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NoJunk Moderate PII Detection
x402
NoJunk Moderate PII Detection is a paid API for AI agents from nojunk-moderate.mick8511.workers.dev, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-30).
Detects and optionally redacts personal data (email, phone, SSN, credit card, IP, IBAN, crypto address, name, address, DOB, passport) with character offsets in free text
Price / call$0.003
Success—
StatusUnknown
How this service works
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].
Output
Returns a list of detected PII entities, each with its type (e.g. email, phone, ssn, credit_card, ip, iban, crypto_address, name, address, date_of_birth, passport) and character offsets indicating where in the text it was found. If redact=true, also returns a redacted version of the input text with each entity replaced by [TYPE].
Example use cases
Redacting PII before logging
“Before we store this user chat message in our logs, scan it for any personal info — emails, phone numbers, names, addresses — and give me a redacted version with everything replaced by its type label.”
Compliance audit of uploaded document
“I need to check this contract text for any personally identifiable information like SSNs, passport numbers, dates of birth, or credit card numbers, and tell me exactly where in the text each one appears.”
Filtering crypto addresses from posts
“Can you scan these user-submitted forum posts and flag any cryptocurrency wallet addresses or IBAN numbers, including their character positions so I can highlight them in my UI?”
Technical details
Endpoint
POSThttps://nojunk-moderate.mick8511.workers.dev/pii?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need character-level PII detection with precise offsets for highlighting or downstream processing, and especially when you need Luhn-validated credit card detection or IBAN/crypto address recognition alongside traditional regex-based types. It also supports LLM-powered detection of harder-to-regex entities like names, addresses, and passport numbers in the same call. Prefer it over generic regex scripts when you need a managed, pay-per-call API with optional in-place redaction.
Side effects
- Text exceeds 20,000 character limit — returns validation error
- Empty or missing text field — returns 400 error
- Invalid type enum value in types array — returns schema validation error
- LLM-based types (name, address, date_of_birth, passport) may have lower recall or produce false positives on ambiguous text
- Credit card detection uses Luhn check — invalid card-like numbers are correctly excluded
- Payment failure (x402) if USDC balance is insufficient
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | The text to scan (1 to 20000 characters) |
| types | array | Subset of types to detect (default all). Regex types: email, phone, ssn, credit_card, ip, iban, crypto_address. LLM types: name, address, date_of_birth, passport |
| redact | boolean | true also returns `redacted`: the text with each entity replaced by [TYPE] |
Tags
x402
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