pii-masker-ai 🔒🤖

Ultra-fast, zero-dependency PII masking, redaction, and de-identification for AI prompts, LLM agents, and datasets.

Prevent sensitive customer data (Emails, Phone Numbers, Credit Cards, Citizen IDs, API Keys, Private Keys, IP Addresses) from leaking into external AI models (Claude, OpenAI, Gemini).

⚡ The AI Privacy Problem & Solution

sequenceDiagram
    participant User
    participant PII_Masker as pii-masker-ai
    participant LLM as Claude / OpenAI / Gemini
    
    User->>PII_Masker: "Contact John at john@company.com with phone 0912345678"
    Note over PII_Masker: Reversible Masking
    PII_Masker->>LLM: "Contact John at <EMAIL_1> with phone <PHONE_1>"
    LLM->>PII_Masker: "Scheduled an appointment for <EMAIL_1> via <PHONE_1>."
    Note over PII_Masker: Automatic Unmasking
    PII_Masker->>User: "Scheduled an appointment for john@company.com via 0912345678."

🌟 Key Features

• Zero dependencies: Written in 100% pure Python standard library. Instant install, zero attack surface.
• 4 De-identification Modes:
  1. reversible: Sequential numbered tokens (<EMAIL_1>, <PHONE_1>) for LLM chat round-trips.
  2. redact: Fixed redaction tags ([EMAIL], [API_KEY]) for audit logs and security reporting.
  3. hash: Salted SHA-256 pseudonym digests (<EMAIL_a1b2c3d4>) for persistent agent memory & cross-session consistency.
  4. synthetic: Realistic fake dummy data (user1@example.com, +84901234561) for realistic model reasoning.
• Allowlist & Safe Exemption: Safely exempt public support emails, internal company domains, or localhost IPs.
• LangChain & LLM Chat Wrapper: Wrap any LLM or ChatModel in 1 line of code with automatic prompt masking and response unmasking.
• Batch Dataset Sanitizer: High-speed CLI to sanitize .jsonl, .csv, and .txt datasets with column/field targeting.
• Comprehensive Pattern Suite (v0.3.0):
  • Financial: Credit cards (Visa, MasterCard, Amex, Discover, JCB) with Luhn algorithm verification, IBAN bank codes.
  • Network: IPv4, IPv6 addresses, MAC addresses.
  • Secrets & API Keys: JWT tokens, PEM Private Keys (RSA, EC), OpenAI, Anthropic, GitHub, AWS, Slack, Stripe, Google Cloud.
  • Global & Regional: Email, US SSN, International phone (E.164), Vietnam Citizen ID (CCCD/CMND), Tax ID, Passports.

📦 Installation

pip install pii-masker-ai

🚀 Quickstart (Python API)

1. Reversible Masking for LLMs

from pii_masker import mask_text, unmask_text

# 1. Mask prompt before calling Claude / OpenAI
prompt = "Please send invoice #123 to customer alice@example.com, phone 0912345678."
result = mask_text(prompt, reversible=True)

print(result.masked_text)
# Output: "Please send invoice #123 to customer <EMAIL_1>, phone <PHONE_1>."

# 2. Call your LLM with masked_text...
llm_response = "I have drafted the invoice for <EMAIL_1> and notified <PHONE_1>."

# 3. Restore original customer PII in the response
final_output = unmask_text(llm_response, result.mapping)
print(final_output)
# Output: "I have drafted the invoice for alice@example.com and notified 0912345678."

2. LangChain & Claude Chat Wrapper

from pii_masker.integrations import PIIChatWrapper
from langchain_anthropic import ChatAnthropic

base_model = ChatAnthropic(model="claude-3-5-sonnet-20241022")

# Shield your LLM: automatically sanitizes prompts & unmasks responses
shielded_model = PIIChatWrapper(base_model)

response = shielded_model.invoke("Send email to alice@company.com with bill $500")
print(response.content)

3. Pseudonymization (Hash Mode) & Synthetic Data

from pii_masker import PIIMasker, MaskMode

masker = PIIMasker(salt="company-secret-salt", allowlist=["support@mycompany.com"])

# Hash mode for persistent agent memory
res_hash = masker.mask("User dev@corp.io reported an issue", mode=MaskMode.HASH)
print(res_hash.masked_text)
# Output: "User <EMAIL_8f2b3e41> reported an issue"

# Synthetic replacement
res_synth = masker.synthetic_mask("Customer phone is 0912345678")
print(res_synth.masked_text)
# Output: "Customer phone is +84901234561"

💻 CLI Usage

Masking text

# Reversible masking
pii-masker mask "My email is alice@company.com"

# Redact mode
pii-masker mask "Contact support@example.com" --mode redact

# Output JSON with mapping
pii-masker mask "User 0912345678" --json --save-mapping map.json

# Restore text
pii-masker unmask "Hello <PHONE_1>" -m map.json

Batch Dataset Sanitization (JSONL & CSV)

# Sanitize fine-tuning or training datasets
pii-masker batch -i raw_dataset.jsonl -o clean_dataset.jsonl --fields prompt,response --mode redact

# Sanitize CSV customer data
pii-masker batch -i users.csv -o safe_users.csv --fields email,phone --mode synthetic

Scanning files for PII leaks (CI/CD friendly)

# Returns exit code 1 if any PII leak is found
pii-masker scan ./data/ --strict

🌍 Supported PII Categories

🤝 Community: Add Your Country's PII Rules!

We are actively expanding localized PII regex rules for more countries! Beginner contributors can easily add new rules in under 15 minutes:

• 🇫🇷 France (NIR / Carte Vitale)
• 🇯🇵 Japan (My Number)
• 🇩🇪 Germany (Steuer-ID)
• 🇬🇧 UK (National Insurance Number)

Check out CONTRIBUTING.md to claim a country module!

📄 License

MIT License © 2026 lui01212