What is PII Redactor?
The PII Redactor API automatically detects and removes personally identifiable information (PII) from text content before sending it to third-party services like LLMs, logging systems, or external APIs. This ensures compliance with privacy regulations like GDPR, CCPA, and HIPAA while maintaining the utility of your data.
Using high-performance compiled regex patterns for structured PII (emails, SSNs, credit cards, phone numbers, URLs, IP addresses, street addresses, and dates of birth), the API provides comprehensive protection with sub-200ms response times and zero external dependencies.
8 Entity Types
Emails, SSNs, phones, credit cards, URLs, IP addresses, street addresses, and dates of birth
Re-hydration Mapping
Optional mapping to restore original values after processing
Regex Detection
Compiled regex patterns for maximum speed and accuracy
Consistent Placeholders
Same PII value always maps to the same placeholder
Code Examples
curl -X POST https://api.atomicapis.dev/api/redact \
-H "X-RapidAPI-Proxy-Secret: YOUR_SECRET" \
-H "Content-Type: application/json" \
-d '{
"text": "Contact John Doe at [email protected] or call 555-123-4567. His SSN is 123-45-6789.",
"includeMapping": true
}'
Request Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
text |
string | Yes | The text content to analyze and redact PII from |
includeMapping |
boolean | No | If true, returns a mapping object for re-hydrating redacted values later. Default: false. |
Detected Entity Types
email
Email addresses
ssn
US Social Security Numbers
phone
US & international phone numbers
credit_card
Credit/debit card numbers
url
HTTP/HTTPS URLs
ip_address
IPv4 and IPv6 addresses
street_address
US street addresses
dob
Dates of birth (various formats)
Response Format
{
"redactedText": "Contact John Doe at [EMAIL_1] or call [PHONE_1]. His SSN is [SSN_1].",
"totalPiiFound": 3,
"piiCounts": {
"email": 1,
"phone": 1,
"ssn": 1
},
"mapping": {
"[EMAIL_1]": "[email protected]",
"[PHONE_1]": "555-123-4567",
"[SSN_1]": "123-45-6789"
}
}
Response Fields
| Field | Type | Description |
|---|---|---|
redactedText |
string | The input text with all detected PII replaced with placeholders |
totalPiiFound |
integer | Total number of PII entities detected |
piiCounts |
object | Counts of each PII type detected (e.g., email, phone, ssn, credit_card, url, ip_address, street_address, dob) |
mapping |
object | Key-value pairs for re-hydration (only if includeMapping is true) |
Use Cases
LLM Privacy
Sanitize user inputs before sending to third-party LLM providers like OpenAI, Anthropic, or Google. Prevent sensitive data from being stored in training datasets or logs.
// Pre-process user messages
const safeInput = await redactPII(
userMessage
);
const response = await openai.chat(
safeInput
);
Log Sanitization
Automatically scrub PII from application logs before shipping to centralized logging systems like Splunk, Datadog, or ELK. Maintain compliance with data retention policies.
# Sanitize before logging
sanitized = redact_pii(log_entry)
logger.info(sanitized)
Data Sharing
Share datasets with partners or analytics teams while preserving privacy. Use the re-hydration mapping to restore original values when data returns to your secure environment.
// Share anonymized data
const { redactedText, mapping } =
await redactPII(data, true);
// Later: restore with mapping
Build Constraints
Technical Implementation
Regex Detection Engine
Uses high-performance compiled regex patterns to detect structured PII including emails, SSNs, credit cards, phone numbers, URLs, IP addresses, street addresses, and dates of birth.
Single-Pass Processing
All entity detection happens in a single pass through the text, minimizing latency and maximizing throughput for high-volume applications.
Sub-200ms Response Time
Optimized for real-time applications. Average processing time is 40-80ms for typical text lengths up to 10,000 characters.
Zero External Dependencies
All detection uses AOT-safe compiled regex patterns that run efficiently with zero external dependencies and no GPU required.
Error Codes
| Code | Status | Description | Resolution |
|---|---|---|---|
400 |
Bad Request | Missing or invalid parameters | Check that text is provided and valid |
401 |
Unauthorized | Invalid or missing API key | Include a valid Authorization header |
429 |
Rate Limited | Too many requests | Wait before retrying or upgrade your plan |
413 |
Payload Too Large | Text exceeds 100KB limit | Split text into smaller chunks |
500 |
Server Error | Internal processing error | Retry the request; contact support if persistent |
Ready to protect your data?
Start redacting PII from your text data in minutes. Free tier includes 1,000 requests per month.
MCP Integration MCP Ready
What is MCP?
Model Context Protocol (MCP) allows AI assistants like Claude to call this API as a native tool during conversation. Instead of writing HTTP requests, the AI invokes the tool directly — no API keys or boilerplate needed on the client side.
Tool Details
PiiRedactorTools
RedactPii()
Description
Detects and redacts personally identifiable information from text