You can make AI agents observable without saving their private conversations: log structured event metadata by default, keep prompts and tool data out of ordinary traces, and add narrowly scoped content capture only when a documented debugging or audit need requires it. Redact sensitive values before writing any record—not merely when displaying it.
What to log from an AI agent
Record enough context to reconstruct the sequence and outcome of an agent’s work without retaining the content it handled. OWASP’s Logging Cheat Sheet frames the core fields as “when, where, who and what.” For agent events, that means a timestamp, application or agent identity, event or step type, severity, tool name when relevant, authorization outcome where applicable, execution status, and an interaction or trace identifier that already exists.
- When and where: timestamp and service, component, or environment.
- Who: the relevant application, agent, service identity, or authenticated actor, subject to your access and privacy model.
- What happened: event type or decision/step category, tool name, authorization result, and success, failure, or other status.
- How events connect: an existing interaction or trace identifier, if the application already has one.
Use an application-wide structured logger or handler rather than scattered print statements. Consistent fields make records easier to filter and correlate, and provide a single place to apply redaction and access rules. OpenTelemetry’s GenAI semantic conventions describe attributes for generative-AI operations; pin the convention and instrumentation versions used by your implementation because these are living specifications.
What to leave out by default
Treat prompts, system and developer instructions, model outputs, retrieval queries, retrieved text, tool arguments, and tool results as potentially sensitive. They can contain credentials, personal information, confidential business data, or information supplied by an external source. Do not include message bodies in routine logs simply because a logging library makes them convenient to capture.
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OpenTelemetry’s content-capture guidance says instrumentation should not capture model instructions, user messages, or model outputs by default, while providing an option for users to opt in. Apply the same conservative default to retrieval and tool data: keep traces to metadata unless you have a defined reason to retain content.
Choose a content-capture design deliberately
There are three practical patterns. The right choice depends on how much content is truly needed and whether it can be governed separately from operational telemetry.
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| Approach | Privacy exposure | Troubleshooting detail | Access separation | Storage and retention burden |
|---|---|---|---|---|
| Metadata-only traces | Lowest of these options; conversation and tool contents are excluded. | Shows sequence, tool use, authorization, and outcomes, but not the private content that produced them. | Operational trace access still needs protection. | Lowest content-retention burden. |
| Opt-in content on traces | Higher: sensitive content is stored with operational telemetry. | Can expose the recorded content for an approved debugging or audit purpose. | Content shares the trace system’s access boundary unless additional controls are applied. | Greater storage, access-control, retention, and deletion burden. |
| Content stored separately, with a reference in traces | Content remains sensitive, but can be governed apart from routine traces. | Provides access to content when authorized and available. | Can support separate access controls for content and telemetry. | Adds infrastructure and requires coordinated retention and deletion rules. |
For a production system that genuinely needs full content, consider a separately controlled store and retain only a reference in the trace. This can separate operational access from content access, but does not remove the need to set and enforce retention, deletion, and authorization rules for both systems.
Redact before records are written
Sanitize sensitive values in the logging path before serialization and persistence. Masking a value only in a dashboard or log viewer does not remove the original from stored records. OWASP’s Logging Cheat Sheet advises excluding sensitive data and sanitizing event data, while its AI Agent Security Cheat Sheet addresses agent-specific risks.
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- Exclude or redact credentials, API keys, access tokens, passwords, sensitive personal identifiers, and confidential fields.
- Inspect nested tool payloads and arbitrary strings, not only fields whose names look sensitive. A secret can appear inside free text or a serialized value.
- Validate event values and sanitize untrusted input so it cannot forge log records or alter their structure.
- Encode values correctly for the output format and protect log access.
Prefer allowlisted event fields over copying whole request, response, or tool objects and attempting to remove sensitive fields afterward. An allowlist makes the default record shape explicit; redaction is still needed for sensitive values that occur in fields you do retain.
Preserve correlation without deriving IDs from private content
Use an interaction or trace identifier only when the system already provides one. Do not create a fallback conversation ID, trace ID, or content hash from a prompt or other private content when no identifier is available. OpenTelemetry’s agent-span conventions caution against inventing such fallback identifiers. A hash is not automatically anonymous: it can preserve a link to the underlying content or permit guesses against predictable inputs.
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Make any content capture bounded and explicit
If metadata cannot answer a specific debugging or audit question, define the purpose and scope before enabling content capture. Make it opt-in rather than the default, restrict who can enable and read it, specify how long records remain, and provide a deletion process. Keep the captured fields and time window as narrow as the use case permits.
- State the need: identify the concrete failure or audit question that metadata cannot resolve.
- Limit the capture: select only the necessary content types and a bounded set of requests or events.
- Control access: authorize the smallest appropriate group and protect the storage location.
- Set lifecycle rules: define retention and deletion for traces and any separate content store or referenced object.
- Turn capture off: make the end condition explicit and verify the normal metadata-only configuration is restored.
Test for leakage and failure modes
Privacy controls should be verified at the point where data is emitted and persisted, not just in the interface used to inspect logs. OWASP AISVS includes a check that normal requests do not leak prompt, response, retrieved-document, or tool-argument text into spans, events, or storage unless content capture is deliberately enabled. See the OWASP AI Security Verification Standard.
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- Send test values representing a prompt, model response, retrieved document, tool argument, credential, and sensitive personal identifier. Confirm they are absent or redacted in emitted events and stored records under the normal configuration.
- Test nested payloads, multiline and malformed values, and content that resembles log delimiters to check sanitization and resistance to log injection.
- Verify opt-in capture is actually disabled by default, and that enabling it changes only the approved scope.
- Check who can read logs and captured content, and confirm retention and deletion behavior for both traces and any separate store.
- Exercise resource-exhaustion cases and logging failures. Ensure a logging outage does not silently trigger a fallback that writes sensitive data elsewhere or destabilizes the agent’s primary operation.
Keep tests aligned with the OpenTelemetry convention and instrumentation versions you deploy. A change in instrumentation can alter emitted fields, so recheck what reaches spans and storage after upgrades.
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