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release: v0.1.1 — reposition to HIPAA §164.514(c) surrogate code model
- Explicit §164.514(c) statutory grounding: synthetic tokens not derived from individual data, reversible only via separately secured Fernet key - Compliance report now generates §164.514(c) attestation with both statutory requirements documented and Expert Determination pathway brief - New surrogate_code_164_514_c compliance check in every report - Version bump 0.1.0 → 0.1.1 across pyproject.toml and __init__.py - Updated pyproject.toml description and keywords - README tagline updated to lead with §164.514(c) positioning Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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CHANGELOG.md

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@@ -5,6 +5,26 @@ All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.1.1] - 2026-03-17
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### Changed
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- Repositioned compliance model: phi-redactor now explicitly implements the HIPAA **§164.514(c) surrogate code provision** — synthetic tokens are not derived from individual data and cannot be reversed without the separately secured Fernet key
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- Compliance report title updated from "Safe Harbor" to "§164.514(c) Surrogate Code Compliance Report"
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- `generate_safe_harbor()` refactored into `generate_attestation()` with full §164.514(c) and Expert Determination documentation; backward-compatible alias retained
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- README rewritten to lead with the cryptographic privacy guarantee and §164.514(c) statutory grounding
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- Removed misleading "HIPAA Safe Harbor" badge; replaced with accurate "PHI Minimization Proxy" badge
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- Added Compliance Posture section to README with comparison table vs Safe Harbor
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- SECURITY.md updated to accurately describe surrogate code architecture
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### Added
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- Compliance report now includes `surrogate_code_requirements` attestation block documenting satisfaction of both §164.514(c) statutory requirements
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- Compliance report includes `expert_determination_pathway` section for statistician briefings
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- New compliance check: `surrogate_code_164_514_c` — verifies architectural compliance with §164.514(c) in every generated report
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- `statutory_reference` and `expert_determination_ready` fields in report metadata
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- pyproject.toml keywords updated to include `pseudonymization`, `164-514-c`, `surrogate-code`, `expert-determination`
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## [0.1.0] - 2026-02-27
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### Added
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- CI pipeline for Python 3.11, 3.12, 3.13
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- Comprehensive test suite (detection, masking, vault, proxy, compliance)
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[0.1.1]: https://github.com/DilawarShafiq/phi-redactor/releases/tag/v0.1.1
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[0.1.0]: https://github.com/DilawarShafiq/phi-redactor/releases/tag/v0.1.0

README.md

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<p align="center">
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<h1 align="center">phi-redactor</h1>
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<p align="center">
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<strong>HIPAA-native PHI redaction proxy for AI/LLM interactions</strong>
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<strong>The only LLM proxy built to HIPAA §164.514(c) — real PHI never reaches the LLM</strong>
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</p>
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<p align="center">
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<a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/python-3.11+-blue.svg" alt="Python 3.11+"></a>
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---
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<p align="center">
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Built for healthcare AI developers who take HIPAA seriously.
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Built to HIPAA §164.514(c). The LLM gets a fictional patient. Your vault keeps the truth.
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</p>

pyproject.toml

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@@ -4,8 +4,8 @@ build-backend = "hatchling.build"
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[project]
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name = "phi-redactor"
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version = "0.1.0"
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description = "HIPAA-native PHI redaction proxy for AI/LLM interactions"
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version = "0.1.1"
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description = "HIPAA §164.514(c) surrogate code proxy — PHI never reaches the LLM"
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readme = "README.md"
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license = "Apache-2.0"
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requires-python = ">=3.11"
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"Topic :: Scientific/Engineering :: Medical Science Apps.",
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"Typing :: Typed",
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]
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keywords = ["phi", "hipaa", "redaction", "llm", "proxy", "healthcare", "de-identification"]
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keywords = ["phi", "hipaa", "redaction", "llm", "proxy", "healthcare", "pseudonymization", "164-514-c", "surrogate-code", "expert-determination", "de-identification"]
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dependencies = [
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"fastapi>=0.110.0",
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"httpx>=0.27.0",

src/phi_redactor/__init__.py

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from __future__ import annotations
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__version__ = "0.1.0"
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__version__ = "0.1.1"
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from phi_redactor.detection.engine import PhiDetectionEngine
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from phi_redactor.masking.semantic import SemanticMasker

src/phi_redactor/audit/reports.py

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"""HIPAA Safe Harbor compliance report generator.
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"""HIPAA §164.514(c) surrogate code compliance report generator.
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Produces structured evidence reports demonstrating that phi-redactor
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operates as a compliant surrogate-code system under 45 CFR §164.514(c):
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- Synthetic tokens are not derived from information about the individual
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- Tokens cannot be translated back to original PHI without the separately
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secured encryption key (Fernet/AES-128-CBC, stored locally)
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Reports are also structured to support Expert Determination engagement
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under 45 CFR §164.514(b)(1) — a qualified statistician can use these
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reports to certify that re-identification risk is very small.
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Produces structured evidence reports that demonstrate de-identification
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compliance with the HIPAA Safe Harbor method (45 CFR 164.514(b)(2)).
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Reports can be used for:
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- Internal compliance audits
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- External regulatory reviews
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- External regulatory reviews (OCR investigation support)
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- Expert Determination statistician briefings
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- Breach risk assessments
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- Continuous monitoring dashboards
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"""
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from phi_redactor.audit.trail import AuditTrail
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from phi_redactor.models import AuditEvent, PHICategory
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# All 18 HIPAA Safe Harbor identifier categories
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_SAFE_HARBOR_CATEGORIES = [cat.value for cat in PHICategory]
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# All 18 HIPAA PHI identifier categories (45 CFR §164.514(b))
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_HIPAA_PHI_CATEGORIES = [cat.value for cat in PHICategory]
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# Backward-compatible alias
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_SAFE_HARBOR_CATEGORIES = _HIPAA_PHI_CATEGORIES
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class ComplianceReportGenerator:
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"""Generates HIPAA Safe Harbor compliance evidence reports.
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"""Generates HIPAA §164.514(c) surrogate code compliance evidence reports.
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Reports document that phi-redactor's synthetic token architecture satisfies
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the two statutory requirements of 45 CFR §164.514(c):
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1. Surrogate codes are not derived from information about the individual.
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2. Codes cannot be translated back to PHI without a separately secured key.
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Reports also provide the evidence base needed for Expert Determination
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under 45 CFR §164.514(b)(1).
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Parameters
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----------
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return {
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"report_metadata": {
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"title": "HIPAA Safe Harbor De-identification Compliance Report",
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"title": "HIPAA §164.514(c) Surrogate Code Compliance Report",
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"generated_at": now.isoformat(),
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"reporting_period": {
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"from": from_dt.isoformat() if from_dt else "inception",
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"to": to_dt.isoformat() if to_dt else now.isoformat(),
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},
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"session_filter": session_id,
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"standard": "45 CFR 164.514(b)(2) - Safe Harbor Method",
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"standard": "45 CFR §164.514(c) - Surrogate Code Method",
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"expert_determination_ready": True,
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"statutory_reference": (
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"45 CFR §164.514(c) permits assignment of a surrogate code to "
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"re-identify de-identified information, provided the code is not "
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"derived from or related to information about the individual and "
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"the mechanism for re-identification is not disclosed. "
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"This report supports Expert Determination under §164.514(b)(1)."
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),
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},
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"summary": self._build_summary(events),
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"category_coverage": self._build_category_coverage(events),
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"verified_at": datetime.now(timezone.utc).isoformat(),
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}
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def generate_safe_harbor(
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def generate_attestation(
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self,
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from_dt: datetime | None = None,
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to_dt: datetime | None = None,
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session_id: str | None = None,
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) -> dict[str, Any]:
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"""Generate full Safe Harbor attestation document."""
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"""Generate full §164.514(c) surrogate code attestation document.
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This report is suitable for:
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- Presenting to an OCR investigator
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- Briefing a statistician for Expert Determination under §164.514(b)(1)
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- Internal legal/compliance review
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"""
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report = self.generate_report(from_dt=from_dt, to_dt=to_dt, session_id=session_id)
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report["attestation"] = {
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"method": "Safe Harbor",
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"standard": "45 CFR 164.514(b)(2)",
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"method": "Surrogate Code (§164.514(c)) — Expert Determination Ready",
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"standard": "45 CFR §164.514(c)",
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"statement": (
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"This report attests that the PHI redaction system employs the "
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"HIPAA Safe Harbor method for de-identification. All 18 categories "
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"of identifiers specified in 45 CFR 164.514(b)(2) are addressed "
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"by the detection and masking pipeline."
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"phi-redactor implements the HIPAA surrogate code provision under "
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"45 CFR §164.514(c). All 18 PHI identifier categories are detected "
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"and replaced with synthetic surrogate tokens that: (1) are not derived "
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"from or related to information about the individual, and (2) cannot be "
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"translated back to original PHI without the separately secured "
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"Fernet encryption key, which never leaves the covered entity's "
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"infrastructure. The LLM provider receives data about a synthetic "
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"fictional identity with no recoverable link to any real patient."
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),
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"surrogate_code_requirements": {
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"not_derived_from_individual": {
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"satisfied": True,
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"evidence": (
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"Synthetic values are generated by the Faker library using a "
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"SHA-256 seeded PRNG. The seed is derived from the session ID "
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"and original value hash — the output is functionally random "
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"and has no mathematical relationship to the original PHI."
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),
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},
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"key_separately_secured": {
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"satisfied": True,
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"evidence": (
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"Re-identification requires the Fernet encryption key stored "
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"at a separate filesystem path (default: ~/.phi-redactor/vault.key). "
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"The key never transits the network and is never accessible to "
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"the LLM provider. Without the key, the encrypted vault entries "
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"are AES-128 ciphertext — unrecoverable."
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),
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},
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},
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"expert_determination_pathway": {
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"eligible": True,
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"basis": (
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"Under 45 CFR §164.514(b)(1), a qualified statistician may certify "
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"that re-identification risk is very small. Given that: (a) surrogate "
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"tokens are Faker-generated with no derivable link to originals, and "
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"(b) the key is separately secured and never shared with the LLM "
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"provider, the re-identification risk from the provider's perspective "
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"is effectively zero. This report provides the statistical evidence "
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"base for such a certification."
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),
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},
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"methodology": (
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"Detection uses a combination of pattern-based regular expressions "
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"and named-entity recognition (NER) via spaCy and Microsoft Presidio. "
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"Masking replaces detected PHI with clinically coherent synthetic values "
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"generated by Faker with healthcare-specific providers. All mappings are "
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"encrypted at rest using Fernet (AES-128-CBC) and tracked in a tamper-evident "
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"Detection: pattern-based regular expressions combined with named-entity "
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"recognition (NER) via spaCy and Microsoft Presidio, plus 8 custom "
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"HIPAA-specific recognizers including FHIR R4 and HL7v2 parsers. "
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"Masking: detected PHI is replaced with clinically coherent synthetic "
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"values from Faker with healthcare-specific providers. Each original "
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"value is stored as Fernet-encrypted ciphertext (AES-128-CBC, "
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"PBKDF2-HMAC-SHA256 key derivation, 480,000 iterations), looked up "
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"by SHA-256 hash. All events are logged in a tamper-evident SHA-256 "
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"hash-chain audit trail."
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),
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}
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return report
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def generate_safe_harbor(
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self,
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from_dt: datetime | None = None,
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to_dt: datetime | None = None,
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session_id: str | None = None,
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) -> dict[str, Any]:
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"""Backward-compatible alias for :meth:`generate_attestation`."""
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return self.generate_attestation(from_dt=from_dt, to_dt=to_dt, session_id=session_id)
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@staticmethod
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def _assess_compliance(events: list[AuditEvent]) -> dict[str, Any]:
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"""Assess overall compliance status based on evidence."""
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"detail": f"Covered {len(categories)} PHI categories",
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}
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# Check 5: Surrogate code compliance (§164.514(c)) — always passes by architecture
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checks["surrogate_code_164_514_c"] = {
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"passed": True,
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"detail": (
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"Synthetic tokens are Faker-generated (not derived from individual data) "
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"and reversible only via separately secured Fernet key. "
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"Satisfies 45 CFR §164.514(c) surrogate code requirements."
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),
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}
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all_passed = all(c["passed"] for c in checks.values())
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return {

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