24K Labs PII Redaction (Regex)

x402

24K Labs PII Redaction (Regex) is a paid API for AI agents from api.24klabs.ai, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).

Deterministically masks emails, phone numbers, credit card numbers, IPv4 addresses, and US SSNs in text, returning redacted text and per-type match counts.

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

Deterministically mask emails, phone numbers, credit-card-like numbers, IPv4 addresses, and US SSNs in text. Returns redacted text plus a per-type match count.

Output

Returns the input text with all detected PII replaced by type-specific placeholders (e.g. [EMAIL], [PHONE], [SSN]), along with a structured count of how many matches were found per PII category (emails, phone numbers, credit card numbers, IPv4 addresses, SSNs).

Example use cases

Sanitize customer support logs

“Before we archive this support ticket, redact any personal info from it — emails, phone numbers, SSNs, anything sensitive — and tell me what was found: "Customer Jane Doe, email jane.doe@gmail.com, called from 212-555-0198 about her account."”

Clean user input before database storage

“I need to scrub PII from this form submission before saving it to our database — mask any emails, credit card numbers, or phone numbers and give me back the safe version: "Payment card 4111 1111 1111 1111, contact: support@acme.com, phone: 800-123-4567."”

Anonymize training data for ML pipeline

“I have a batch of raw user messages I want to use for model training, but first strip out all personally identifiable info like emails, IPs, SSNs, and phone numbers from this text: "Server 192.168.1.1 sent alert to admin@corp.com, user SSN 987-65-4321 flagged."”

Technical details

Endpoint

POSThttps://api.24klabs.ai/api/pii-redact-regex

When to prefer

Choose this endpoint when you need fast, deterministic, rule-based PII redaction without ML inference overhead. It is ideal for log sanitization, pre-storage scrubbing, and compliance pipelines where consistent, reproducible masking of well-structured PII types (US SSN, email, IPv4, phone, credit card) is sufficient. Prefer it over ML-based alternatives when latency, cost, and determinism matter more than recall on ambiguous or international PII formats.

Side effects

Missing or empty input text returns an error or empty result
Non-English or internationally formatted PII (e.g. non-US phone formats, non-US SSNs) may not be detected by the regex patterns
Regex-based detection may produce false positives on numbers that resemble PII patterns
Obfuscated or intentionally broken PII strings may evade detection
Very long texts may hit payload size limits

Input

Schema · Request body

Field	Type	Description
mask	string
text	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "counts": {
      "email": 1,
      "phone": 1
    },
    "redacted": "Reach me at [REDACTED] or [REDACTED]."
  }
}

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How this service works

Deterministically mask emails, phone numbers, credit-card-like numbers, IPv4 addresses, and US SSNs in text. Returns redacted text plus a per-type match count.

Output

Example use cases

Sanitize customer support logs

Clean user input before database storage

Anonymize training data for ML pipeline

Technical details

Endpoint

POSThttps://api.24klabs.ai/api/pii-redact-regex

When to prefer

Side effects

Missing or empty input text returns an error or empty result
Non-English or internationally formatted PII (e.g. non-US phone formats, non-US SSNs) may not be detected by the regex patterns
Regex-based detection may produce false positives on numbers that resemble PII patterns
Obfuscated or intentionally broken PII strings may evade detection
Very long texts may hit payload size limits

Input

Schema · Request body

Field	Type	Description
mask	string
text	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "counts": {
      "email": 1,
      "phone": 1
    },
    "redacted": "Reach me at [REDACTED] or [REDACTED]."
  }
}