LLM Output Scanner
The model answered. Before that answer goes into a ticket, a report or a customer's inbox: did it reproduce someone's e-mail, IBAN or an API key from its context, and which of its confident citations has a human actually opened? Paste the output, get the sensitive values masked and every reference as a checklist.
Sensitive data reproduced in the output
| Line | Type | Source | Severity | Value | What it means |
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Citations, URLs and figures to verify
Redacted copy
Why the output side is different. The LLM Pre-flight Redactor stops you sending sensitive data into a model. This tool looks at what came out: a model can reproduce a customer's e-mail or an access key it saw in the retrieved documents, the conversation, or its training data, and it can cite a paper, a URL, a CVE or a regulation article that does not exist or does not say what it claims (OWASP LLM Top 10: Sensitive Information Disclosure, Improper Output Handling, Misinformation — see the OWASP LLM Top 10 Checker). Personal data comes from the same detector library as the Pre-flight Redactor and the Log Snippet Anonymizer; credentials from the same rule set as the Secrets & Credential Leak Scanner. Regulatory articles link to the Compliance Reference Database so you can read the article the model quoted; CVEs link to NVD, DOIs to doi.org, RFCs to the RFC Editor. Rule sets . Informational only: a citation the tool lists is neither confirmed nor refuted, and text with nothing flagged can still be wrong.