Core
PII Handling and Redaction
Personal data leaks into AI systems through three doors: the prompt you send a model API, the logs you keep for debugging, and the traces you store for evaluation. Handling it means detecting and redacting personal data before it crosses any of those boundaries, then minimizing, encrypting, access-controlling, and expiring whatever you must keep. In regulated industries, logging a raw prompt is the single most common compliance failure.
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Related concepts
Practise this in questions
AI Security, Privacy & GovernanceCompare PII detection methods, regex, entropy, NER, external APIs. Why can't regex alone find a person's name? →easy · Free with sign-inAI Security, Privacy & GovernanceDesign a PII redaction system for an LLM pipeline, PII enters at user input, retrieved context, tool results, and output. Guard all four. →hard · Free with sign-inLLM & GenAI FundamentalsA customer refuses to send PII to an LLM API. What are your options? →medium · PremiumAI Security, Privacy & GovernanceShould PII redaction live at the AI gateway or in the application layer? Argue the trade-offs. →medium · Free with sign-inAI Security, Privacy & GovernancePrompts and outputs contain personal data. What does GDPR mean for each call to an external LLM endpoint? →medium · Free with sign-inBehavioral & Customer ScenariosCISO ambush: 'Where does our data go? Do you train on it? SOC 2? Residency?', all before your first slide. →hard · Premium
