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ZebraByte Dark Web Intelligence

Defensive threat-intelligence platform for exposure discovery, investigation, and continuous monitoring. Public architecture: Cloudflare Workers, Workflows, Queues, D1, R2, Workers AI, Analytics Engine, rate limiting and a constrained Tor collector. Sensitive customer data, provider credentials and Tor-collected evidence are isolated from the public interface.

Technical stack: Threat Intelligence · Cloudflare Workers · Tor · D1 · R2 · Workers AI · TypeScript

Real Wix Portfolio cover: public website or source repository
Real Wix Portfolio cover: public website or source repository

Code and demonstration

Problem to solve

An exposure-monitoring platform needs more than a search box: investigation state, isolated evidence, tenant access controls and defensible monitoring workflows.

Architecture and approach

The public implementation uses Cloudflare Workers for the application/API; Workflows and Queues for orchestrated investigations; D1 for structured state; R2 for retained evidence; and Workers AI for constrained defensive analysis. A short-lived Tor collector is isolated in a Cloudflare Container.

What it provides

Tenant-scoped investigations, monitoring jobs, quotas and audit metadata Cloudflare-native evidence retention and asynchronous processing Separate clear-web enrichment, private collection and AI-assisted analysis

Security considerations

Tor retrieval is constrained to validated .onion addresses; no generic proxy or internal-network scanner. Evidence is treated as untrusted input; service credentials do not belong in the collector. Optional features require provisioning; the public README explicitly distinguishes them from configured functionality.

GitHub repository

Source code on GitHub

Open project