[CloakLLM]

Cloak your prompts. Prove your compliance.

Open-source PII protection middleware for LLMs. Detect sensitive data, replace it with reversible tokens, and maintain tamper-evident audit logs — all before your prompts leave your infrastructure.

Get StartedGitHub
Python
$ pip install cloakllm
JavaScript
$ npm install cloakllm
CloakLLM Demo
CloakLLM 30-second demo showing PII detection and tokenization

Your LLM prompts are plaintext confessions.

Every API call to an LLM sends raw customer data — names, emails, SSNs — to third-party servers. Under the EU AI Act, that's a compliance liability.

The Risk

PII in prompts means your users' personal data is processed by third-party LLM providers — often without consent or safeguards.

The Deadline

August 2, 2026 — EU AI Act Article 12 transparency requirements take effect for high-risk AI systems.

The Penalty

Non-compliance fines up to 7% of global revenue or 35 million, whichever is higher.

3-Pass Detection Pipeline

Multiple layers of detection ensure no PII slips through. Each pass catches what the previous one missed.

Pass 1

Regex

High-precision pattern matching for structured data.

EMAILSSNCREDIT_CARDPHONEIP_ADDRESSAPI_KEYJWTIBAN
Pass 2

spaCy NER

Named entity recognition for names, orgs, and locations. (Python only)

PERSONORGGPE
Pass 3

Ollama LLM

Local LLM-based semantic detection for contextual PII. (opt-in)

ADDRESSDOBMEDICALFINANCIALBIOMETRIC
Before — Plaintext prompt
Help me write a follow-up email
to Sarah Johnson (sarah.j@techcorp.io)
about the Q3 security audit.
Her direct line is +1-555-0142.
After — Cloaked prompt
Help me write a follow-up email
to [PERSON_0] ([EMAIL_0])
about the Q3 security audit.
Her direct line is [PHONE_0].

Everything you need to protect PII

Drop-in middleware that works with your existing LLM stack. No vendor lock-in, no cloud dependencies.

9 Detection Categories

Emails, SSNs, credit cards, phone numbers, API keys, IBANs, JWTs, AWS keys, and IP addresses — all detected out of the box.

Reversible Tokenization

Deterministic [CATEGORY_N] tokens preserve context for the LLM. Desanitize to restore originals in responses.

Tamper-Evident Audit Logs

Hash-chained JSONL entries with SHA-256. No PII stored — just hashes and counts. EU AI Act Article 12 ready.

One-Line Integration

cloakllm.enable() wraps LiteLLM (Python) or the OpenAI SDK (JS). Works with Vercel AI SDK middleware too.

Zero Runtime Deps (JS)

The JavaScript SDK has zero runtime dependencies. Just npm install and go. Python uses only spaCy.

Local LLM Detection

Opt-in Ollama integration catches addresses, medical terms, DOBs, and more. Data never leaves your machine.

One line to protect your LLM calls

Drop-in middleware for every major LLM framework. No code rewrites needed.

Python
import cloakllm

cloakllm.enable()  # Wraps LiteLLM — all calls are now protected

import litellm

response = litellm.completion(
    model="anthropic/claude-sonnet-4-20250514",
    messages=[{
        "role": "user",
        "content": "Help me email Sarah Johnson (sarah.j@techcorp.io)"
    }],
)

# PII automatically restored in the response
print(response.choices[0].message.content)

Get started in seconds

Install the SDK for your language and start protecting PII immediately.

Python

$ pip install cloakllm
$ python -m spacy download en_core_web_sm

JavaScript / TypeScript

$ npm install cloakllm

MCP Server

$ pip install cloakllm-mcp

SDK Comparison

Three SDKs, same core protection. Pick the one that fits your stack.

FeaturePythonJavaScriptMCP
Regex PII Detection
spaCy NER (PERSON, ORG, GPE)
Ollama LLM Detection (opt-in)
Reversible Tokenization
Hash-Chained Audit Logs
CLI (scan / verify / stats)
Multi-Turn Token Maps
Custom Patterns
Middleware IntegrationLiteLLMOpenAI / VercelClaude Desktop
Zero Runtime Dependencies