Redact sensitive data before agent telemetry leaves the application whenever practical, and treat redaction as one part of a broader logging policy. First map every place agent data is recorded, decide which data must not be retained, filter or transform it, then verify the resulting logs. Access controls and retention limits are also necessary: hiding a field from some users does not necessarily remove it from storage.
Where sensitive data can enter agent logs
An AI agent can pass sensitive content through more than its prompt and final answer. Logs and traces may capture retrieved documents, memory or state snapshots, tool-call arguments and results, error messages, and span attributes. OWASP identifies sensitive data in agent context or logs as an exposure risk, and AWS notes that prompts and responses can contain user messages, retrieved documents, and personal data (OWASP guidance on agent risks; AWS CloudWatch GenAI observability documentation).
Include application logs, model-provider records, and cloud audit logs in the inventory. A filter applied to one trace exporter will not necessarily cover a separate application logger or provider-side record.
Decide what should be excluded or transformed
Start with the logging system’s classification and authorization limits. OWASP’s logging guidance identifies data that should generally not be recorded directly, including credentials and access tokens, passwords, encryption keys, sensitive personal data, payment information, session identifiers, connection strings, source code, commercially sensitive data, and information the logging system is not authorized to store. OWASP’s rule is direct: “Never log data unless it is legally sanctioned.” (OWASP Logging Cheat Sheet).
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- Delete: Use when the original value is not needed for debugging, security monitoring, or an approved business purpose.
- Mask: Keep only the portion needed for diagnosis, such as a non-sensitive suffix, when partial visibility is useful.
- Pseudonymize or hash: Use when correlation across events is required, and the method and resulting identifiers can be safely managed.
- Encrypt: Consider only where authorized retention of the underlying value is necessary; encryption does not make unrestricted logging appropriate.
Do not rely only on matching field names. Sensitive values can appear in nested objects or free-form prompts, retrieved text, and tool payloads. No single detector should be assumed to find every sensitive value in every format.
Redact before telemetry is exported
Filtering inside the agent process can prevent raw values from reaching telemetry destinations in the first place. AWS documents configurable span-attribute redaction for supported agent instrumentation, OpenInference flags to hide input or output content before spans are created, and custom span processors for more selective filtering. AWS also warns that removing attributes may affect integrations that depend on them, so test the specific instrumentation and downstream consumers before deploying a change (AWS CloudWatch GenAI observability documentation).
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AWS states: “CloudWatch Omni does not automatically detect or redact personally identifiable information (PII); no data is removed unless you configure it.” Check the exact product and instrumentation rather than assuming a default will protect logs.
If suitable in-process filtering is unavailable, a controlled processor at the telemetry pipeline boundary can filter or transform data before it reaches broader storage and analytics systems. Define what happens when that processor is unavailable or cannot parse an event; the filtering path must not silently allow raw telemetry to flow to destinations that should not receive it.
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Separate redaction, permissions, and retention
These controls address different risks. Redaction changes or removes a value; access control limits who can see it; retention policy limits how long a record is kept. Google Cloud Logging field-level access controls can hide individual LogEntry fields, such as an email address in a payload, from users without the relevant permission. That is a visibility control, not proof that the underlying stored value has been deleted or irreversibly redacted. Google also notes that field-level access controls may affect use of Observability Analytics on the relevant log bucket, so check the intended analytics workflow before enabling them (Google Cloud field-level access control documentation).
- Grant log access by role and purpose, following least privilege.
- Define retention and deletion rules alongside data classification.
- Use encryption in transit and at rest as part of the logging design.
- Make raw-content retention exceptional, time-limited, and access-controlled when an investigation or approved purpose genuinely requires it.
OWASP’s AI-agent security guidance recommends data minimization, classification, retention and deletion policies, and encryption in transit and at rest (OWASP guidance on agent risks; OWASP Logging Cheat Sheet).
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Provider-specific details to check
AWS CloudWatch
CloudWatch Omni does not automatically detect or redact PII. Configure supported redaction explicitly, and verify which span attributes and input/output content your instrumentation actually emits. Custom processing and hiding input or output may be available, but behavior depends on the instrumentation and can affect integrations that consume those attributes (AWS documentation).
Google Cloud Logging
Field-level access controls restrict visibility of selected LogEntry fields; they should not be treated as data removal. Assess any impact on Observability Analytics for the affected bucket before applying the control (Google Cloud documentation).
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Dialogflow CX and conversational-agent metadata
A Google Cloud article published December 16, 2021 describes Dialogflow CX parameter redaction and SecuritySettings-based options. Because that article is dated, confirm the current product documentation and configuration before relying on those exact controls (Google Cloud article on Dialogflow CX redaction).
Google also advises against putting protected health information or credentials in conversational-agent definitions and notes that resource metadata may be captured in logs. Avoid placing sensitive values in agent names, definitions, or metadata under the assumption those fields are outside logging (Google Cloud conversational-agent data logging documentation).
Validate coverage before rollout and after changes
Test the actual data paths and destinations, not just the redaction rule in isolation. Use representative structured and unstructured examples, including nested fields and unexpected formats, then inspect the stored output to confirm sensitive values are absent or transformed as intended.
- Exercise prompts, model completions, retrieved content, memory or state, tool arguments, tool results, errors, and trace attributes.
- Check every destination, including application logs, telemetry backends, analytics stores, and provider audit records where applicable.
- Confirm that redaction has not removed fields required for security monitoring or business operations.
- Re-run the checks after changing an agent framework, model provider, instrumentation package, processor, or telemetry destination.
There is no universal detection-accuracy figure established for these approaches. Coverage must be verified for the specific agent, instrumentation, and log destinations in use.
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