Redact PII from JSON Payloads

The problem with PII in JSON payloads

Modern applications pass JSON everywhere: API requests, logs, analytics events, background jobs, and LLM prompts. When those payloads contain personally identifiable information (PII), every system they touch becomes a potential compliance risk.

Common examples include:

• User emails and phone numbers embedded in request bodies
• IP addresses and identifiers stored in logs
• Payment details included in debugging payloads
• Raw user data sent to LLMs or third-party APIs

Manually removing PII from JSON is slow, error-prone, and easy to get wrong.

Why manual JSON redaction fails

Developers often try to sanitize JSON by:

• Deleting entire fields
• Using ad-hoc string replacements
• Maintaining fragile allowlists or denylists

These approaches break schemas, remove useful context, and frequently miss nested or repeated PII values.

Worse, partial redaction can create a false sense of security — leaving regulated data behind in production logs or AI prompts.

Deterministic PII redaction for structured JSON

Maskify redacts PII from JSON payloads using deterministic, rule-based detection. Sensitive values are replaced in place while the original structure remains intact.

• Nested objects and arrays are handled correctly
• Non-PII fields are left untouched
• Output remains valid, schema-safe JSON
• Identical input always produces identical output

Example: JSON PII redaction

{
  "user": {
    "id": "user_48291",
    "email": "alex.smith@example.com",
    "phones": ["+1 (415) 555-0199"]
  },
  "session": {
    "ip_address": "203.0.113.42"
  },
  "payment": {
    "card_number": "4000 1234 5678 9010",
    "billing_email": "billing@example.com"
  }
}

{
  "user": {
    "id": "user_48291",
    "email": "[EMAIL]",
    "phones": ["[PHONE]"]
  },
  "session": {
    "ip_address": "[IP_ADDRESS]"
  },
  "payment": {
    "card_number": "[CREDIT_CARD]",
    "billing_email": "[EMAIL]"
  }
}

JSON structure is preserved. Only regulated identifiers are replaced.

Common use cases

• Sanitize logs before sending data to Datadog, Splunk, or Sentry
• Redact PII from API payloads during debugging
• Clean JSON data before sending prompts to LLMs
• Prepare datasets for testing, demos, or documentation
• Reduce GDPR, SOC 2, and HIPAA compliance risk