# UK ICO Enforcement Actions (`spookyweb/uk-ico-enforcement-actions`) Actor Search the UK Information Commissioner's Office (ICO) Enforcement Register for monetary penalties, reprimands, enforcement notices and prosecutions under GDPR, UK GDPR, PECR and Data Protection Act 2018. - **URL**: https://apify.com/spookyweb/uk-ico-enforcement-actions.md - **Developed by:** [Dan](https://apify.com/spookyweb) (community) - **Categories:** AI, Automation, Lead generation - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $40.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## UK ICO Enforcement Actions Search the **UK Information Commissioner's Office (ICO) Enforcement Register** for monetary penalties, reprimands, enforcement notices and prosecutions under GDPR, UK GDPR, PECR and Data Protection Act 2018. Returns structured data on fines, enforcement actions, breach types, affected organisations and sectors. All data is public from the ICO and licensed under the Open Government Licence v3.0. --- ### What this actor does - Searches the official ICO enforcement register at ico.org.uk - Filters by enforcement type (fines, reprimands, notices, prosecutions) - Filters by sector (health, finance, tech, government, etc.) - Filters by date range - Keyword search for organisations or breach types - Automatic pagination through result pages - Clean structured JSON/CSV output --- ### Example use cases **Privacy & GDPR consultancies** — Build trend reports showing enforcement patterns by sector, breach type and fine amounts. Demonstrate risks to clients using real-world examples. **Cybersecurity firms & MSPs** — Use enforcement actions as sales tools ("Capita lost £14m for lacking MFA - we can prevent this"). Track technical failures identified by ICO to improve service offerings. **Law firms** — Identify companies fined for data breaches = potential group action targets. Build databases of enforcement precedent for client defense strategies. **Cyber insurance underwriters** — Analyze sector risk exposure, track common failure patterns (no MFA, poor incident response), benchmark client security against enforcement data. **Compliance software vendors** — Create training modules with real ICO enforcement examples. Track regulatory trends to update product features. Build "what not to do" case studies. **Researchers & journalists** — Analyze UK vs EU enforcement divergence, track ICO enforcement philosophy shifts, investigate sector-specific compliance failures. **Competitors of fined companies** — Monitor competitor enforcement actions for reputational intelligence and competitive positioning. --- ### Output fields Each result contains: | Field | Description | |---|---| | `01_organisation` | Company or entity name | | `02_title` | Enforcement action title/description | | `03_enforcementType` | Monetary penalty, Reprimand, Enforcement notice, or Prosecution | | `04_fineAmount` | Fine amount (e.g. "£14,000,000") if applicable | | `05_sector` | Industry sector (Health, Finance, Tech, etc.) | | `06_date` | Date of enforcement action | | `07_summary` | Details of the breach and ICO's reasoning | | `08_detailsUrl` | Link to full enforcement notice PDF | *Note: Column names include numeric prefixes to ensure correct display order in exports and previews.* --- ### Enforcement types explained **Monetary Penalty** — Financial fines up to £17.5 million or 4% of global turnover for serious GDPR breaches. Typically reserved for major data breaches, systemic failures, or reckless behaviour. **Reprimand** — Formal written warning for GDPR violations. Often used for public sector organisations instead of fines, or for first-time offenders who cooperate. **Enforcement Notice** — Legal order requiring organisation to take (or stop) specific actions to comply with data protection law. Non-compliance can lead to prosecution. **Prosecution** — Criminal proceedings for serious offences like unlawfully obtaining/disclosing personal data, obstructing ICO investigations, or failing to pay data protection fees. --- ### Sector coverage The ICO enforces across all UK sectors: - Central & local government - Health & social care - Finance, insurance & credit - Education & childcare - Online technology & telecoms - Marketing - Retail & manufacturing - Legal services - Charitable & voluntary - Criminal justice - Media - Transport & leisure - Utilities - Regulators --- ### Data source & licence All data sourced from the [ICO Enforcement Register](https://ico.org.uk/action-weve-taken/enforcement/) maintained by the Information Commissioner's Office. Published under the **Open Government Licence v3.0** — commercial use permitted with attribution. **Attribution:** *Contains public sector information licensed under the Open Government Licence v3.0.* Full licence: [nationalarchives.gov.uk/doc/open-government-licence/version/3](https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) --- ### Performance - Typical run for 100 results: 60-120 seconds (depends on filters) - Pagination supported for larger datasets - Rate-limited to respect ICO servers --- ### Notes - ICO enforcement data dates back several years - Large fines are often negotiated down from initial amounts (check details URL for settlement info) - Public sector organisations typically receive reprimands instead of fines - PECR (spam/marketing) violations are more common but smaller fines than GDPR breaches - Data is continuously updated as new enforcement actions are published # Actor input Schema ## `keywords` (type: `string`): Search by company name, breach type, or keywords. Leave empty for all results. ## `enforcementType` (type: `array`): Type of enforcement action to filter by ## `sector` (type: `array`): Industry sector to filter by ## `dateFrom` (type: `string`): Start date for enforcement actions (YYYY-MM-DD) ## `dateTo` (type: `string`): End date for enforcement actions (YYYY-MM-DD) ## `maxResults` (type: `integer`): Maximum number of enforcement actions to return. Default 100, max 1000. ## Actor input object example ```json { "keywords": "data breach", "enforcementType": [], "sector": [], "dateFrom": "2024-01-01", "dateTo": "2025-12-31", "maxResults": 100 } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("spookyweb/uk-ico-enforcement-actions").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("spookyweb/uk-ico-enforcement-actions").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call spookyweb/uk-ico-enforcement-actions --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=spookyweb/uk-ico-enforcement-actions", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "UK ICO Enforcement Actions", "description": "Search the UK Information Commissioner's Office (ICO) Enforcement Register for monetary penalties, reprimands, enforcement notices and prosecutions under GDPR, UK GDPR, PECR and Data Protection Act 2018.", "version": "0.0", "x-build-id": "uJ9wGvxnTnMuWtA8h" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/spookyweb~uk-ico-enforcement-actions/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-spookyweb-uk-ico-enforcement-actions", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/spookyweb~uk-ico-enforcement-actions/runs": { "post": { "operationId": "runs-sync-spookyweb-uk-ico-enforcement-actions", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/spookyweb~uk-ico-enforcement-actions/run-sync": { "post": { "operationId": "run-sync-spookyweb-uk-ico-enforcement-actions", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "keywords": { "title": "Keywords", "type": "string", "description": "Search by company name, breach type, or keywords. Leave empty for all results." }, "enforcementType": { "title": "Enforcement type", "uniqueItems": true, "type": "array", "description": "Type of enforcement action to filter by", "items": { "type": "string", "enum": [ "monetary_penalties", "enforcement_notices", "reprimands", "prosecutions" ] }, "default": [] }, "sector": { "title": "Sector", "uniqueItems": true, "type": "array", "description": "Industry sector to filter by", "items": { "type": "string", "enum": [ "central_government", "charitable_voluntary", "criminal_justice", "education_childcare", "finance_insurance_credit", "general_business", "health", "land_property", "legal", "local_government", "marketing", "media", "online_tech_telecoms", "political", "regulators", "retail_manufacture", "social_care", "transport_leisure", "utilities" ] }, "default": [] }, "dateFrom": { "title": "Date from", "type": "string", "description": "Start date for enforcement actions (YYYY-MM-DD)" }, "dateTo": { "title": "Date to", "type": "string", "description": "End date for enforcement actions (YYYY-MM-DD)" }, "maxResults": { "title": "Maximum results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of enforcement actions to return. Default 100, max 1000.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```