What Is PII Detection?
PII detection identifies personally identifiable information in text — emails, phone numbers, government IDs, and more. Learn what it covers and where it fits in AI pipelines.
Blog / Data Protection
PII detection, secrets scanning, redaction, and data leakage prevention for AI pipelines.
PII detection identifies personally identifiable information in text — emails, phone numbers, government IDs, and more. Learn what it covers and where it fits in AI pipelines.
Use a PII detection API to scan user input, logs, and LLM context. Request format, response fields, verdict semantics, and integration patterns.
Redact or mask sensitive data before it reaches an LLM. Learn preprocessing patterns, placeholder strategies, and when to block instead of redact.
LLM data leakage happens when sensitive information enters prompts, context, logs, or model output. Understand common causes and practical prevention controls.
API keys in prompts, retrieved documents, and chat history are a common leakage path. Learn detection, redaction, and architectural controls.
Detect private keys, bearer tokens, cloud credentials, and high-entropy secrets in LLM inputs and outputs before they cause a breach.
PII detection and DLP overlap but serve different scopes. Compare real-time text scanning vs enterprise data governance and when to use each.
Scan user-submitted text for usernames, passwords, tokens, and credential pairs before storage, logging, or LLM forwarding.
Redaction removes values, masking partially hides them, tokenization replaces them with reversible references. Compare approaches for LLM pipelines.
Card-number detection needs format checks and Luhn validation — not every long digit string is a PAN. Learn reliable detection patterns.
Identify private key blocks, bearer tokens, and cloud API key formats in text before they reach logs, models, or third-party services.
Design a privacy filter that scans, redacts, or blocks sensitive input before every LLM request — architecture, failure modes, and testing.
A practical checklist to prevent PII and secrets from entering prompts, logs, retrieval indexes, and model outputs.