Load ReversingLabs Spectra Intelligence data to DuckDB

ReversingLabs Spectra Intelligence provides REST APIs for file reputation, analysis, and malware hunting information. Everything needed to build a working ReversingLabs Spectra Intelligence → 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.

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Build your ReversingLabs Spectra Intelligence to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from ReversingLabs Spectra Intelligence 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 ReversingLabs Spectra Intelligence 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.

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ReversingLabs Spectra Intelligence API at a glance

These values come from the ReversingLabs Spectra Intelligence API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the ReversingLabs Spectra Intelligence API?

All requests require an HTTP Authorization header using basic authentication (username and password). The credentials should be encoded as a base64 string according to the standard HTTP Basic Authentication scheme.

1. Get your credentials

ReversingLabs Spectra Intelligence API credentials (username and password) are not generated via a self-service dashboard; they are provided by ReversingLabs Support upon account activation. If you have an active subscription via a marketplace (e.g., Azure), you can retrieve your credentials by navigating to the subscription details page and clicking the link to open the ReversingLabs API Provisioning Portal. Inside this portal, your username and password can typically be viewed by hovering over the designated credential fields. If you do not have an existing account, contact ReversingLabs Sales or Support to request access.

2. Add them to .dlt/secrets.toml

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[sources.reversinglabs_spectra_intelligence_source]
credentials = "REPLACE_ME"

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.

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What ReversingLabs Spectra Intelligence data can I load into DuckDB?

These are the ReversingLabs Spectra Intelligence endpoints dlt can load into DuckDB:

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How do I load only new ReversingLabs Spectra Intelligence records?

ReversingLabs Spectra Intelligence exposes last_timestamp on api/feeds/tcf-0101/pull, 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.

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{"name": "malicious_files_feed", "endpoint": {
    "path": "api/feeds/tcf-0101/pull",
    "data_selector": "rl.malware_detection_feed.entries",
    "incremental": {"cursor_path": "last_timestamp", "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.

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What does the generated ReversingLabs Spectra Intelligence pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading tca-0104 (File Analysis API) and tca-0201 (File download API) from the ReversingLabs Spectra Intelligence API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def reversinglabs_spectra_intelligence_source(credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://data.reversinglabs.com",
            "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": credentials},
        },
        "resources": [
            {"name": "malicious_files_feed", "endpoint": {"path": "api/feeds/tcf-0101/pull", "data_selector": "rl.malware_detection_feed.entries"}},
            {"name": "ioc_latest", "endpoint": {"path": "api/ioc/v1/query/sample/latest", "data_selector": "rl.entries"}}
        ],
    }
    yield from rest_api_resources(config)


def load_reversinglabs_spectra_intelligence_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="reversinglabs_spectra_intelligence_pipeline",
        destination="duckdb",
        dataset_name="reversinglabs_spectra_intelligence_data",
    )
    load_info = pipeline.run(reversinglabs_spectra_intelligence_source())
    print(load_info)


if __name__ == "__main__":
    load_reversinglabs_spectra_intelligence_to_duckdb()

Run it with python reversinglabs_spectra_intelligence_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query ReversingLabs Spectra Intelligence 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):

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import dlt

data = dlt.pipeline("reversinglabs_spectra_intelligence_pipeline").dataset()
df = data.ioc_latest.df()
print(df.head())

SQL:

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SELECT * FROM reversinglabs_spectra_intelligence_data.ioc_latest LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the ReversingLabs Spectra Intelligence 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 ReversingLabs Spectra Intelligence loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load ReversingLabs Spectra Intelligence data to?

dlt loads into any of these — only the destination argument changes:

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.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack