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Zero-egress PII redaction for Claude. Runs locally — no data leaves your infrastructure.
About
Zero-egress PII redaction for Claude. Runs locally — no data leaves your infrastructure.
Security Report
10.0
Low Risk10.0Low RiskValid MCP server (4 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: 4 highly-trusted packages.
11 files analyzed · 1 issue found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
URL of your locally running Ocultar Refinery
Environment variable: OCULTAR_URL
Ocultar API key (leave blank if not configured)
Environment variable: OCULTAR_API_KEY
Enables reveal_tokens tool. Must match OCU_AUDITOR_TOKEN on the server.
Environment variable: OCULTAR_AUDITOR_TOKEN
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-edu963-ocultar-pii": {
"env": {
"OCULTAR_URL": "your-ocultar-url-here",
"OCULTAR_API_KEY": "your-ocultar-api-key-here",
"OCULTAR_AUDITOR_TOKEN": "your-ocultar-auditor-token-here"
},
"args": [
"ocultar-claude-mcp"
],
"command": "uvx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
🛡️ OCULTAR Monorepo
Zero-egress PII refinery for AI pipelines. Runs in your infrastructure. Your data never leaves.
[!IMPORTANT] Featured Article: OpenAI shipped a model. We built the system. 📖 OpenAI shipped a model. We built the system. Read on dev.to
Quick Security Stats
| Stat | Value |
|---|---|
| SSRF bypass vectors found + fixed | 2 |
| Fail-closed scenarios tested | 6 |
| Vault persistence | Named Docker volume |
| Tier 2 engine | OpenAI Privacy Filter (Apache 2.0) |
| Key management | Doppler |
Welcome to the Unified OCULTAR Engine. This monorepo contains the core refinery, integrated applications, and enterprise security tiers.
Structure
/apps/- Applications (Proxy, Sombra Gateway, SLM Engine, Dashboard, Automation Bridge, Web)/services/- Core backend logic (Refinery, Vault, Mock API)/enterprise/- Enterprise security extensions & licensing logic/internal/pii/- Centralized PII detection engine & registry/extensions/- Third-party AI tool integrations (Goose MCP, etc.)/docs/- Technical and product documentation/security/- Regulatory policies and integrity manifests
Security Model
OCULTAR is built on a Zero-Trust for Data architecture. It is designed for senior security engineers who require verifiable guarantees before connecting internal data to external AI providers.
- Zero-Egress: A hard architectural guarantee. All PII detection and tokenization happen within your trust boundary. No network calls are made to third-party detection providers.
- Fail-Closed: 6 critical failure modes are rigorously tested (SLM timeout, vault failure, empty boot-guard, queue saturation, refinery internal error, re-hydration failure). In all cases, OCULTAR blocks the request rather than degrading to plaintext exposure.
- SSRF Protection: Hardened IP/DNS validation blocking RFC 1918 and
169.254.169.254(IMDS) ranges with active DNS rebinding safety. 2 bypass vectors (including IPv6 loopback and non-standard decimal encoding) were identified and patched during adversarial testing. - Secure Vault: AES-256-GCM encryption with keys derived via HKDF-SHA256. The vault is persisted via a named Docker volume to survive redeployments while keeping the master key in memory.
- Ed25519 Audit Logs: Tamper-proof, hash-chained audit trails signed with Ed25519. Every vault event (matching or vaulting) is logged for SIEM ingestion and compliance verification.
Multi-Tier Refinery Pipeline
Tokenization is handled via a defense-in-depth pipeline that runs before any payload reaches an upstream AI provider.
| Tier | Shield | Technical Description |
|---|---|---|
| 0.1 | Base64 Evasion | Decodes, scans, and re-encodes PII hidden inside Base64/JWT blobs. |
| 0 | Dictionary | High-speed protection for VIPs, internal projects, and sensitive org names. |
| 0.5 | Pattern + Entropy | Shannon scoring for high-entropy strings, catching keys and tokens. |
| 1 | Rule Engine | EMAIL, SSN, IBAN (MOD97), CC (Luhn mod-10), 50+ national ID types. |
| 1.1 | Phone Shield | libphonenumber validation to reduce false positives on digit sequences. |
| 1.2 | Address Shield | Heuristic street address parser supporting EN/FR/ES/DE. |
| 1.5 | Greeting/Signature | Detects names in salutations ("Regards, Jean") and intro sentences. |
| 2 | AI NER | OpenAI Privacy Filter — 1.5B param, local inference. Optimized for French Finance. |
| 3 | Structural Heuristics | Proximity expansion: [TOKEN] ET Dupont → re-tokenized as single entity. |
Why OCULTAR Is Different
Obfuscation-Resistant: Recursive Base64 Scanning
Most PII filters operate on plaintext. A sophisticated attacker can embed sensitive data inside a Base64-encoded blob inside a JSON field, bypassing naive pattern matching. OCULTAR decodes and recursively scans every Base64 segment, running the full pipeline on the decoded content.
Luhn-Validated Credit Card Detection
OCULTAR applies the Luhn algorithm (mod-10 checksum) to every credit card candidate before vaulting it. A match that fails Luhn is passed through without redaction or vault storage, eliminating the noise typical of regex-only filters.
Deterministic Tokens for Privacy-Safe Analytics
Tokens are derived from SHA-256(original_PII). The same input always produces the same token. This allows you to run aggregations, joins, and frequency analysis on fully tokenized data without de-tokenizing it — preserving analytical value while eliminating privacy risk.
Extensions
Goose AI Workflow Integration
Zero-egress PII protection for Goose AI workflows.
pip install ocultar-goose-mcp
Read the launch story: OpenAI shipped a model. We built the system.
Integration Boundary
Ocultar's responsibility ends at POST /refine. It returns cleanText and a vault token map. It has no knowledge of downstream AI decisions. Callers must fail loudly if Ocultar is unavailable — never degrade gracefully by passing raw data.
Getting Started
-
Secrets Management: OCULTAR uses Doppler for secure secret injection.
doppler setup -
Go Workspace:
go work sync -
Build and Run:
make build ./scripts/start.sh
Development
- Documentation: See
/docs/referencefor architecture details. - Testing: Run
go test ./...to verify all modules.
Discovery & Community
- Topics:
privacy,gdpr,pii,golang,ai-security,zero-trust,llm,data-privacy - License: Apache 2.0 (Open-Core)
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