ZTDS (Zero-Trust Data Sanitization)

Canonical Python Reference Implementation of the Zero-Trust Data Sanitization (ZTDS) Protocol (IETF draft-sibiryakov-ztds-protocol-02, RFC v1.0).

ZTDS physically prevents PII, PHI, API tokens, and corporate secrets from crossing WAN sockets unmasked. It operates 100% in local process RAM with zero external network egress, sub-millisecond execution (<0.05ms), and verifiable memory zeroization.

🏛️ Invariants Enforced (RFC v1.0)

1. Invariant 1: Zero External Egress Prior to Sanitization Every byte of prompt data is inspected and sanitized locally in volatile memory. Zero unmasked data touches network interfaces.
2. Invariant 2: Deterministic Reversible Bijective Tokenization Syntactic bracketed surrogates ([NAME_1], [EMAIL_1], [API_SECRET_1]) preserve entity coreference and LLM reasoning semantics while enabling exact bijective restoration ($f^{-1}(f(x)) = x$).
3. Invariant 3: Ephemeral In-RAM Session Isolation & Zeroization (Theorem 2) Cryptographic mapping tables reside strictly in volatile RAM, isolated per session, and are destructively overwritten upon session completion.
4. Invariant 4: Zero Subprocessors & Zero Telemetry No SaaS calls, no cloud APIs, and no telemetry side-channels. Eliminates GDPR Article 28 data processing agreements and vendor risk reviews.

⚡ Quickstart

Install the zero-dependency Python package:

pip install ztds

1. In-Memory Sanitization & Restoration

import ztds

prompt = "Deploy microservice with key sk-ant-api03-0123456789abcdef0123456789abcdef and email dev@corp.internal"

# Use context manager for automatic Invariant 3 RAM zeroization
with ztds.session() as s:
    # Phase 1: Local In-Memory Sanitization (<0.05ms)
    sanitized, minted_tokens = s.sanitize(prompt)
    print(sanitized)
    # Output: "Deploy microservice with key [API_SECRET_1] and email [EMAIL_1]"

    # Phase 2: Send sanitized string safely to any frontier model
    # ai_raw_response = client.chat.completions.create(messages=[{"role": "user", "content": sanitized}])
    ai_raw_response = "Confirmed. Credentials for [EMAIL_1] are stored."

    # Phase 3: Bijective Restoration in Local RAM
    clean_response = s.reveal(ai_raw_response)
    print(clean_response)
    # Output: "Confirmed. Credentials for dev@corp.internal are stored."

# Memory mapping is completely wiped upon context exit (Theorem 2)

🔌 Framework Integrations

LiteLLM Proxy / SDK

Install with LiteLLM extras:

pip install "ztds[litellm]"

import litellm
from ztds.integrations import ZTDSGuardrail

# Intercept all calls locally before WAN socket dispatch
litellm.input_callbacks = [ZTDSGuardrail()]
litellm.output_callbacks = [ZTDSGuardrail()]

response = litellm.completion(
    model="gpt-4o",
    messages=[{"role": "user", "content": "My AWS key is AKIAIOSFODNN7EXAMPLE"}]
)
# Upstream OpenAI receives only "[API_SECRET_1]"
# Your application receives restored output automatically

LangChain

from langchain_openai import ChatOpenAI
from ztds.integrations import ZTDSSanitizingCallbackHandler

llm = ChatOpenAI(
    callbacks=[ZTDSSanitizingCallbackHandler()]
)

CrewAI Multi-Agent Workflows

from crewai import Agent
from ztds.integrations import ZTDSSanitizerTool

security_agent = Agent(
    role="Data Officer",
    goal="Sanitize customer logs before delegation",
    tools=[ZTDSSanitizerTool()]
)

LlamaIndex RAG Node Postprocessor

from llama_index.core import VectorStoreIndex
from ztds.integrations import ZTDSNodePostprocessor

query_engine = index.as_query_engine(
    node_postprocessors=[ZTDSNodePostprocessor()]
)

🛠️ CLI Tools

# Verify compliance with RFC v1.0 canonical test vectors
ztds conformance

# Output JSON for CI/CD pipelines
ztds conformance --json

# Audit local codebase for unmasked secrets and telemetry side-channels
ztds audit --dir ./src --strict

# Quick in-memory sanitization from command line
ztds sanitize "Contact alice@example.com with key sk-proj-12345678901234567890"

📊 Conformance & Performance

All 8 canonical RFC v1.0 test vectors pass with 100% Invariant fidelity:

Average latency per prompt: ~0.031 ms (31 microseconds).

📜 Intellectual Property & Standards

• IETF Specification: draft-sibiryakov-ztds-protocol-02
• Consortium & RFC Registry: https://ztds.ai
• IPR Disclosure: Filed under IETF RFC 8179 rules (Royalty-Free grant for Open-Source implementations with Defensive Termination).
• Commercial Certified Reference Implementation: PrivacyScrubber (30 specialized industry profiles, HIPAA/FRE 502/SOC 2 compliance packs, enterprise air-gapped on-premise engines).

📄 License

MIT License. Copyright (c) 2026 Ilya Sibiryakov & ZTDS AI Consortium.