output-sanitizer

To redact API keys and PII from AI agent output, apply a post-processing sanitization module that uses pattern-based detection and masking rules to obscure credentials, email addresses, and phone numbers before responses are displayed or logged.

Output sanitization for agent security is a post-processing technique that detects and masks sensitive information, such as personally identifiable information and internal system paths, to prevent accidental data leakage in displayed or logged AI responses.

To prevent internal system paths from leaking in agent responses, implement output sanitization rules that detect sensitive file paths and hostnames, replacing them with generalized placeholders before the content is shared or logged.

Yes, you can use pattern-based detection to mask credentials in logged responses. This sanitization approach automatically identifies and obscures API keys, passwords, and tokens during the post-processing phase of agent output handling.

Yes, output sanitization works as a post-processing module for code review comments. It ensures that any accidentally quoted API keys or internal server paths within the review comments are redacted before the output is shared with the team.

Pattern-based detection for data redaction relies on predefined masking rules and patterns, meaning it may not identify sensitive information that lacks recognizable structural formats or falls outside of configured credential, PII, and internal path detection rules.