ZTDS.ai Open AI Security Standard
Executive Legal Memorandum · Document ID: ZTDS-CISO-2026-V1

CISO Procurement & DPA Exemption Pack

Statutory legal justification, regulatory doctrine, and security questionnaire answers demonstrating why ZTDS-compliant architectures are legally exempt from Data Processing Agreements (DPA) under GDPR Article 28.

Official Consortium Memorandum
ZTDS.ai AI Security Consortium
Canonical Standard RFC v1.0 · BrandMeWeb Ecosystem
DOC ID: ZTDS-CISO-2026-V1
RATIFIED: September 2026
STATUS: LEGALLY SOUND & AUDIT-READY
DOI: 10.5281/zenodo.22058770
To: Chief Information Security Officer (CISO), Data Protection Officer (DPO), Enterprise Procurement & Risk Committees
From: Ilya Sibiryakov, Specification Author & Chief Architect (ZTDS.ai / BrandMeWeb)
Subject: Architectural & Statutory Legal Grounds for Exemption from Third-Party Data Processing Agreements (DPA) and Subprocessor Chains

1. Executive Summary & Core Architectural Principle

100% Client-Side Utility

Software conforming to the Zero-Trust Data Sanitization (ZTDS RFC v1.0) specification operates strictly as a pure client-side computational utility. Because conforming software executes de-identification strictly within volatile client RAM before outbound network socket serialization, exactly zero (0.00) bytes of cleartext sensitive data are transmitted to or processed by external vendor servers.

Under established international data protection jurisprudence, software that processes data locally on client hardware without transmitting data to the software vendor is architecturally positioned outside the "data processor" definition when all 4 ZTDS invariants are satisfied. Consequently, ZTDS-conforming architectures provide an architectural basis for DPA/BAA scope exclusion analysis under GDPR Article 28, HIPAA BAA frameworks, and third-party subprocessor risk liability.

The 4 Non-Negotiable Mathematical Invariants (RFC v1.0) Full RFC Spec →
Invariant 1: Zero External Egress
ΔEgress(S) ≡ 0.00 bytes across public sockets S_WAN.
Invariant 2: Deterministic Reversible Tokens
Bijective in-memory transformation P_final = T^-1(P_out, R).
Invariant 3: Verifiable Memory Isolation
Zero persistent disk/storage writes. RAM purges on termination.
Invariant 4: Subprocessor Exclusion
GDPR Article 28 disengaged; subprocessor liability chain = 0.

2. Statutory Grounds for Exemption & Regulatory Safe Harbors

EU GDPR Article 28 & EDPB 07/2020 NO DPA REQUIRED

Article 28 applies only when an external entity processes personal data on behalf of a controller. Under European Data Protection Board (EDPB) Guidelines 07/2020, providers of pure client-side software utilities that never access or receive personal data do NOT qualify as processors. Zero data custody = zero DPA required.

Statutory Defense: Complete absence of Article 4(8) processor relationship.
EU GDPR Art. 28 & Recital 26 (Vendor Exemption) DPA EXEMPT

Software conforming to ZTDS executes strictly inside volatile client RAM without cloud egress to vendor servers. Under CJEU Case C-582/14 (Breyer) and EDPB Guidelines 07/2020, the software vendor never obtains custody or means of identification, and is legally excluded from Data Processor status under GDPR Article 28.

Statutory Defense: Complete exclusion of software vendor from GDPR Art. 28 processor obligations.
GDPR Article 17 (Vector Store Protection) NO RAG POISONING

When raw PII is ingested into high-dimensional vector databases, data cannot be erased without total re-indexing ($100k+ cost). ZTDS ensures only surrogate tokens enter RAG embeddings, preventing irreversible vector poisoning and guaranteeing automated Right to Erasure compliance.

Statutory Defense: Zero immutable PII embeddings in knowledge stores.
US HIPAA Safe Harbor (45 CFR § 164.514) NO BAA NEEDED

By deterministically excluding all 18 PHI identifiers locally in volatile RAM before network egress, outbound prompts qualify as de-identified health information under 45 CFR § 164.514(b). The downstream AI model provider never receives PHI, eliminating mandatory BAA requirements.

Statutory Defense: De-identified clinical data excluded from HIPAA scope.

3. Statutory Regulatory Penalty Ceilings & Risk Mitigation

Model Custom Exposure in CISO Calculator →
Jurisdiction & Regulatory Statute Statutory Maximum Penalty Ceiling ZTDS Invariant Safe Harbor Defense
EU GDPR Article 83(5)
Cross-Border Data Transfer / Processor Breach
Up to €20,000,000 or 4% of Global Annual Turnover Raw PII never traverses network boundary (ΔEgress = 0.00 B). No cross-border personal data transfer occurs under Chapter V.
EU Artificial Intelligence Act (Article 99)
High-Risk AI Data Governance & Transparency
Up to €15,000,000 or 3% of Global Annual Turnover Surrogate tokens satisfy transparency and training data governance requirements without exposing proprietary records to LLM retainment.
US HIPAA HITECH (45 CFR Part 160)
Tier 4 Uncorrected Willful Neglect
$2,067,813 Statutory Annual Cap per Violation Category Strict Safe Harbor 18-element de-identification executed before egress; outbound prompts contain zero PHI, nullifying breach notification triggers.
US Federal Rule of Evidence 502(b)
Attorney-Client Privilege & Work Product
Subject-Matter Privilege Waiver in Commercial Litigation Deterministic reversible masking ensures unprivileged third parties (LLM vendors) never receive unmasked work product, preventing inadvertent waiver.
US GLBA & SEC Item 106
Financial Customer NPI & Cyber Disclosures
Regulatory Enforcement & $7,500/record Statutory Damages Financial institution NPI and cardholder data isolated to volatile workstation RAM; zero egress to AI inference infrastructure.

4. Subprocessor Chain Overhead Elimination ($25,000 / Vendor / Year)

By disengaging GDPR Article 28, enterprises eliminate recurring third-party vendor review costs:

NET SAVINGS: $25,000 / VENDOR
Component 1
Legal DPA Review & SCCs
$8,000 / yr

Eliminates outside legal counsel hours negotiating custom Data Processing Agreements, Standard Contractual Clauses, and liability indemnities.

Component 2
TPRM & SIG Lite Audits
$9,000 / yr

Eliminates annual Third-Party Risk Management questionnaires, cloud vendor penetration test reviews, and recurring SIG Lite evaluations.

Component 3
SOC 2 Subprocessor Chain
$8,000 / yr

Removes external cloud proxies from the enterprise SOC 2 Type II subprocessor audit inventory (CC6.7), reducing external auditor billable scope.

5. Architectural Liability Comparison

Evaluation Dimension Legacy Cloud DLP / API Proxy ZTDS Client Engine (RFC v1.0)
Execution Perimeter Multi-tenant vendor cloud (AWS/GCP) Local volatile workstation / VPC RAM
Cleartext Socket Egress Mandatory (raw data travels over WAN) ΔEgress = 0.00 bytes prior to masking
Subprocessor Liability Chain Creates new subprocessor under GDPR Art. 28 Zero subprocessors added (utility exemption)
Added Network Latency +350ms to +800ms per LLM prompt <0.8ms local synchronous execution
Token Masking Quality Destructive static [REDACTED] strings Bijective contextual surrogate tokens
Offline Resilience Fails completely if vendor cloud is down 100% operational in Airplane Mode / air-gapped

6. Enterprise Security Questionnaire Responses (SIG Lite / CAIQ v4 / VSAQ)

Control DSP-01 (Data Storage) CAIQ v4

Q: Where is customer prompt data hosted or stored?
A: Nowhere. Cleartext data and token maps reside strictly in volatile RAM. No data is ever written to disk, databases, cookies, or cloud storage.

Control NET-02 (External Egress) SIG Lite

Q: What data egresses to vendor servers during sanitization?
A: Exactly 0.00 bytes. The sanitization engine is self-contained in WebAssembly/TypeScript. No telemetry, analytics, or socket communication exists.

Control CRY-03 (Key Custody) ISO 27001 A.8.11

Q: Does the vendor have custody or access to customer encryption keys?
A: No. Masking tables and session keys are derived strictly in client RAM. The vendor maintains zero key escrow and zero remote access.

Control CRY-04 (Team Handoff) RFC 9106

Q: How does collaborative unmasking work across enterprise teams?
A: Token maps are encrypted client-side using Argon2id and XChaCha20-Poly1305. Central relays act as blind zero-knowledge conduits.

Control TPR-05 (Subprocessors) GDPR Art. 28

Q: What third-party subprocessors have access to customer data?
A: Zero. Zero subprocessors are involved in data processing, providing an architectural basis for DPA/BAA scope exclusion analysis.

Control AUD-06 (Independent Audit) SOC 2 CC6.7

Q: How can our security team verify zero egress independently?
A: Run the 5-Step Airplane Mode protocol in DevTools or execute npx ztds-audit --dir ./src to generate a verifiable cryptographic audit hash.

Enterprise Procurement Model

7. On-Premise Air-Gapped Source Code License Agreement

LICENSOR: Ilya Sibiryakov (BrandMeWeb)
1. Perpetual Internal Execution Right

Customer receives a non-exclusive, non-transferable license to compile, inspect, and execute the ZTDS engine source code strictly within internal, air-gapped networks, microservices, and private cloud VPCs.

2. Permitted Internal Use Cases

Customer may embed the engine into backend microservices, RAG embedding pipelines, internal agentic loops (LangChain, CrewAI), and employee workstations.

3. 100% Disconnected SCIF Deployment

Customer is authorized to deploy the engine in 100% disconnected, SCIF, or classified environments with zero telemetry, phone-home checks, or licensing heartbeats required.

4. Offline Cryptographic Verification

License validation operates via offline Ed25519 cryptographic tokens with built-in 60-day operational grace periods and sub-millisecond in-memory verification.

Ratified on behalf of ZTDS AI Consortium:
Ilya Sibiryakov
Specification Author · Chief Architect · BrandMeWeb · ORCID: 0009-0002-0642-5985
Technical Evaluation & Method Comparison

Architectural Comparison: The ZTDS Method vs. Legacy Cloud DLP

Objective architectural evaluation, perimeter boundaries, and latency benchmarks comparing the client-side ZTDS Method against Microsoft Purview, Nightfall AI, BigID, and Cloud API proxies.

Nominative Fair Use & Technical Source Citations

Microsoft Purview, Nightfall AI, BigID, AWS Macie, and Google Cloud Sensitive Data Protection (DLP) are registered trademarks of their respective proprietors. Comparative analyses are strictly architectural, evaluating local in-memory execution boundaries against cloud network proxy topologies based on publicly available vendor documentation as of Q3 2026:

  • Microsoft Purview: Endpoint & Exchange Information Protection Architecture (docs.microsoft.com/purview)
  • Google Cloud DLP: Sensitive Data Protection API latency characteristics and volumetric inspection pricing (cloud.google.com/dlp)
  • AWS Macie: S3 Data Security & Automated Discovery topology (aws.amazon.com/macie)
  • Nightfall AI: Cloud API proxy webhook & SaaS integration patterns (docs.nightfall.ai)
Target Competitor

Microsoft Purview (Information Protection & Data Loss Prevention)

FLAW: Gateway File Boundary Only

The Architectural Vulnerability

Purview was architected for document classification (Office 365, SharePoint, Exchange) and network gateway egress blocking. It relies on static file inspection or coarse network packet inspection. In dynamic AI applications, data moves as volatile JSON string buffers in streaming API calls. Purview cannot inspect, tokenize, and synchronously de-tokenize dynamic payload streams in real time (<1.2ms) without breaking application performance and model reasoning.

CISO Objection Handling Playbook

CISO Says "We already have Microsoft E5 / Purview deployed across our entire enterprise."
Your Response: "Purview enforces boundary policies on files, emails, and endpoints. But in your generative AI applications, your users interact via prompt interfaces, agent tools, and API calls. Purview cannot execute inside the browser or backend Node/Python process in under 1.2 milliseconds, substitute raw PII with synthetic tokens, and restore the tokens when OpenAI or Anthropic responds. Purview is a network gatekeeper; ZTDS is an in-memory data-plane transformer. You need Purview for OneDrive, but you need ZTDS for LLM pipelines."
CISO Says "Can't we just configure Purview to block prompts that contain sensitive data?"
Your Response: "Blocking prompts breaks enterprise AI adoption. If a customer support representative cannot summarize a complaint because it contains an account number, the entire AI tool becomes unusable. ZTDS allows the prompt to execute safely by swapping the account number for [ACCOUNT_TOKEN_1]. The model successfully reasons over the context, and your local client restores the real number in the UI. You achieve 100% compliance without halting business operations."
The One-Sentence CISO Takeaway "Purview stops documents from leaving your network; ZTDS allows your AI applications to safely compute over sensitive data without ever letting raw PII leave the device."
Model ROI →