Encryption: Data at Rest & In Transit

Encryption is the foundation of PHI protection. This module covers everything from basic cryptographic concepts to production-ready implementations for healthcare applications. Real-world compliance scenario: In 2017, Advocate Medical Group paid

5.55 million after four unencrypted laptops were stolen from an administrative office, exposing the ePHI of approximately 4 million patients. Had those laptops used full-disk encryption with proper key management, the incident would have qualified for HIPAA's encryption safe harbor and would not have been considered a reportable breach at all. The cost of encrypting those laptops? Under

200 total. The cost of not encrypting them? $5.55 million in fines, plus years of remediation and reputational damage. Encryption is the single highest-ROI compliance investment you can make.

Learning Objectives:

Understand symmetric vs asymmetric encryption
Implement AES-256-GCM for data at rest
Configure TLS 1.3 for data in transit
Design key management systems
Implement field-level and database encryption

Why Encryption Matters for HIPAA

┌─────────────────────────────────────────────────────────────────────────────┐
│                    HIPAA ENCRYPTION REQUIREMENTS                             │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                              │
│  SECURITY RULE §164.312(a)(2)(iv)        SECURITY RULE §164.312(e)(2)(ii)  │
│  ────────────────────────────────        ─────────────────────────────────  │
│  "Implement a mechanism to               "Implement a mechanism to          │
│   encrypt and decrypt ePHI"               encrypt ePHI whenever deemed      │
│                                           appropriate"                       │
│                                                                              │
│  DATA AT REST                            DATA IN TRANSIT                    │
│  ─────────────                           ───────────────                    │
│  • Database encryption                   • TLS 1.2+ required                │
│  • File system encryption                • Certificate management           │
│  • Backup encryption                     • VPN for internal traffic         │
│  • Key management                        • API security                     │
│                                                                              │
│  SAFE HARBOR PROVISION                                                      │
│  ─────────────────────                                                      │
│  If encrypted data is breached, it may NOT be considered a breach if:      │
│  • Encryption meets NIST standards                                          │
│  • Keys were not compromised                                                │
│  • Data was rendered "unusable, unreadable, or indecipherable"             │
│                                                                              │
└─────────────────────────────────────────────────────────────────────────────┘

Cryptography Fundamentals

Symmetric vs Asymmetric Encryption

"""
Symmetric Encryption:
- Same key for encryption and decryption
- Fast, suitable for bulk data
- Key distribution is the challenge
- Examples: AES, ChaCha20

Asymmetric Encryption:
- Public key encrypts, private key decrypts
- Slower, suitable for small data
- Solves key distribution
- Examples: RSA, ECDSA, Ed25519
"""

from cryptography.hazmat.primitives.ciphers.aead import AESGCM
from cryptography.hazmat.primitives.asymmetric import rsa, padding
from cryptography.hazmat.primitives import hashes
import os

# Symmetric: AES-256-GCM
# SECURITY NOTE: AES-256-GCM is the NIST-recommended algorithm for HIPAA compliance.
# GCM provides both confidentiality AND integrity (authenticated encryption),
# meaning tampered ciphertext will be rejected on decryption -- critical for PHI.
def symmetric_encrypt(plaintext: bytes, key: bytes) -> tuple[bytes, bytes]:
    """Encrypt using AES-256-GCM
    
    HIPAA §164.312(a)(2)(iv): Mechanism to encrypt and decrypt ePHI.
    Using GCM mode satisfies both encryption and integrity requirements.
    """
    # SECURITY: 12-byte nonce is mandatory for GCM. Never reuse a nonce
    # with the same key -- doing so completely breaks GCM's security.
    # os.urandom is cryptographically secure on all major platforms.
    nonce = os.urandom(12)  # 96 bits for GCM
    aesgcm = AESGCM(key)
    ciphertext = aesgcm.encrypt(nonce, plaintext, None)
    return nonce, ciphertext

def symmetric_decrypt(nonce: bytes, ciphertext: bytes, key: bytes) -> bytes:
    """Decrypt using AES-256-GCM
    
    Will raise InvalidTag if ciphertext has been tampered with,
    providing tamper-evidence required by HIPAA integrity controls.
    """
    aesgcm = AESGCM(key)
    return aesgcm.decrypt(nonce, ciphertext, None)


# Asymmetric: RSA-OAEP
def asymmetric_encrypt(plaintext: bytes, public_key: rsa.RSAPublicKey) -> bytes:
    """Encrypt using RSA-OAEP (for small data like symmetric keys)"""
    return public_key.encrypt(
        plaintext,
        padding.OAEP(
            mgf=padding.MGF1(algorithm=hashes.SHA256()),
            algorithm=hashes.SHA256(),
            label=None
        )
    )

def asymmetric_decrypt(ciphertext: bytes, private_key: rsa.RSAPrivateKey) -> bytes:
    """Decrypt using RSA-OAEP"""
    return private_key.decrypt(
        ciphertext,
        padding.OAEP(
            mgf=padding.MGF1(algorithm=hashes.SHA256()),
            algorithm=hashes.SHA256(),
            label=None
        )
    )

Choosing the Right Algorithm

Use Case	Algorithm	Key Size	Notes
Data at rest	AES-256-GCM	256 bits	HIPAA recommended
File encryption	AES-256-GCM	256 bits	With authenticated encryption
Key wrapping	AES-256-KW	256 bits	For protecting DEKs
Key exchange	ECDH P-256	256 bits	For TLS
Digital signatures	Ed25519	256 bits	For audit logs
Password hashing	Argon2id	-	For user passwords

Data at Rest Encryption

Envelope Encryption Pattern

The envelope encryption pattern provides multiple layers of protection:

Master Key (KEK): Stored in HSM / AWS KMS / HashiCorp Vault
Data Encryption Keys (DEKs): Unique per record, stored encrypted
PHI Data: Encrypted with the DEK

Implementation with AWS KMS

import boto3
from cryptography.hazmat.primitives.ciphers.aead import AESGCM
import base64
import json
from dataclasses import dataclass
from typing import Optional

@dataclass
class EncryptedData:
    """Container for encrypted data with metadata"""
    ciphertext: bytes
    encrypted_dek: bytes
    nonce: bytes
    key_id: str
    algorithm: str = "AES-256-GCM"
    
    def to_dict(self) -> dict:
        return {
            "ciphertext": base64.b64encode(self.ciphertext).decode(),
            "encrypted_dek": base64.b64encode(self.encrypted_dek).decode(),
            "nonce": base64.b64encode(self.nonce).decode(),
            "key_id": self.key_id,
            "algorithm": self.algorithm,
        }
    
    @classmethod
    def from_dict(cls, data: dict) -> "EncryptedData":
        return cls(
            ciphertext=base64.b64decode(data["ciphertext"]),
            encrypted_dek=base64.b64decode(data["encrypted_dek"]),
            nonce=base64.b64decode(data["nonce"]),
            key_id=data["key_id"],
            algorithm=data.get("algorithm", "AES-256-GCM"),
        )


class EnvelopeEncryption:
    """
    HIPAA-compliant envelope encryption using AWS KMS
    """
    
    def __init__(self, kms_key_id: str, region: str = "us-east-1"):
        self.kms = boto3.client("kms", region_name=region)
        self.kms_key_id = kms_key_id
        
    def encrypt(
        self,
        plaintext: bytes,
        context: Optional[dict] = None
    ) -> EncryptedData:
        """
        Encrypt data using envelope encryption
        
        Args:
            plaintext: Data to encrypt
            context: Encryption context for additional AAD
        """
        # Generate a data encryption key from KMS
        dek_response = self.kms.generate_data_key(
            KeyId=self.kms_key_id,
            KeySpec="AES_256",
            EncryptionContext=context or {}
        )
        
        # Extract plaintext and encrypted DEK
        dek_plaintext = dek_response["Plaintext"]
        dek_encrypted = dek_response["CiphertextBlob"]
        
        # Encrypt the data with the DEK
        nonce = os.urandom(12)
        aesgcm = AESGCM(dek_plaintext)
        
        # Include context as AAD if provided
        aad = json.dumps(context).encode() if context else None
        ciphertext = aesgcm.encrypt(nonce, plaintext, aad)
        
        # Zero out the plaintext DEK
        dek_plaintext = b'\x00' * len(dek_plaintext)
        
        return EncryptedData(
            ciphertext=ciphertext,
            encrypted_dek=dek_encrypted,
            nonce=nonce,
            key_id=self.kms_key_id,
        )
    
    def decrypt(
        self,
        encrypted_data: EncryptedData,
        context: Optional[dict] = None
    ) -> bytes:
        """
        Decrypt data using envelope encryption
        """
        # Decrypt the DEK using KMS
        dek_response = self.kms.decrypt(
            CiphertextBlob=encrypted_data.encrypted_dek,
            EncryptionContext=context or {}
        )
        
        dek_plaintext = dek_response["Plaintext"]
        
        # Decrypt the data with the DEK
        aesgcm = AESGCM(dek_plaintext)
        aad = json.dumps(context).encode() if context else None
        plaintext = aesgcm.decrypt(
            encrypted_data.nonce,
            encrypted_data.ciphertext,
            aad
        )
        
        # Zero out the plaintext DEK
        dek_plaintext = b'\x00' * len(dek_plaintext)
        
        return plaintext


# Usage example
encryption = EnvelopeEncryption(kms_key_id="alias/hipaa-phi-key")

# Encrypt patient data
patient_data = json.dumps({
    "patient_id": "P12345",
    "diagnosis": "Type 2 Diabetes",
    "medications": ["Metformin 500mg"]
}).encode()

# Context binds encryption to specific patient
context = {"patient_id": "P12345", "record_type": "medical_history"}

encrypted = encryption.encrypt(patient_data, context)

# Store encrypted_data.to_dict() in database

# Later, decrypt
decrypted = encryption.decrypt(encrypted, context)

Field-Level Encryption

from typing import Any, Dict, List
from dataclasses import dataclass, field

@dataclass
class FieldEncryptionConfig:
    """Configuration for field-level encryption"""
    field_name: str
    encrypt: bool = True
    searchable: bool = False  # If true, use deterministic encryption
    indexed: bool = False

class FieldLevelEncryption:
    """
    Encrypt specific fields in documents
    
    Useful when you need to:
    - Search on some fields while encrypting others
    - Apply different encryption policies to different data
    - Minimize encryption overhead
    """
    
    def __init__(
        self,
        envelope_encryption: EnvelopeEncryption,
        encrypted_fields: List[FieldEncryptionConfig]
    ):
        self.encryption = envelope_encryption
        self.field_configs = {f.field_name: f for f in encrypted_fields}
        
    def encrypt_document(
        self,
        document: Dict[str, Any],
        context: dict
    ) -> Dict[str, Any]:
        """Encrypt specified fields in a document"""
        
        encrypted_doc = {}
        
        for key, value in document.items():
            if key in self.field_configs and self.field_configs[key].encrypt:
                config = self.field_configs[key]
                
                # Serialize value
                serialized = json.dumps(value).encode()
                
                # Encrypt
                if config.searchable:
                    # Deterministic encryption for searchable fields
                    encrypted = self._deterministic_encrypt(serialized, context)
                else:
                    # Randomized encryption for maximum security
                    encrypted = self.encryption.encrypt(serialized, context)
                
                encrypted_doc[key] = {
                    "__encrypted__": True,
                    "data": encrypted.to_dict(),
                }
            else:
                encrypted_doc[key] = value
                
        return encrypted_doc
    
    def decrypt_document(
        self,
        document: Dict[str, Any],
        context: dict
    ) -> Dict[str, Any]:
        """Decrypt specified fields in a document"""
        
        decrypted_doc = {}
        
        for key, value in document.items():
            if isinstance(value, dict) and value.get("__encrypted__"):
                encrypted_data = EncryptedData.from_dict(value["data"])
                decrypted_bytes = self.encryption.decrypt(encrypted_data, context)
                decrypted_doc[key] = json.loads(decrypted_bytes)
            else:
                decrypted_doc[key] = value
                
        return decrypted_doc
    
    def _deterministic_encrypt(
        self,
        plaintext: bytes,
        context: dict
    ) -> EncryptedData:
        """
        Deterministic encryption for searchable fields
        
        Warning: Less secure than randomized encryption.
        Use only when search is required.
        """
        # Derive a deterministic nonce from the plaintext and context
        import hashlib
        nonce_input = plaintext + json.dumps(context, sort_keys=True).encode()
        nonce = hashlib.sha256(nonce_input).digest()[:12]
        
        # Use a stable DEK for this context
        dek = self._get_deterministic_dek(context)
        
        aesgcm = AESGCM(dek)
        ciphertext = aesgcm.encrypt(nonce, plaintext, None)
        
        return EncryptedData(
            ciphertext=ciphertext,
            encrypted_dek=b"",  # DEK derived, not stored
            nonce=nonce,
            key_id="deterministic",
        )


# Usage
field_encryption = FieldLevelEncryption(
    envelope_encryption=encryption,
    encrypted_fields=[
        FieldEncryptionConfig("ssn", encrypt=True, searchable=False),
        FieldEncryptionConfig("name", encrypt=True, searchable=True),
        FieldEncryptionConfig("diagnosis", encrypt=True, searchable=False),
        FieldEncryptionConfig("patient_id", encrypt=False),  # Not encrypted
    ]
)

patient_record = {
    "patient_id": "P12345",
    "name": "John Smith",
    "ssn": "123-45-6789",
    "diagnosis": "Hypertension",
    "created_at": "2024-01-15",
}

encrypted_record = field_encryption.encrypt_document(
    patient_record,
    context={"patient_id": "P12345"}
)

Database Encryption

PostgreSQL Transparent Data Encryption (TDE)

-- PostgreSQL with pgcrypto for column-level encryption

-- Enable pgcrypto extension
CREATE EXTENSION IF NOT EXISTS pgcrypto;

-- Create encrypted column function
CREATE OR REPLACE FUNCTION encrypt_phi(
    data TEXT,
    key_id TEXT
) RETURNS BYTEA AS $$
DECLARE
    encryption_key BYTEA;
BEGIN
    -- Get key from secure key storage (simplified example)
    -- In production, use AWS KMS, HashiCorp Vault, etc.
    encryption_key := get_encryption_key(key_id);
    
    RETURN pgp_sym_encrypt(
        data,
        encode(encryption_key, 'base64'),
        'cipher-algo=aes256, compress-algo=0'
    );
END;
$$ LANGUAGE plpgsql SECURITY DEFINER;

CREATE OR REPLACE FUNCTION decrypt_phi(
    encrypted_data BYTEA,
    key_id TEXT
) RETURNS TEXT AS $$
DECLARE
    encryption_key BYTEA;
BEGIN
    encryption_key := get_encryption_key(key_id);
    
    RETURN pgp_sym_decrypt(
        encrypted_data,
        encode(encryption_key, 'base64')
    );
END;
$$ LANGUAGE plpgsql SECURITY DEFINER;

-- Create patients table with encrypted columns
CREATE TABLE patients (
    id SERIAL PRIMARY KEY,
    -- Encrypted columns
    ssn_encrypted BYTEA,
    name_encrypted BYTEA,
    diagnosis_encrypted BYTEA,
    -- Metadata (not encrypted)
    created_at TIMESTAMPTZ DEFAULT NOW(),
    updated_at TIMESTAMPTZ DEFAULT NOW(),
    -- Key reference
    encryption_key_id TEXT NOT NULL
);

-- Insert with encryption
INSERT INTO patients (
    ssn_encrypted,
    name_encrypted,
    diagnosis_encrypted,
    encryption_key_id
) VALUES (
    encrypt_phi('123-45-6789', 'key_v1'),
    encrypt_phi('John Smith', 'key_v1'),
    encrypt_phi('Type 2 Diabetes', 'key_v1'),
    'key_v1'
);

-- Select with decryption
SELECT 
    id,
    decrypt_phi(ssn_encrypted, encryption_key_id) as ssn,
    decrypt_phi(name_encrypted, encryption_key_id) as name,
    decrypt_phi(diagnosis_encrypted, encryption_key_id) as diagnosis
FROM patients
WHERE id = 1;

-- Create view for automatic decryption (for authorized users only)
CREATE VIEW patients_decrypted AS
SELECT 
    id,
    decrypt_phi(ssn_encrypted, encryption_key_id) as ssn,
    decrypt_phi(name_encrypted, encryption_key_id) as name,
    decrypt_phi(diagnosis_encrypted, encryption_key_id) as diagnosis,
    created_at,
    updated_at
FROM patients;

-- Grant access only to authorized roles
GRANT SELECT ON patients_decrypted TO hipaa_authorized_users;

MongoDB Client-Side Field-Level Encryption

from pymongo import MongoClient
from pymongo.encryption import ClientEncryption
from bson.codec_options import CodecOptions
from bson import STANDARD
import os

# MongoDB CSFLE configuration
def create_encrypted_client():
    """Create MongoDB client with client-side field-level encryption"""
    
    # KMS provider configuration (AWS KMS example)
    kms_providers = {
        "aws": {
            "accessKeyId": os.environ["AWS_ACCESS_KEY_ID"],
            "secretAccessKey": os.environ["AWS_SECRET_ACCESS_KEY"],
        }
    }
    
    # Key vault configuration
    key_vault_namespace = "encryption.__keyVault"
    
    # Schema map defining which fields to encrypt
    schema_map = {
        "healthcare.patients": {
            "bsonType": "object",
            "encryptMetadata": {
                "keyId": "/encryptionKeyId",  # Key per document
            },
            "properties": {
                "ssn": {
                    "encrypt": {
                        "bsonType": "string",
                        "algorithm": "AEAD_AES_256_CBC_HMAC_SHA_512-Deterministic"
                    }
                },
                "name": {
                    "encrypt": {
                        "bsonType": "string",
                        "algorithm": "AEAD_AES_256_CBC_HMAC_SHA_512-Random"
                    }
                },
                "medicalHistory": {
                    "encrypt": {
                        "bsonType": "array",
                        "algorithm": "AEAD_AES_256_CBC_HMAC_SHA_512-Random"
                    }
                },
                "diagnosis": {
                    "encrypt": {
                        "bsonType": "string",
                        "algorithm": "AEAD_AES_256_CBC_HMAC_SHA_512-Random"
                    }
                }
            }
        }
    }
    
    # Auto encryption options
    auto_encryption_opts = {
        "kms_providers": kms_providers,
        "key_vault_namespace": key_vault_namespace,
        "schema_map": schema_map,
    }
    
    # Create encrypted client
    client = MongoClient(
        os.environ["MONGODB_URI"],
        auto_encryption_opts=auto_encryption_opts
    )
    
    return client


def create_data_encryption_key(client_encryption, key_alt_name: str) -> bytes:
    """Create a new data encryption key in AWS KMS"""
    
    master_key = {
        "region": "us-east-1",
        "key": os.environ["AWS_KMS_KEY_ARN"],
    }
    
    data_key_id = client_encryption.create_data_key(
        "aws",
        master_key=master_key,
        key_alt_names=[key_alt_name]
    )
    
    return data_key_id


# Usage
client = create_encrypted_client()
db = client.healthcare

# Insert encrypted document (encryption happens automatically)
patient = {
    "patientId": "P12345",
    "ssn": "123-45-6789",  # Will be encrypted deterministically
    "name": "John Smith",  # Will be encrypted randomly
    "diagnosis": "Hypertension",  # Will be encrypted randomly
    "medicalHistory": [
        {"date": "2024-01-15", "procedure": "Annual checkup"}
    ],  # Will be encrypted randomly
    "createdAt": datetime.utcnow(),
}

db.patients.insert_one(patient)

# Query on deterministically encrypted field
# (Only works for deterministic encryption)
result = db.patients.find_one({"ssn": "123-45-6789"})
# Decryption happens automatically for authorized clients
print(result["name"])  # "John Smith"

Data in Transit Encryption

TLS handshake process for secure data in transit

TLS 1.3 Configuration

# Python/FastAPI with TLS 1.3
import ssl
import uvicorn
from fastapi import FastAPI

app = FastAPI()

def create_ssl_context():
    """Create secure SSL context for TLS 1.3"""
    
    context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
    
    # Minimum TLS 1.2, prefer 1.3
    context.minimum_version = ssl.TLSVersion.TLSv1_2
    context.maximum_version = ssl.TLSVersion.TLSv1_3
    
    # Load certificate and key
    context.load_cert_chain(
        certfile="/path/to/certificate.pem",
        keyfile="/path/to/private-key.pem"
    )
    
    # Strong cipher suites only
    context.set_ciphers(
        "TLS_AES_256_GCM_SHA384:"
        "TLS_CHACHA20_POLY1305_SHA256:"
        "TLS_AES_128_GCM_SHA256:"
        "ECDHE+AESGCM:"
        "DHE+AESGCM"
    )
    
    # Enable OCSP stapling
    # context.ocsp_stapling = True
    
    return context


if __name__ == "__main__":
    ssl_context = create_ssl_context()
    
    uvicorn.run(
        app,
        host="0.0.0.0",
        port=443,
        ssl_keyfile="/path/to/private-key.pem",
        ssl_certfile="/path/to/certificate.pem",
        ssl_version=ssl.PROTOCOL_TLS_SERVER,
    )

NGINX TLS Configuration

# /etc/nginx/conf.d/hipaa-ssl.conf

# SSL configuration for HIPAA compliance
server {
    listen 443 ssl http2;
    server_name api.healthcare.example.com;
    
    # SSL Certificate
    ssl_certificate /etc/nginx/ssl/fullchain.pem;
    ssl_certificate_key /etc/nginx/ssl/privkey.pem;
    
    # TLS versions - TLS 1.2 and 1.3 only
    ssl_protocols TLSv1.2 TLSv1.3;
    
    # Strong cipher suites
    ssl_ciphers 'TLS_AES_256_GCM_SHA384:TLS_CHACHA20_POLY1305_SHA256:TLS_AES_128_GCM_SHA256:ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305';
    ssl_prefer_server_ciphers on;
    
    # SSL session configuration
    ssl_session_timeout 1d;
    ssl_session_cache shared:SSL:50m;
    ssl_session_tickets off;
    
    # OCSP Stapling
    ssl_stapling on;
    ssl_stapling_verify on;
    ssl_trusted_certificate /etc/nginx/ssl/chain.pem;
    resolver 8.8.8.8 8.8.4.4 valid=300s;
    resolver_timeout 5s;
    
    # Security headers
    add_header Strict-Transport-Security "max-age=63072000; includeSubDomains; preload" always;
    add_header X-Content-Type-Options nosniff always;
    add_header X-Frame-Options DENY always;
    add_header X-XSS-Protection "1; mode=block" always;
    
    # Proxy to application
    location / {
        proxy_pass http://localhost:8000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}

# Redirect HTTP to HTTPS
server {
    listen 80;
    server_name api.healthcare.example.com;
    return 301 https://$server_name$request_uri;
}

Certificate Management with Let’s Encrypt

#!/bin/bash
# certificate-management.sh

# Install certbot
apt-get update
apt-get install -y certbot python3-certbot-nginx

# Obtain certificate
certbot certonly \
    --nginx \
    --non-interactive \
    --agree-tos \
    --email security@healthcare.example.com \
    --domains api.healthcare.example.com \
    --rsa-key-size 4096

# Set up auto-renewal
echo "0 0 * * * root certbot renew --quiet --post-hook 'systemctl reload nginx'" \
    > /etc/cron.d/certbot-renewal

# Verify configuration
nginx -t && systemctl reload nginx

Key Management

HashiCorp Vault Integration

import hvac
from typing import Optional
import os

class VaultKeyManager:
    """
    Key management using HashiCorp Vault
    
    Features:
    - Automatic key rotation
    - Key versioning
    - Audit logging
    - Access control
    """
    
    def __init__(self):
        self.client = hvac.Client(
            url=os.environ["VAULT_ADDR"],
            token=os.environ["VAULT_TOKEN"],
        )
        
    def create_encryption_key(
        self,
        key_name: str,
        key_type: str = "aes256-gcm96"
    ) -> dict:
        """Create a new encryption key in Vault"""
        
        self.client.secrets.transit.create_key(
            name=key_name,
            key_type=key_type,
            exportable=False,  # Keys never leave Vault
            allow_plaintext_backup=False,
        )
        
        return self.get_key_info(key_name)
    
    def get_key_info(self, key_name: str) -> dict:
        """Get key metadata (not the key itself)"""
        
        key_info = self.client.secrets.transit.read_key(name=key_name)
        return {
            "name": key_name,
            "type": key_info["data"]["type"],
            "latest_version": key_info["data"]["latest_version"],
            "min_decryption_version": key_info["data"]["min_decryption_version"],
            "supports_encryption": key_info["data"]["supports_encryption"],
        }
    
    def encrypt(
        self,
        key_name: str,
        plaintext: bytes,
        context: Optional[bytes] = None
    ) -> str:
        """Encrypt data using Vault Transit"""
        
        import base64
        
        result = self.client.secrets.transit.encrypt_data(
            name=key_name,
            plaintext=base64.b64encode(plaintext).decode(),
            context=base64.b64encode(context).decode() if context else None,
        )
        
        return result["data"]["ciphertext"]
    
    def decrypt(
        self,
        key_name: str,
        ciphertext: str,
        context: Optional[bytes] = None
    ) -> bytes:
        """Decrypt data using Vault Transit"""
        
        import base64
        
        result = self.client.secrets.transit.decrypt_data(
            name=key_name,
            ciphertext=ciphertext,
            context=base64.b64encode(context).decode() if context else None,
        )
        
        return base64.b64decode(result["data"]["plaintext"])
    
    def rotate_key(self, key_name: str) -> dict:
        """Rotate encryption key (old data still decryptable)"""
        
        self.client.secrets.transit.rotate_key(name=key_name)
        return self.get_key_info(key_name)
    
    def rewrap_data(
        self,
        key_name: str,
        ciphertext: str,
        context: Optional[bytes] = None
    ) -> str:
        """
        Re-encrypt data with latest key version
        (without exposing plaintext)
        """
        
        import base64
        
        result = self.client.secrets.transit.rewrap_data(
            name=key_name,
            ciphertext=ciphertext,
            context=base64.b64encode(context).decode() if context else None,
        )
        
        return result["data"]["ciphertext"]


# Usage
vault = VaultKeyManager()

# Create a key for patient data
vault.create_encryption_key("patient-phi-key")

# Encrypt patient data
context = b"patient:P12345"  # Binds ciphertext to context
ciphertext = vault.encrypt(
    "patient-phi-key",
    b'{"diagnosis": "Hypertension"}',
    context=context
)

# Decrypt
plaintext = vault.decrypt("patient-phi-key", ciphertext, context=context)

# Rotate key periodically
vault.rotate_key("patient-phi-key")

# Re-wrap old data with new key version
new_ciphertext = vault.rewrap_data("patient-phi-key", ciphertext, context=context)

Key Rotation Strategy

class KeyRotationScheduler:
    """
    Automated key rotation for HIPAA compliance
    
    Best practices:
    - Rotate master keys annually
    - Rotate data keys based on usage
    - Never delete old key versions until all data re-wrapped
    """
    
    ROTATION_POLICIES = {
        "master_key": {
            "rotation_days": 365,
            "min_versions_to_keep": 3,
        },
        "data_key": {
            "rotation_days": 90,
            "rotation_on_usage": 1_000_000,  # Or after N encryptions
            "min_versions_to_keep": 5,
        },
        "session_key": {
            "rotation_days": 1,
            "min_versions_to_keep": 2,
        },
    }
    
    async def run_rotation_check(self):
        """Check and rotate keys as needed"""
        
        for key_name, policy in self.ROTATION_POLICIES.items():
            key_info = await self.vault.get_key_info(key_name)
            
            if self._should_rotate(key_info, policy):
                await self._rotate_and_rewrap(key_name, policy)
                
    def _should_rotate(self, key_info: dict, policy: dict) -> bool:
        """Determine if key should be rotated"""
        
        last_rotation = key_info.get("last_rotation_time")
        if not last_rotation:
            return False
            
        days_since_rotation = (datetime.utcnow() - last_rotation).days
        return days_since_rotation >= policy["rotation_days"]
    
    async def _rotate_and_rewrap(self, key_name: str, policy: dict):
        """Rotate key and re-wrap existing data"""
        
        # Rotate the key
        await self.vault.rotate_key(key_name)
        
        # Schedule background re-wrapping
        await self.job_queue.enqueue(
            "rewrap_all_data",
            {"key_name": key_name}
        )
        
        # Log rotation event
        await self.audit_logger.log({
            "event_type": "KEY_ROTATION",
            "key_name": key_name,
            "new_version": key_info["latest_version"] + 1,
        })

Key Takeaways

Encrypt Everything

All PHI must be encrypted at rest and in transit

Use Envelope Encryption

Separate data keys from master keys for security and performance

TLS 1.2+ Required

Never allow older TLS versions or weak ciphers

Manage Keys Properly

Use HSM or Vault; never store keys alongside data

Practice Exercise

Set Up Key Management

Deploy HashiCorp Vault or configure AWS KMS for your application.

Implement Envelope Encryption

Create an encryption service using the envelope encryption pattern.

Configure TLS

Set up TLS 1.3 with proper cipher suites for your API.

Encrypt Database

Implement field-level encryption for PHI in your database.

Test Key Rotation

Verify that key rotation works without data loss.

Next Steps

E2E Encryption with AI

Learn how to encrypt chat data while using AI agents

Implementation Guide

Put it all together in a production system

Interview Deep-Dive

Explain envelope encryption and why it is the standard pattern for encrypting PHI at rest. Why not just encrypt everything directly with a master key?

Strong Answer:

Envelope encryption uses a two-tier key hierarchy: a Master Key (KEK) that lives in an HSM or KMS, and Data Encryption Keys (DEKs) that are unique per record or per logical unit of data. The DEK encrypts the actual PHI, and the KEK encrypts the DEK. The encrypted DEK is stored alongside the ciphertext.
The reason you do not encrypt everything directly with the master key comes down to three concerns. First, performance: calling out to an HSM or KMS for every encrypt/decrypt operation introduces latency. With envelope encryption, you generate a DEK locally (one KMS call), encrypt potentially megabytes of data with that local key (fast AES operations), then store the encrypted DEK. Decryption reverses this: one KMS call to unwrap the DEK, then local decryption.
Second, blast radius: if a single DEK is compromised, only the data encrypted with that specific DEK is at risk. If your master key is compromised, everything is exposed. By generating unique DEKs per patient record or per session, you limit the damage of any single key compromise.
Third, key rotation: rotating the master key with envelope encryption is straightforward. You re-wrap all the encrypted DEKs with the new master key (a KMS-side operation that never exposes plaintext DEKs) without re-encrypting the underlying data. Without envelope encryption, rotating a key means decrypting and re-encrypting every single record.
In a HIPAA context, this also helps with the safe harbor provision. If your master key in the HSM is never compromised but an encrypted DEK blob leaks, the attacker still cannot decrypt the PHI without access to the KMS.

Follow-up: Your team stores the encrypted DEK in the same database row as the ciphertext. An auditor flags this. Is the auditor right to be concerned?The auditor has a valid concern but the answer is nuanced. Storing the encrypted DEK alongside the ciphertext is actually the standard envelope encryption pattern — AWS KMS documentation explicitly recommends it. The security does not come from separating the encrypted DEK from the ciphertext; it comes from the fact that the encrypted DEK is useless without access to the KMS master key. The real question the auditor should ask is: who has KMS decrypt permissions? If the same database credentials that read the ciphertext also have KMS decrypt access, then an attacker who compromises the database connection effectively has both. The mitigation is IAM separation — the application role that reads from the database should require a separate, tightly scoped KMS policy to decrypt DEKs.

A junior engineer proposes using AES-256-CBC for encrypting PHI fields. You recommend AES-256-GCM instead. Explain why and what could go wrong with CBC in this context.

Strong Answer:

AES-256-GCM is an authenticated encryption mode — it provides both confidentiality and integrity in a single operation. When you decrypt, GCM verifies that the ciphertext has not been tampered with. If someone flips a bit in the ciphertext, decryption fails with an authentication error.
AES-256-CBC provides confidentiality only. It does not tell you whether the ciphertext was modified. This makes it vulnerable to padding oracle attacks: if the application returns different error messages for “invalid padding” versus “invalid data,” an attacker can iteratively recover the plaintext without knowing the key. This is not theoretical — it has been exploited in production systems.
CBC also requires careful IV management. The IV must be unique and unpredictable for each encryption operation. If you reuse an IV with the same key, an attacker can XOR two ciphertexts to derive information about the plaintexts. GCM uses a nonce that must be unique but does not need to be unpredictable, and GCM explicitly fails if you accidentally reuse a nonce.
For HIPAA compliance, the Security Rule requires integrity controls (Section 164.312(c)(1)). GCM gives you integrity for free. With CBC, you need to add a separate HMAC computation (encrypt-then-MAC), which adds complexity and more opportunities for implementation errors.

Follow-up: You discover a legacy service is using AES-128-ECB to encrypt patient SSNs. How bad is this and what is your remediation plan?This is critical. ECB mode encrypts each block independently, so identical plaintext blocks produce identical ciphertext blocks. For SSNs with predictable patterns, an attacker can build lookup tables or identify patterns without decrypting. Remediation: immediately rotate to AES-256-GCM, re-encrypt all SSNs with the new algorithm, verify the migration with checksums, then purge the old ECB-encrypted values. This should be treated as a security incident — conduct a risk assessment to determine if the ECB-encrypted data was ever exposed, because ECB encryption may not qualify for the HIPAA safe harbor provision.

Your HIPAA-compliant application needs to support searching for patients by SSN, but SSNs are encrypted at rest. How do you design this without decrypting the entire table?

Strong Answer:

The standard approach is blind indexing. For each searchable encrypted field, you compute a deterministic, one-way hash (typically HMAC-SHA256 with a dedicated search key) and store it alongside the encrypted value. To search, you compute the same HMAC of the search input and compare it against the stored hashes.
This works because the same plaintext always produces the same HMAC with the same key, enabling exact-match lookups. But the HMAC is not reversible — an attacker who obtains the hash column cannot recover SSNs from it (assuming the HMAC key is secured separately).
The tradeoff is that blind indexing only supports exact matches. You cannot do range queries, partial matches, or LIKE searches. For SSNs, exact match is usually sufficient. For names, you might index normalized forms (lowercase, stripped of punctuation).
A more advanced approach is deterministic encryption for searchable fields and randomized encryption for non-searchable fields. MongoDB’s Client-Side Field-Level Encryption offers exactly this split.
Security implication: deterministic encryption or blind indexes leak equality information. An attacker can tell which records have the same SSN. For high-cardinality fields like SSN this is acceptable, but for low-cardinality fields like gender or blood type, the leakage is significant. Never use deterministic encryption on low-cardinality PHI fields.

Follow-up: A product manager wants fuzzy search on patient names with encrypted data. How would you approach this?This is one of the hardest problems in encrypted search. You could compute and store phonetic hashes (Soundex or Metaphone) of names before encryption, and index those. “Smith” and “Smyth” produce the same Soundex code, enabling phonetic matching. This leaks phonetic equivalence classes, so you need to assess whether that is acceptable for your threat model. Alternatively, decrypt a narrowed result set server-side: first filter by department or date range (unencrypted metadata), then decrypt only those names and apply fuzzy matching in application memory. For more sophisticated approaches, look at searchable encryption schemes, but these have well-documented security tradeoffs and I would want a cryptographer to review the design before deploying it in a HIPAA context.

Walk me through your key rotation strategy for a HIPAA-compliant system. How often do you rotate, what happens to old data, and what are the failure modes?

Strong Answer:

Key rotation frequency depends on the key tier. Master keys in an HSM or KMS rotate annually, aligning with NIST guidelines. Data encryption keys rotate every 90 days or after a configurable number of encryptions. Session keys rotate per session or per message.
With envelope encryption, master key rotation is a “rewrap” operation: the KMS decrypts each stored DEK with the old master key version and re-encrypts it with the new version. The underlying data is never decrypted or re-encrypted, making master key rotation fast and safe.
Old key versions must be retained until all data encrypted under them has been re-wrapped. Never delete a key version while ciphertext encrypted under it still exists. Most KMS systems handle this with key versioning — new encryptions use the latest version, but old versions remain available for decryption.
Failure modes to plan for: (1) Incomplete rotation — some DEKs re-wrapped but the process fails partway. Each ciphertext must store which key version encrypted it. (2) Accidental key version deletion renders data permanently unrecoverable. Implement a “minimum decryption version” policy. (3) Rotation during high load — schedule during maintenance windows and make the re-wrap process idempotent and resumable. (4) Every rotation event must be audit logged.

Follow-up: An auditor asks how you would handle actual key compromise — not routine rotation, but a suspected key breach. What changes?Key compromise is fundamentally different. With routine rotation, old data remains readable under old key versions. With compromise, you must assume the attacker can decrypt anything encrypted under the compromised key. The response: immediately generate a new key version and disable the compromised version for encryption. Then launch an emergency re-encryption campaign — not just re-wrapping DEKs, but actually decrypting and re-encrypting the underlying data with new DEKs under the new master key. Simultaneously, trigger your incident response plan: assess what data was at risk, conduct the four-factor breach assessment, and prepare for potential notification obligations. The compromised key’s existence and the timeline of its exposure become forensic evidence.

Overview

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Documentation Index

​Encryption: Data at Rest & In Transit

​Why Encryption Matters for HIPAA

​Cryptography Fundamentals

​Symmetric vs Asymmetric Encryption

​Choosing the Right Algorithm

​Data at Rest Encryption

​Envelope Encryption Pattern

​Implementation with AWS KMS

​Field-Level Encryption

​Database Encryption

​PostgreSQL Transparent Data Encryption (TDE)

​MongoDB Client-Side Field-Level Encryption

​Data in Transit Encryption

​TLS 1.3 Configuration

​NGINX TLS Configuration

​Certificate Management with Let’s Encrypt

​Key Management

​HashiCorp Vault Integration

​Key Rotation Strategy

​Key Takeaways

Encrypt Everything

Use Envelope Encryption

TLS 1.2+ Required

Manage Keys Properly

​Practice Exercise

​Next Steps

E2E Encryption with AI

Implementation Guide

​Interview Deep-Dive

Encryption: Data at Rest & In Transit

Why Encryption Matters for HIPAA

Cryptography Fundamentals

Symmetric vs Asymmetric Encryption

Choosing the Right Algorithm

Data at Rest Encryption

Envelope Encryption Pattern

Implementation with AWS KMS

Field-Level Encryption

Database Encryption

PostgreSQL Transparent Data Encryption (TDE)

MongoDB Client-Side Field-Level Encryption

Data in Transit Encryption

TLS 1.3 Configuration

NGINX TLS Configuration

Certificate Management with Let’s Encrypt

Key Management

HashiCorp Vault Integration

Key Rotation Strategy

Key Takeaways

Practice Exercise

Next Steps

Interview Deep-Dive