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FastAPI middleware for emitting PHI-safe audit events for behavioral healthcare systems

Project description

bh-fastapi-audit

A FastAPI middleware for emitting PHI-safe audit events for behavioral healthcare systems, designed for teams building modern healthcare APIs.

This project emits audit events conforming to the bh-audit-schema standard (currently v1.0):
https://github.com/bh-healthcare/bh-audit-schema

Why

Behavioral health systems handle highly sensitive regulated data. Audit logging is often implemented inconsistently across services, making access review and incident investigation unnecessarily difficult.

The goal of this library is to make consistent, structured audit trails easy to adopt in FastAPI services without logging raw PHI.

Status

This project is an implementation layer that turns the bh-audit-schema standard into working FastAPI middleware.

Current version: v0.2.1 — Now available on PyPI with cloud-ready logging.

v0.2 (current)

  • PyPI distributionpip install bh-fastapi-audit
  • LoggingSink — stdout/logging-based sink for cloud deployments
  • FastAPI middleware emitting events conforming to bh-audit-schema v1.0
  • PHI-safe defaults (no bodies, safe headers only, error sanitization)
  • Captures: service, actor, action, resource, outcome, correlation
  • Pluggable sinks:
    • MemorySink — in-memory for testing
    • JsonlFileSink — JSON Lines file for local dev and demos
    • LoggingSink — Python logging for cloud platforms (CloudWatch, Cloud Logging, Azure Monitor, Kubernetes)
    • SQLAlchemySink — relational database storage (Postgres, SQLite, etc., via SQLAlchemy Core)
  • Redaction utilities for error message sanitization

Planned

  • Schema validation for emitted events
  • Non-blocking / async sink variants (optional)

The bh-audit-schema v1.0 JSON schema is vendored into this package to enable offline validation.

Quickstart

from fastapi import FastAPI
from bh_fastapi_audit import AuditMiddleware, AuditConfig, MemorySink

app = FastAPI()

# For testing/development - use MemorySink
sink = MemorySink()
config = AuditConfig(
    service_name="example-bh-api",
    service_environment="dev",
)

app.add_middleware(AuditMiddleware, sink=sink, config=config)

@app.get("/patients/{patient_id}")
def get_patient(patient_id: str):
    return {"patient_id": patient_id}

Each request emits an audit event like:

{
  "schema_version": "1.0",
  "event_id": "c1d2e3f4-1111-2222-3333-444455556666",
  "timestamp": "2026-01-14T22:00:00Z",
  "service": { "name": "example-bh-api", "environment": "dev" },
  "actor": { "subject_id": "unknown", "subject_type": "service" },
  "action": { "type": "READ", "data_classification": "UNKNOWN" },
  "resource": { "type": "get_patient" },
  "http": { "method": "GET", "route_template": "/patients/{patient_id}", "status_code": 200 },
  "outcome": { "status": "SUCCESS" }
}

Production Example: Container Logging (CloudWatch / GCP / K8s)

from fastapi import FastAPI
from bh_fastapi_audit import AuditMiddleware, AuditConfig, LoggingSink

app = FastAPI()

app.add_middleware(
    AuditMiddleware,
    sink=LoggingSink(logger_name="audit"),
    config=AuditConfig(service_name="my-api", service_environment="prod"),
)

When deployed in containers, audit events are emitted as structured JSON logs to stdout and collected by your platform logging system (CloudWatch, Cloud Logging, Azure Monitor, Fluentd, etc.). No SDK dependencies required.

Sinks

Sinks determine where audit events are stored. Choose based on your deployment:

MemorySink (testing)

from bh_fastapi_audit import MemorySink

sink = MemorySink()
# After requests: sink.events contains all emitted events

JsonlFileSink (local dev, demos)

Writes one JSON object per line. Thread-safe, flushes by default.

from bh_fastapi_audit import JsonlFileSink

sink = JsonlFileSink("/var/log/audit/events.jsonl")
# Events appended as compact JSON lines

LoggingSink (cloud deployments)

Emits one compact JSON audit event per request using Python logging. Works with any platform that captures application stdout, including AWS CloudWatch, GCP Cloud Logging, Azure Monitor, and Kubernetes-based logging pipelines.

from bh_fastapi_audit import LoggingSink

sink = LoggingSink(logger_name="bh.audit", level="INFO")
# Each event emitted as a single JSON line via logging

No SDK dependencies, no retries, no buffering. The cloud platform handles collection.

SQLAlchemySink (production database)

Stores events in a relational database with query-friendly columns plus full JSON.

from bh_fastapi_audit import SQLAlchemySink

# PostgreSQL
sink = SQLAlchemySink("postgresql://user:pass@localhost/mydb")

# SQLite (for local testing)
sink = SQLAlchemySink("sqlite:///audit.db")

The sink creates a bh_audit_events table with indexed columns for common compliance queries:

  • timestamp, patient_id, actor_subject_id, action_type, outcome_status
  • Full event stored in event_json column

See docs/indexing.md for recommended database indexes and query examples.

Configuration

AuditConfig supports:

Option Default Description
service_name (required) Name of the service emitting events
service_environment "unknown" Environment (prod, staging, dev)
service_version None Service version string
default_actor_id "unknown" Default actor when no auth context
default_actor_type "service" Default actor type ("human" or "service")
get_actor None Callback (Request) -> dict for custom actor extraction
get_resource None Callback (Request, Response) -> dict for custom resource extraction
get_metadata None Callback (Request, Response) -> dict for custom metadata
metadata_allowlist set() Set of allowed metadata keys (empty = no metadata)
excluded_paths {"/health", "/healthz", "/ready"} Paths to skip auditing

PHI-safe defaults

This library is designed to be safe by default:

  • No bodies: Never reads or logs request/response bodies
  • Route templates: Uses /patients/{id} not /patients/12345
  • Safe headers only: Only extracts correlation headers (no Authorization, Cookie)
  • Error sanitization: Exception messages are stripped of SSN/email/phone patterns and truncated

PHI safety is enforced by tests that assert synthetic PHI tokens never appear in emitted events.

Error message sanitization

When exceptions occur, error messages are automatically sanitized:

from bh_fastapi_audit import sanitize_error_message

# Patterns like SSNs, emails, phone numbers are redacted
sanitize_error_message("Patient SSN 123-45-6789 invalid")
# → "Patient SSN [REDACTED-SSN] invalid"

# Long messages are truncated (default 200 chars)
sanitize_error_message("x" * 500)
# → "xxxx...xxx..."

Metadata allowlist

Metadata is opt-in and strictly filtered:

config = AuditConfig(
    service_name="my-api",
    get_metadata=lambda req, res: {
        "content_length": req.headers.get("content-length"),
        "status_family": f"{res.status_code // 100}xx",
        "notes": "sensitive",
    },
    metadata_allowlist={"content_length", "status_family"},  # Only these keys appear
)

Performance

Audit emission is synchronous in v0.2.x. For high-throughput systems, use LoggingSink or a non-blocking sink (planned for v0.3).

Scope and non-goals

In scope:

  • Structured audit events designed for compliance and operational monitoring
  • Correlation support (request_id / trace_id) to connect events across services

Out of scope:

  • Legal compliance guarantees
  • Storing raw PHI or clinical content in logs
  • Opinionated IAM or authentication frameworks

Installation

Requires Python 3.11+

pip install bh-fastapi-audit

Optional dependencies

# For SQLAlchemy sink (production database storage)
pip install bh-fastapi-audit[sqlalchemy]

Development installation

git clone https://github.com/bh-healthcare/bh-fastapi-audit
cd bh-fastapi-audit
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,sqlalchemy]"

License

Apache 2.0

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