All projects on Base matching “pii”

Scan source code or configuration text for hardcoded secrets: AWS access keys, GitHub/Slack/Google tokens, Stripe and OpenAI keys, PEM private-key blocks, JWTs and high-entropy secret assignments. Placeholder values are filtered out. Each finding gives the rule, a severity (critical/high/medium/low), line and column, entropy and a masked excerpt. Offline and deterministic.

Scores JSONL rows using fixed rules and adds _quality. Detects some PII and bad-word patterns; optional redaction and score filtering. Detection is incomplete and can produce false positives. No AI.

Text Moderation pii: Detect personal data (email, phone, SSN, credit card with Luhn check, IP, IBAN, crypto address, name, address, date of birth, passport) with character offsets; optional redaction to [TYPE].

Overwing guardrail: check text before you send, post, or act on it. Content moderation, PII detection, confidential leak detection, toxicity, self-harm and severity in ~150 ms. Returns a verdict plus one recommended_action (block / redact / review / allow) with calibrated confidence. Pass context (recipient, channel, owns_contact_info) with the outbound-message set. $0.002 USDC, no account.

PII sanitization — pay-per-call entry point

Detect and redact PII in text or JSON. Recognizers are pure pattern/checksum matching (regex + Luhn/mod-97/SSN-area validation) — no LLM calls, no external services. Person names and dates of birth are matched only via nearby context (e.g. 'Mr. Smith', 'DOB: ...'), not general NER, to keep false positives low.