HHS Healthcare Data Breach Change Scraper

Security researchers, healthcare risk teams, and compliance analysts use this actor to monitor public HHS OCR breach disclosures. Provide a date window, optional state/entity filters, and watch terms; the actor returns source-linked disclosure digests with affected-entity counts, incident types, and change evidence.

The default changes_only mode is designed for recurring runs: unchanged checks write zero Dataset rows and incur zero result charges. The output reports public disclosure facts as published and does not provide legal advice, security certification, or inferred culpability.

Store Quickstart

Run this actor with your monitoring filters. Results appear in the Apify Dataset and can be sent to a webhook after the Dataset charge is captured. Use dryRun to validate before committing to a schedule.

Key Features

• Public-source evidence - Uses published HHS OCR disclosure rows and preserves source context.
• Recurring change detection - Emits a digest only for a first baseline or a changed disclosure set.
• Bounded output - Produces one summary row per configured query window rather than charging per raw table cell.
• Watch filters - Filters by state, entity keyword, affected count, date window, and incident terms.
• No-change is free - A stable recurring run writes zero Dataset rows and captures zero result charges.

Use Cases

Who	Why
Developers	Automate recurring data fetches without building custom scrapers
Data teams	Pipe structured output into analytics warehouses
Ops teams	Monitor changes via webhook alerts
Product managers	Track competitor/market signals without engineering time

Input

Field	Type	Default	Description
lookbackDays	integer	30	How many days back from today to include breach submissions. Breaches submitted before this window are ignored. Default
entityKeywords	string	""	Comma-separated keywords to filter breaches by covered entity name. Case-insensitive substring match. Leave empty to inc
stateFilter	string	""	Comma-separated two-letter US state codes to filter breaches (e.g. 'CA,TX,NY'). Leave empty to include all states.
minIndividualsAffected	integer	500	Only include breaches affecting at least this many individuals. The HHS portal only lists breaches affecting 500+, so va
maxBreachesInEvidence	integer	50	Maximum number of individual breach records to include in the evidence array. Keeps output manageable.
watchTerms	string	""	Comma-separated terms that trigger actionNeeded=true when found in breach entity names or breach types. Use for competit
requestTimeoutSeconds	integer	45	HTTP timeout for the HHS portal request.
delivery	string	"dataset"	dataset: write digest to Apify dataset. webhook: POST digest to a URL.

Input Example

{
  "lookbackDays": 30,
  "entityKeywords": "",
  "stateFilter": "",
  "minIndividualsAffected": 500,
  "maxBreachesInEvidence": 50,
  "watchTerms": "",
  "requestTimeoutSeconds": 45,
  "delivery": "dataset",
  "datasetMode": "all",
  "notifyOnNoChange": false,
  "snapshotKey": "hhs-breach-monitor-snapshots",
  "dryRun": false
}

Input Examples

Example: California recent breaches

{
  "states": [
    "CA"
  ],
  "sinceDays": 30
}

Example: Multi-state coverage

{
  "states": [
    "CA",
    "NY",
    "MD",
    "WA"
  ],
  "sinceDays": 90
}

Example: Specific entity watchlist

{
  "states": [
    "CA"
  ],
  "entityKeywords": [
    "healthcare",
    "insurance"
  ]
}

Output

Field	Type	Description
queryId	string
source	string
checkedAt	timestamp
windowStart	string
windowEnd	string
executiveSummary	string
status	string
actionNeeded	boolean
totalBreachCount	number
newBreachCount	number
totalIndividualsAffected	number
breachTypeSummary	object
topEntities	array
watchTermHits	array
recommendedActions	array
changedSinceLastRun	boolean
evidence	array
meta	object
topEntities[].entityName	string
topEntities[].state	string
topEntities[].individualsAffected	number
topEntities[].breachType	string
topEntities[].submissionDate	string

Output Example

{
  "queryId": "hhs-breach-30d",
  "source": "hhs_ocr_breach_portal",
  "checkedAt": "2025-06-15T12:00:00.000Z",
  "windowStart": "2025-05-16",
  "windowEnd": "2025-06-15",
  "executiveSummary": "18 HIPAA breaches reported in the last 30 days affecting 142,853 individuals. 3 new since last run. 1 watch-term hit: UnitedHealth Group (54,200 affected).",
  "status": "action_needed",
  "actionNeeded": true,
  "totalBreachCount": 18,
  "newBreachCount": 3,
  "totalIndividualsAffected": 142853,
  "breachTypeSummary": {
    "Hacking/IT Incident": 12,
    "Unauthorized Access/Disclosure": 4,
    "Theft": 1,
    "Loss": 1
  },
  "topEntities": [
    {
      "entityName": "UnitedHealth Group",
      "state": "MN",
      "individualsAffected": 54200,
      "breachType": "Hacking/IT Incident",
      "submissionDate": "2025-06-10"
    },
    {
      "entityName": "Regional Medical Center of San Jose",
      "state": "CA",
      "individualsAffected": 32100,
      "breachType": "Hacking/IT Incident",
      "submissionDate": "2025-06-05"
    },
    {
      "entityName": "Blue Cross of Texas",
      "state": "TX",
      "individualsAffected": 21000,
      "breachType": "Unauthorized Access/Disclosure",
      "submissionDate": "2025-05-28"
    }

API Usage

Run this actor programmatically using the Apify API. Replace YOUR_API_TOKEN with your token from Apify Console → Settings → Integrations.

cURL

curl -X POST "https://api.apify.com/v2/acts/taroyamada~data-breach-disclosure-monitor/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "lookbackDays": 30, "entityKeywords": "", "stateFilter": "", "minIndividualsAffected": 500, "maxBreachesInEvidence": 50, "watchTerms": "", "requestTimeoutSeconds": 45, "delivery": "dataset", "datasetMode": "all", "notifyOnNoChange": false, "snapshotKey": "hhs-breach-monitor-snapshots", "dryRun": false }'

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("taroyamada/data-breach-disclosure-monitor").call(run_input={
  "lookbackDays": 30,
  "entityKeywords": "",
  "stateFilter": "",
  "minIndividualsAffected": 500,
  "maxBreachesInEvidence": 50,
  "watchTerms": "",
  "requestTimeoutSeconds": 45,
  "delivery": "dataset",
  "datasetMode": "all",
  "notifyOnNoChange": false,
  "snapshotKey": "hhs-breach-monitor-snapshots",
  "dryRun": false
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });
const run = await client.actor('taroyamada/data-breach-disclosure-monitor').call({
  "lookbackDays": 30,
  "entityKeywords": "",
  "stateFilter": "",
  "minIndividualsAffected": 500,
  "maxBreachesInEvidence": 50,
  "watchTerms": "",
  "requestTimeoutSeconds": 45,
  "delivery": "dataset",
  "datasetMode": "all",
  "notifyOnNoChange": false,
  "snapshotKey": "hhs-breach-monitor-snapshots",
  "dryRun": false
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Tips & Limitations

• Schedule weekly runs against your production domains to catch config drift.
• Use webhook delivery to pipe findings into your SIEM (Splunk, Datadog, Elastic).
• For CI integration, block releases on critical severity findings using exit codes.
• Combine with ssl-certificate-monitor for layered cert + headers coverage.
• Findings include links to official remediation docs — share with dev teams via the webhook payload.

FAQ

Is running this against a third-party site legal?

Passive public-header scanning is generally permitted, but follow your own compliance policies. Only scan sites you have authorization for.

How often should I scan?

Weekly for production domains; daily if you have high config-change velocity.

Can I export to a compliance tool?

Use webhook delivery or Dataset API — formats map well to Drata, Vanta, OneTrust import templates.

Is this a penetration test?

No — this actor performs passive compliance scanning only. No exploitation, fuzzing, or auth bypass.

Does this qualify as a SOC2 control?

This actor produces evidence artifacts suitable for SOC2 CC7.1 (continuous monitoring). It is not itself a SOC2 certification.

Related Actors

Security & Compliance cluster — explore related Apify tools:

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• Trust Center & Subprocessor Monitor API — Monitor vendor trust centers, subprocessor lists, DPA updates, and security posture changes.

Cost

Pay Per Event:

• actor-start: $0.01 (flat fee per run)
• dataset-item: $0.003 per output item

Example: 1,000 items = $0.01 + (1,000 × $0.003) = $3.01

No subscription required — you only pay for what you use.

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