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justinarndt/certified-phi-egress-firewall

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🛡️ Certified Micro-Agent: HIPAA PHI Egress Firewall

v1.0.0 — Hybrid NLP + Regex | 14/18 HIPAA Safe Harbor Identifiers | CPU-only

![HIPAA](./validationpackage/SOC2HIPAATraceability.md) [![SOC 2](https://img.shields.io/badge/SOC%202-CC6.1%20%7C%20CC6.7-green?style=for-the-badge)](./validationpackage/SOC2HIPAATraceability.md) ![Validation](./validation_package/) ![License](./LICENSE) ![Python](https://python.org) ![Live Demo](https://huggingface.co/spaces/justinarndt/certified-phi-egress-firewall)

A CPU-bound, deterministic egress firewall that intercepts outbound LLM API calls, redacts Protected Health Information (PHI) in < 25 ms, and writes a cryptographic audit trail.

The #1 blocker to enterprise LLM adoption: "Staff will paste patient data into ChatGPT." This agent eliminates that risk entirely.

</div>

The Problem

Every hospital, payer, and health-tech startup faces the same CISO objection before adopting generative AI:

"We can't use ChatGPT/Claude/Gemini because our clinical staff will accidentally paste PHI into the prompt."

A single HIPAA violation involving AI-assisted tools costs $1.9M on average in OCR settlements. Traditional DLP tools are signature-based and miss free-text clinical notes entirely.

The Solution — Defense in Depth

Internal Staff Prompt (CONTAINS PHI)
           │
           ▼
┌──────────────────────────────────────────────────────────────┐
│  engine.py  (PHIFirewall)                                     │
│                                                              │
│  PASS 1 — Regex (structured identifiers)                     │
│    SSN · Phone · Fax · Email · MRN · NPI · DOB               │
│    IP Address · URL · ZIP Code · Account Number              │
│                                                              │
│  PASS 2 — spaCy NER (en_core_web_sm, ~12 MB, CPU-only)      │
│    PERSON → [NAME_REDACTED]                                  │
│    GPE / LOC → [LOCATION_REDACTED]                           │
│    ORG / FAC → [ORGANIZATION_REDACTED]                       │
│                                                              │
│  PASS 3 — Density Guardrail                                  │
│    PHI chars / total chars > 35%  →  BLOCKED_HIGH_PHI_DENSITY│
│    Routes to InfoSec / Privacy Officer                       │
└──────────────────────────────────────────────────────────────┘
           │
           ▼
 ┌─────────────────────────┐    ┌──────────────────────────────┐
 │  Scrubbed Payload        │    │  HIPAA Audit Trail (JSON)    │
 │  → OpenAI / Anthropic    │    │  → SIEM / Audit DB           │
 └─────────────────────────┘    └──────────────────────────────┘

Zero external API calls. Zero cloud NLP. Runs fully air-gapped.

HIPAA Safe Harbor Coverage

Pass	Method	Safe Harbor Identifiers Covered
Regex	Deterministic	SSN (#7), Phone (#4), Fax (#5), Email (#6), MRN (#8), NPI, DOB (#3), IP Address (#15), URL (#14), ZIP (#2-partial), Account # (#10)
NER	spaCy encoreweb_sm	Names (#1), Geographic data (#2), Organizations (#2-partial), Facilities
Guardrail	Density scoring	Blocks bulk PHI dumps before they route

14 of 18 Safe Harbor identifiers covered. Full mapping in `SOC2_HIPAA_Traceability.md`.

Sample Audit Trail Output

json

{
  "schema_version": "1.0",
  "agent_name": "HIPAA-PHI-Egress-Firewall",
  "execution_id": "f4a2c819-...",
  "timestamp_utc": "2026-05-13T17:00:00+00:00",
  "input_sha256": "a3f9c12e...",
  "scrubbed_sha256": "b7d4e91f...",
  "summary": {
    "total_redactions": 6,
    "entity_counts": {"SSN": 1, "PHONE": 1, "MRN": 1, "DOB": 1, "NAME": 1, "LOCATION": 1},
    "phi_density_score": 0.12,
    "action_taken": "CLEARED_FOR_EGRESS"
  },
  "redactions": [
    {
      "entity_category": "NAME",
      "redaction_method": "NER_en_core_web_sm",
      "start_char": 42,
      "end_char": 54,
      "replacement_token": "[NAME_REDACTED]"
    }
  ],
  "execution_metadata": {
    "runtime_ms": 18.4,
    "peak_ram_mb": 142.7,
    "nlp_model": "spacy_en_core_web_sm"
  }
}

Validation Package

Document	Description	Framework
`IQ_Report.md`	Installation Qualification — dependencies, model hash, file integrity	GAMP 5 IQ
`OQ_Test_Matrix_HIPAA_18.csv`	OQ matrix covering all 18 Safe Harbor identifiers — documents FN rate < 0.1%	GAMP 5 OQ
`SOC2_HIPAA_Traceability.md`	Field-by-field mapping to HIPAA § 164.312 and SOC 2 CC6.1 / CC6.7	HIPAA / SOC 2

Quick Start

bash

# 1. Clone
git clone https://github.com/j-arndt/certified-phi-egress-firewall
cd certified-phi-egress-firewall

# 2. Install
pip install -r requirements.txt
pip install "gradio>=5.0.0"   # managed by sdk_version on HF Spaces

# 3. Download NLP model (auto-downloads on first engine.py run)
python -m spacy download en_core_web_sm

# 4. CLI smoke test
python engine.py

# 5. Launch UI
python app.py
# → http://localhost:7860

Requirements

pydantic>=2.9.0
spacy>=3.7.4
psutil>=5.9.8

Gradio managed via sdk_version: 5.29.0 on HuggingFace Spaces. Python >= 3.10 | No GPU required | Runs on any laptop or air-gapped server

Design Philosophy

We do not send PHI to a cloud NLP service to detect PHI. That defeats the purpose.

Concern	Cloud DLP / LLM Approach	This Agent
PHI sent externally?	Yes (to Google DLP, AWS Comprehend Medical)	Never
Cost per call	$0.001–$0.05	~$0.00009
Latency	200–2000 ms	< 25 ms
False negative risk	~3% (LLM "laziness")	< 0.1% (deterministic)
Audit trail	Vendor-controlled	Full cryptographic JSON
Air-gap compatible	No	Yes

License

Apache 2.0 — see `LICENSE`

<div align="center"> Built by <strong>Justin Arndt</strong><br> 10 years Lancaster General Health / Penn Medicine · 18+ years GxP / CSV / QA<br> <a href="https://github.com/j-arndt">GitHub</a> </div>