• Rules for logs sent to third parties (data minimization plus contractual/TPRM alignment). ²

Practical tip: Most PII leakage happens in “miscellaneous” fields, not in structured identity fields.

Step 4: Implement technical enforcement in log generation and pipelines

You need controls that work even when teams forget.

Common enforcement patterns:

• Application logging libraries/wrappers that filter or redact fields before writing.
• Schema-based logging (structured JSON logs) with field allowlisting.
• Ingress pipeline filtering (log forwarders, collectors) that drop or redact disallowed keys.
• Tokenization/pseudonymization for identity correlation without direct identifiers.
• DLP-style detection for logs as a compensating control: alert and quarantine if disallowed patterns appear in log streams. ²

Minimum expectation for audits: show that the allowlist is not just a document; it is implemented in configurations, code, or pipeline rules.

Step 5: Add change control hooks (keep it from regressing)

AU-3(3) breaks quietly over time. Add two gates:

• SDLC gate: logging changes that introduce new fields require review against the allowlist.
• Privacy/security sign-off: a lightweight approval workflow if a team needs to add a new PII element to audit records, with the privacy risk assessment updated accordingly. ²

Step 6: Validate with sampling and targeted tests

Create a repeatable test:

• Pull representative log samples from each major source.
• Confirm only allowed PII fields appear.
• Confirm masking rules are applied consistently.
• Document exceptions and remediation.

If you use Daydream to manage evidence and control operations, treat the sampling output as recurring evidence tied to AU-3(3) with clear owners, due dates, and reviewer sign-off. ²

Required evidence and artifacts to retain

Auditors usually want “decision + implementation + proof.”

Decision artifacts

• Privacy risk assessment output or excerpt that identifies permitted PII elements for audit records. ¹
• Approved “PII elements allowed in audit records” matrix with version history and approvals.

Implementation artifacts

• Logging standard / secure logging requirements document.
• Configuration screenshots/exports for:
  • Logging library settings
  • Log forwarder and pipeline filters/redaction rules
  • SIEM field mappings and ingestion rules (if used)
• Change management records for updates to logging fields and allowlist.

Operational proof

• Sanitized log samples demonstrating compliance (date/time, system, log type).
• Exception register (what’s out of standard, why, compensating controls, target remediation).
• Periodic review record confirming the allowlist still matches the privacy risk assessment. ²

Common exam/audit questions and hangups

Expect these, and pre-answer them in your evidence package:

1. “Show me the privacy risk assessment output that defines allowed PII in audit records.” ¹
   Hangup: teams have a generic privacy assessment but no log-specific decisions.

2. “Which systems generate audit records, and how do you prevent extra PII from being logged?” ²
   Hangup: undocumented log sources (serverless, managed services, SaaS).

3. “Prove it with data. Provide log samples.”
   Hangup: samples contain sensitive data and can’t be shared. Provide redacted samples plus evidence of the redaction rule configuration.

4. “What about logs shared with third parties?” ²
   Hangup: APM/SIEM vendors ingest raw events that contain PII by default.

Frequent implementation mistakes and how to avoid them

Mistake 1: Writing a policy without an allowlist.
Fix: publish a field-level allowlist tied to the privacy risk assessment, per system/log type. ¹

Mistake 2: Treating “username/email” as harmless.
Fix: assume identifiers are PII unless your privacy program has a clear classification that says otherwise, then follow the allowlist.

Mistake 3: Ignoring free-text logs.
Fix: constrain stack traces and error logging, and add scanning/detection for accidental PII in message fields.

Mistake 4: Allowing request/response bodies into logs by default.
Fix: disable by default; create narrowly-scoped break-glass debugging with time-bound approvals and documented handling.

Mistake 5: No sustained testing.
Fix: schedule recurring sampling and exception review, and store it as routine evidence.

Enforcement context and risk implications

No public enforcement cases were provided in the source material for AU-3(3), so treat this as an assessment-driven requirement rather than a “case law” control. The risk is still concrete: excess PII in audit logs increases breach exposure, expands incident scope, complicates data subject requests, and creates unnecessary third-party sharing risk when logs are exported to service providers. ²

Practical 30/60/90-day execution plan

First 30 days (stabilize and define)

• Assign ownership and map the audit logging data flow (sources, pipelines, destinations, third parties).
• Extract or create the privacy risk assessment decision points specific to audit records. ¹
• Publish the initial allowlist matrix for top systems (highest data sensitivity and highest log volume first).
• Implement “stop the bleeding” quick wins: disable raw request body logging where it exists; redact obvious identifiers in high-risk logs.

Days 31–60 (enforce and evidence)

• Roll out structured logging and field allowlisting patterns across priority applications.
• Configure log pipeline filtering/redaction rules at central collectors.
• Establish the change control gate for new log fields and new PII elements.
• Produce the first evidence pack: allowlist, approvals, configs, and sanitized log samples.

Days 61–90 (operationalize and sustain)

• Expand coverage to remaining systems and third-party log destinations.
• Run a sampling-based control test and track exceptions to closure.
• Add recurring reviews: align allowlist updates with privacy risk assessment updates and system changes. ²
• In Daydream, map AU-3(3) to the control owner, implementation procedure, and recurring evidence artifacts so audits don’t become a scramble. ¹

Frequently Asked Questions

Do we have to remove all PII from audit logs to satisfy AU-3(3)?

No. AU-3(3) allows PII in audit records, but only the specific elements identified as necessary in the privacy risk assessment. Keep an explicit allowlist and enforce it technically. ¹

What counts as “PII elements” for this requirement?

Treat any field that identifies or can reasonably be linked to a person as PII for this control, then decide which of those fields are permitted in audit records based on your privacy risk assessment output. Document the exact elements by name. ¹

Our engineers need rich logs for debugging. How do we balance that with AU-3(3)?

Keep audit logs minimal and structured, and separate “debug logging” into tightly controlled, time-bound workflows with masking and approvals. The default path must follow the allowlist. ²

Does AU-3(3) apply to SIEM events and security telemetry?

Yes, if the SIEM records contain audit records with PII. Your allowlist should cover both app-generated logs and security tooling outputs, plus any transformations in the pipeline. ²

How do we show evidence without exposing sensitive log data to auditors?

Provide sanitized log extracts that demonstrate field presence/absence and masking behavior, plus the configuration artifacts that implement filtering/redaction. Pair this with the allowlist and the privacy risk assessment decision record. ¹

What about logs sent to third-party monitoring or support providers?

Treat outbound log sharing as part of the logging boundary. Apply the same allowlist and filtering before export, and confirm third-party data handling expectations through your third-party risk management process. ²

Footnotes

1. NIST SP 800-53 Rev. 5 OSCAL JSON

2. NIST SP 800-53 Rev. 5