I'm planning to build a completely private, self-hosted CAPTCHA solving system that runs entirely on my own hardware. The goal is to have a system that can handle virtually any CAPTCHA type (text, image grids, sliders, audio, etc.) without relying on external services or paying per-solve fees.
Why I'm Building It
Privacy — No external API calls, no data leaving my network
Cost — No per-request fees, no subscriptions
Control — Full ownership of the system
Speed — Local inference should be faster than cloud-based solutions
Learning — It's a fascinating technical challenge
How It Would Work (High Level)
A single REST API endpoint that automation tools can call
API key authentication with rate limiting
Smart routing that sends each CAPTCHA to the best solver for the job
Multiple AI models running locally on a powerful GPU
A web-based dashboard for monitoring usage and managing API keys
Secure remote access via Cloudflare with WAF protection
What I'm Curious About
Has anyone here built something like this? I'd love to hear about your experience, what worked, what didn't, and any lessons learned.
What's the biggest challenge you faced? I'm thinking VRAM management and model accuracy will be the main hurdles.
Are you using a commercial solver? If so, what's your experience been like with cost, speed, and reliability?
Any advice on model selection? I've been researching different architectures but would appreciate any real-world insights.
How are you handling detection of different CAPTCHA types? I'm planning something based on DOM analysis but open to suggestions.
Key Features I'm Aiming For
Universal coverage (all major CAPTCHA types)
Local inference (no external dependencies)
Smart validation (auto-correct wrong config types)
API key management
Real-time statistics dashboard
Multi-user support
Rate limiting
Audit logging
Cloud fallback (optional, for rare edge cases)
Current Status
I'm currently in the planning and research phase. I've mapped out the architecture and started evaluating different open-source models that could be integrated. Next steps are setting up the test environment and starting to build the core solver logic.
I've been doing automation work for a few years and have always been frustrated by the cost and privacy implications of commercial solving services. This project is my attempt to solve that problem once and for all.
I'm also really interested in the AI/ML side of things and see this as a great opportunity to get hands-on with some interesting models and architectures.
Why I'm Building It
Privacy — No external API calls, no data leaving my network
Cost — No per-request fees, no subscriptions
Control — Full ownership of the system
Speed — Local inference should be faster than cloud-based solutions
Learning — It's a fascinating technical challenge
How It Would Work (High Level)
A single REST API endpoint that automation tools can call
API key authentication with rate limiting
Smart routing that sends each CAPTCHA to the best solver for the job
Multiple AI models running locally on a powerful GPU
A web-based dashboard for monitoring usage and managing API keys
Secure remote access via Cloudflare with WAF protection
What I'm Curious About
Has anyone here built something like this? I'd love to hear about your experience, what worked, what didn't, and any lessons learned.
What's the biggest challenge you faced? I'm thinking VRAM management and model accuracy will be the main hurdles.
Are you using a commercial solver? If so, what's your experience been like with cost, speed, and reliability?
Any advice on model selection? I've been researching different architectures but would appreciate any real-world insights.
How are you handling detection of different CAPTCHA types? I'm planning something based on DOM analysis but open to suggestions.
Key Features I'm Aiming For
Universal coverage (all major CAPTCHA types)
Local inference (no external dependencies)
Smart validation (auto-correct wrong config types)
API key management
Real-time statistics dashboard
Multi-user support
Rate limiting
Audit logging
Cloud fallback (optional, for rare edge cases)
Current Status
I'm currently in the planning and research phase. I've mapped out the architecture and started evaluating different open-source models that could be integrated. Next steps are setting up the test environment and starting to build the core solver logic.
I've been doing automation work for a few years and have always been frustrated by the cost and privacy implications of commercial solving services. This project is my attempt to solve that problem once and for all.
I'm also really interested in the AI/ML side of things and see this as a great opportunity to get hands-on with some interesting models and architectures.