Insights
Our investigation method
How datafetch.wtf turns a selector into a defensible narrative: stream first, correlate second, export last — and keep the dead ends visible.
Insights
Our investigation method
How datafetch.wtf turns a selector into a defensible narrative: stream first, correlate second, export last — and keep the dead ends visible.
We design for investigators who must explain their work. That means labeled sources, timestamps, and the courage to show empty modules.
The console and API share one method so automation never invents a second story.
- Stream results as modules finish
- Correlate presence with exposure
- Export with provenance intact
- Document empty lanes honestly
Method
Dead ends included
Like our case studies, we show empty lanes — so you trust the hits that remain.
A finding is stronger when you can see what was tried and failed. datafetch.wtf keeps that path in history.
Correlate
Presence vs exposure
We deliberately separate accounts that exist today from credentials that leaked before — the mistake that wrecks briefings.
Ship
Human and machine parity
Whatever you automate through the API should match what an analyst sees in the console.
Ready to investigate
Open the console or call the API — same modules, live results, black-and-white clarity.
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