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Before storing AI-agent logs, remove or transform credentials, unnecessary personal data, confidential business information, and sensitive content carried in prompts, tool calls, retrieved material, or model responses. Keep structured security events and pseudonymous correlation data where policy permits, so an investigation can still establish what happened without retaining the sensitive values themselves.
What should be redacted from AI-agent logs?
OWASP’s Logging Cheat Sheet says: “The following should usually not be recorded directly in the logs, but instead should be removed, masked, sanitized, hashed, or encrypted.” Apply that principle to the full agent data path—not only the initial user prompt.
Credentials and secrets
- Access tokens, API keys, passwords, credentials, encryption keys, and other primary secrets.
- Session identifiers, database connection strings, and similar values that could enable access or expose how systems connect.
Where possible, prevent these values from entering logs at all. If an identifier is necessary for correlation, use a protected pseudonym or hash rather than the raw credential or session value. OWASP’s AI Agent Security Cheat Sheet demonstrates recursively masking fields such as password, api_key, token, secret, and credential before logging tool-call parameters; it also suggests hashed session IDs when session-specific tracking is needed.
Personal and regulated information
Remove or protect health information, government identifiers, payment-card and bank-account data, and direct or indirect identifiers—such as names, phone numbers, and email addresses—when they are not necessary for the logging purpose. Sensitivity depends on context, not just a fixed list of field names. NIST’s SP 800-122 advises identifying PII in context and choosing an appropriate protection level for each instance.
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Confidential or restricted business information
Do not store confidential user records or commercially sensitive content in a log store that is not permitted to hold it. The remaining data must fit the store’s allowed security classification; if it does not, remove it, transform it, or use an appropriately protected destination.
Agent payloads that carry sensitive data
Prompts are only one possible source. Agent context and memory, retrieved documents, external content, tool arguments and results, and model responses can all contain secrets, PII, or confidential information. OWASP’s agent guidance describes sensitive data in agent context and logs as a risk, while its LLM Prompt Injection Prevention Cheat Sheet addresses external inputs, interaction monitoring, tool controls, and output filtering. Treat each payload as a possible carrier and apply the same data rules before it is persisted.
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Operational details that could expose infrastructure
File paths, internal network names and addresses, and connection strings may help investigators, but can also reveal system structure. Decide whether each detail is necessary; mask or restrict it when the exposure risk outweighs its diagnostic value.
Why field-name filters are not enough
A filter that redacts keys named token or password is a useful layer, not a complete control. Sensitive values can be nested, encoded, mislabeled, or embedded in free text. OWASP’s example shows recursive handling of structured tool parameters, but it does not establish detection accuracy for any particular implementation. Combine structured-field rules with classification and other checks, then verify the behavior with representative safe test data. Do not assume a regular expression, key-name filter, or model-based detector catches every secret or identifier.
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Preserve the evidence needed to investigate
Redaction and observability solve different problems. The aim is to retain evidence about activity and decisions without retaining raw sensitive values simply because they are convenient for debugging. OWASP recommends monitoring security-relevant agent behavior and recording decisions, tool calls, outcomes, and structured metadata for high-risk actions.
A useful event design may retain, where policy allows:
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- Event type and timestamp.
- Agent and session pseudonyms rather than raw identifiers or credentials.
- Tool identity and the action or event category.
- Risk classification, authorization outcome, and approval reference.
- Policy version and execution result.
This is an implementation approach, not a universal required field set. Keep only the fields needed for your investigation and operational purpose, and ensure that correlation identifiers cannot be used as credentials.
For MCP-based systems
OWASP Foundation’s MCP08:2025 – Lack of Audit and Telemetry recommends tracing from prompt creation through tool invocation while masking or tokenizing user identifiers and redacting sensitive fields before storage. It also recommends labeling streams to govern access and retention. Restrict access to the log store and audit changes to its retention or deletion settings.
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Where and when to apply redaction
- Minimize collection at the source. Do not capture a value merely because it is available in a prompt, tool result, or context window.
- Redact or transform before persistent logging. Apply controls before data reaches log storage, traces, error reports, analytics exports, or third-party systems that receive copies.
- Check the whole agent flow. Include prompts, retrieved content, tool arguments and results, intermediate context or memory, and model outputs in the review.
- Control the destination. Classify retained data, limit access, and confirm that the log store is permitted to hold it.
- Set retention and deletion rules. Choose periods through applicable policy and legal review; the cited guidance does not prescribe one duration for every deployment.
Applicable collection and monitoring rules depend on jurisdiction, workforce, consent model, and sector. OWASP warns that some monitoring or collection may be unlawful without legal sanction or consent, so determine the requirements for the deployment rather than treating a general logging recommendation as legal clearance.
How to assess a redaction design
When reviewing an implementation, check whether it:
- Removes sensitive data before it reaches persistent logs.
- Covers structured and nested fields as well as free text and the different payload types an agent handles.
- Preserves safe correlation and enough event context to investigate activity.
- Has been evaluated with representative safe data for missed detections and unnecessary redactions; do not infer accuracy without measurements from your own environment.
- Applies access, retention, and deletion controls to the log store and downstream copies.
- Leaves only data permitted by the destination’s classification and the deployment’s jurisdictional requirements.
OWASP and NIST provide guidance for data handling and logging, but the cited material does not establish vendor-specific data flows or comparative detection performance. Verify every path that writes or exports logs in the system you operate.
Quick Recap
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