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OSINT Recon Assistant for Security Researchers
I’m developing cleaner ways to organize authorized reconnaissance.
GEARZ OSINT Helper brings link extraction, subdomain discovery, and research workflows into one Replit interface with optional AI support. Separately, ReconSynth is a local Next.js prototype that runs subfinder and ProjectDiscovery httpx and turns the output into a reviewable report.
GEARZ OSINT Helper: https://replit.com/@gear8405/GearzOSINT?v=1
ReconSynth source: https://github.com/Gearsoldier/gearz-reconsynth
replit.com
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A strong specialist skill is useless if the wrong system gets invoked. Long-running AI work breaks in boring, expensive ways.
That is not a prompting problem. It is a routing and authority problem.
How I can help you:
I build project routers for teams using multiple AI workflows, agents, or specialist assistants so that they work with each other as a team.
I design source-of-truth resolutions so your agents retrieve the current rules instead of improvising or relying on assumptions or stale chat data.
I create reusable skill registries and specialist handoff logic hardened by determined and dedicated flow states reducing the need for model reliance on its own internal and displaced memory context.
I separate project states with individualized canonical states bound by rules living under essential model instructions and routed properly so unrelated workflows do not contaminate one another, but exist with awareness of the role each project plays, enabling a persistently growing ecosystem to develop organically.
I add governance wrappers, escalation hooks, and recovery mirrors around existing AI stacks so that trust is designed at the root, and variance is eliminated with rule based source archiving and implementation.
Trust means closing your eyes at night and sleeping soundly because your agents got your back. And I can put it all together for you, precision results sourced and undisputed because I got tired of doing things the hard way.
Phillip, agree that routing is where it breaks. In our builds the worst bugs came from an agent pulling an old rule from chat history instead of the current source. Pinning one source of truth per project fixed more than any prompt change did.
I designed and developed a web-based Conflict Early Warning and Management Control Room that helps organizations collect, manage and analyze conflict-related information. The system includes an administrative dashboard, incident reporting, interactive geographic mapping, report management, officer/user management, authentication and role-based access, document handling, fact-checking workflows and data visualization. Built with React, TypeScript and Supabase.
NetworkAI — AI-Powered Campus Network Monitoring System
A real-time network monitoring dashboard designed to help campus IT teams observe network health, monitor interfaces, and identify potential issues from a single interface.
What I built
Real-time network monitoring with live interface and system status
Network interface analytics showing traffic and connection activity
Historical monitoring data for analyzing network behavior over time
Live WebSocket communication for continuously updated monitoring data
Network controls to start and stop monitoring directly from the dashboard
Interactive charts and visualizations for easier interpretation of
network metrics
Responsive dashboard UI designed for clear monitoring rather than unnecessary complexity
FastAPI backend providing REST APIs and WebSocket communication
React frontend with a modern monitoring-focused interface
Why I built it
The goal was to create a practical campus network monitoring system that demonstrates how real-time networking data can be collected, processed, and presented through a modern web interface.
cool project bro. live data + history in one place is useful. how do you handle reconnecting when the websocket drops?