OpenSanctions Entities Scraper

OpenSanctions Entities Scraper

Stream sanctioned entities, PEPs, and persons of interest from OpenSanctions, filtered by list, country, or risk topic. Each record returns the canonical name, aliases, addresses, and identifiers in a flat, machine-readable row. Export to CSV, JSON, Excel, or XML.

OpenSanctions consolidates global sanctions lists, PEP registries, and wanted databases into one open dataset. This Actor reads that public data directly, letting you pull targeted entities without building your own ETL pipeline. Filter by source list, entity type, country, or risk topic, and get a clean, deduplicated record for each match.

Who uses it	What they scrape OpenSanctions for
Compliance officers	Build a local watchlist of sanctioned individuals and entities for a specific jurisdiction.
Financial crime investigators	Pull the latest PEPs and their close associates for enhanced due diligence.
Supply chain risk managers	Check for debarred suppliers and companies linked to forced labor or trafficking.
OSINT researchers	Collect all entities linked to a specific oligarch or intelligence officer network.

What it does

This Actor collects entities from the OpenSanctions API and returns each one as a flat row with its name, aliases, identifiers, and risk topics.

• 📋 Source list filter: Restrict results to a single authority, such as the US OFAC SDN List, the EU Financial Sanctions File, or the INTERPOL Red Notices.
• 🏷️ Risk topic filter: Pull only entities flagged for sanctions, PEP roles, terrorism, cybercrime, trafficking, or frozen assets.
• 🌐 Country filter: Limit the dataset to entities tied to a specific country using its ISO 3166-1 alpha-2 code.
• 🔍 Name search: Find a specific person or organization by canonical name or alias, using a case-insensitive substring or a fuzzy match that ignores diacritics and punctuation.
• 📊 Compact output: Cap the number of aliases per entity to keep payloads small, as some records carry hundreds of transliteration variants.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with OpenSanctions data

🛡️ Sanctions screening list generation.

A compliance team runs the Actor weekly with the 'sanctions' dataset and a country filter for 'ru' to update their internal screening tool with the latest Russian sanctions targets.

👤 PEP and RCA identification.

A financial crime analyst pulls all entities with the 'role.pep' and 'role.rca' topics to identify politically exposed persons and their close associates during client onboarding.

🚢 Maritime and aviation asset tracing.

An investigator filters by the 'Vessel' or 'Airplane' schema to collect sanctioned transport assets and their registered owners for a network analysis.

🏢 Debarment and exclusion checks.

A procurement officer extracts entities from the 'debarment' dataset to verify that a new vendor is not on the World Bank or US SAM exclusion lists.

Why choose this scraper

	What you get
No API key or registration	Reads the public OpenSanctions bulk data, so you skip the official API's rate limits and authentication.
Fixed, flat schema	Every entity, whether a person, vessel, or company, lands in your dataset with the same predictable columns.
Targeted extraction	Pull only the entities you need by combining source list, topic, country, and name filters in a single run.

How it compares

This Actor focuses on targeted extraction from the core OpenSanctions API, while the alternative combines OpenSanctions with other registries and adds a screening mode.

Feature	ParseForge	PEP Screening - OpenSanctions + Wikidata + National Registries
Direct OpenSanctions API extraction	Yes	Yes
Filter by specific source list (e.g., US OFAC SDN)	Yes	Not listed
Filter by risk topic (e.g., cybercrime, trafficking)	Yes	Not listed
Fuzzy name matching against aliases	Yes	Yes
Combined Wikidata and national registry data	No	Yes
Built-in batch screening mode	No	Yes

Configure the run

Drive the Actor from a dataset collection, a specific source list, a country code, a risk topic, and a name query, alone or together, and filters run as each entity is read so only matches reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
 "maxItems": 10
}

A larger pull:

{
 "maxItems": 200
}

Pricing

Pay-per-result: $0.03 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$3.00
1,000 results	$30.00
10,000 results	$300.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the OpenSanctions Entities Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to OpenSanctions through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/opensanctions-entities-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that your filters are not too restrictive. A specific name query combined with a narrow topic and a single source list might return zero matches. Try broadening one filter at a time.

The run is taking a long time.

Pulling the full 'default' collection with a high maxItems value can take a while. Use a more specific dataset collection or a lower entity limit to speed up the run.

I am missing aliases for some entities.

Check the 'Max Aliases per Entity' setting. If it is set too low, the Actor truncates the aliases array. Increase the cap to capture more name variants.

The country filter is not working as expected.

Ensure you are using the correct lowercase ISO 3166-1 alpha-2 code. For example, use 'gb' for the United Kingdom, not 'uk'.

FAQ

Question	Answer
What is the difference between the 'sanctions' and 'default' dataset collections?	The 'sanctions' collection is a consolidated list of all global sanctions. The 'default' collection is the full union of all datasets, including sanctions, PEPs, crime, and debarment lists.
How does the fuzzy name match work?	The fuzzy match strips diacritics, punctuation, and standardizes casing before comparing the query to the entity's canonical name and all aliases. It catches transliteration variants and minor spelling differences.
Can I pull entities from only one specific sanctions list, like the US OFAC SDN?	Yes. Use the 'Specific Source List' filter and select 'US OFAC SDN List' to restrict the output to entities from that single authority.
Does this Actor include relatives and close associates of sanctioned persons?	Yes. When you select the 'Linked to sanctioned entity' or 'Relative or Close Associate (RCA)' topic, the Actor returns entities that OpenSanctions has flagged with those relationships.
What entity types can I filter by?	You can filter by Person, Organization, Company, Legal Entity, Vessel, Airplane, Position, or Crypto Wallet. Leave the filter empty to get all types.
How do I filter by country?	Enter the lowercase two-letter ISO 3166-1 alpha-2 code, such as 'ir' for Iran or 'kp' for North Korea, in the Country field.
Is the data updated live?	The Actor reads from the public OpenSanctions API, which is refreshed daily from its upstream sources. Each run pulls the latest available data.
Can I search for a specific person by name?	Yes. Enter a name in the 'Entity name' field and choose a substring or fuzzy match mode to find a specific individual or organization across all aliases.
What is the maximum number of entities I can collect in one run?	You can set the 'Maximum entities' input up to 1,000,000 per run.
Why would I cap the number of aliases per entity?	Some entities, particularly sanctioned individuals, have hundreds of transliteration variants. Capping aliases keeps each row compact and your dataset easier to process.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by OpenSanctions.org. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.