Load VirusTotal data to DuckDB
Build a VirusTotal to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the VirusTotal API base URL, auth, endpoints, and incremental loading.
VirusTotal is a threat intelligence platform providing an API to scan and analyze files, URLs, domains, and IP addresses for malicious content. Everything needed to build a working VirusTotal → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.
Build your VirusTotal to DuckDB pipeline
Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.
PromptRunuvx dlthub-init@latestto build a pipeline from VirusTotal to DuckDB and run it on dltHub
That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the VirusTotal API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →
Prefer to write it yourself? Every fact the agent uses is below.
VirusTotal API at a glance
| Base URL | https://www.virustotal.com/api/v3 |
| Example endpoint | GET comments |
| Records found at | data |
| Authentication | all requests require the x-apikey header with your personal API key — sent in the x-apikey header |
| Pagination | Cursor-based via cursor, next cursor at meta.cursor (and also returned as query param in links.next), page size via limit (default 10, max 300). Pagination is cursor-based: read the continuation cursor from the response (meta.cursor) and send it back as the 'cursor' query parameter on the next request. Page size is controlled with the 'limit' query parameter. Example shown in Collections responses also includes limit and cursor on links.next. |
| Incremental field | cursor |
| Record id | id |
| API reference | https://docs.virustotal.com/reference/authentication |
These values come from the VirusTotal API reference — the authoritative source if anything here looks out of date.
How do I authenticate with the VirusTotal API?
All requests require the 'x-apikey' header containing the user's API key. Additionally, it is standard practice to include the 'accept: application/json' header.
1. Get your credentials
- Register for a free VirusTotal Community account at https://www.virustotal.com/. 2. Sign in to your account. 3. Click on your user name in the top right-hand corner of the page to open the dropdown menu. 4. Navigate to the API key section (or visit https://www.virustotal.com/gui/my-apikey directly while signed in) to view and copy your personal API key.
2. Add them to .dlt/secrets.toml
[sources.virustotal_source] virustotal_api_key = "your_api_key_here"
dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.
What VirusTotal data can I load into DuckDB?
These are the VirusTotal endpoints dlt can load into DuckDB:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| comments | /comments | GET | data | Retrieve the latest comments. |
| hunting_rulesets | /intelligence/hunting_rulesets | GET | data | Retrieve VT Hunting rulesets. |
| intelligence_search | /intelligence/search | GET | data | Search for files/URLs using queries. |
| collections | /collections | GET | data | List system collections. |
| graph_nodes | /graphs/{id}/nodes | GET | data | Retrieve nodes within a graph. |
How do I load only new VirusTotal records?
VirusTotal exposes cursor on comments, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.
{"name": "comments", "endpoint": { "path": "comments", "data_selector": "data", "incremental": {"cursor_path": "cursor", "initial_value": "2024-01-01T00:00:00Z"}, }}
On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.
What does the generated VirusTotal pipeline look like?
A standard dlt REST API pipeline — the same code you would write by hand, loading /files and /urls (common examples for file and URL analysis) from the VirusTotal API into DuckDB:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def virustotal_source(api_key=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://www.virustotal.com/api/v3", "auth": {"type": "api_key", "api_key": api_key, "name": "x-apikey", "location": "header"}, }, "resources": [ {"name": "comments", "endpoint": {"path": "comments", "data_selector": "data"}}, {"name": "intelligence_search", "endpoint": {"path": "intelligence/search", "data_selector": "data"}} ], } yield from rest_api_resources(config) def load_virustotal_to_duckdb() -> None: pipeline = dlt.pipeline( pipeline_name="virustotal_pipeline", destination="duckdb", dataset_name="virustotal_data", ) load_info = pipeline.run(virustotal_source()) print(load_info) if __name__ == "__main__": load_virustotal_to_duckdb()
Run it with python virustotal_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.
How do I query VirusTotal data in DuckDB?
dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.
Python (pandas DataFrame):
import dlt data = dlt.pipeline("virustotal_pipeline").dataset() df = data.comments.df() print(df.head())
SQL:
SELECT * FROM virustotal_data.comments LIMIT 10;
See querying your data with dataset and exploring it in marimo notebooks.
How do I deploy the VirusTotal to DuckDB pipeline in production?
The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.
- Deploy & schedule — run the pipeline as a managed job with automatic retries.
- Monitor — observable job queues, alerting, and load metrics for every run.
- Transform — promote raw VirusTotal loads into governed, documented models.
- Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.
What other destinations can I load VirusTotal data to?
dlt loads into any of these — only the destination argument changes:
| Destination | Example value |
|---|---|
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.
Next steps
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