Continuous Token Exposure Monitoring Platform
Budget: $30 – $250 USD
I want to build a modular service that sniffs out accidentally exposed HTTP API tokens every day, not just in the usual domain-wide crawls but in the places developers most often slip up—public repos, paste sites, forums, mis-indexed backups, logs, and any other corners you can suggest.
Key expectations
• The first release should concentrate on Python code, with the scanner recognising common token patterns inside `.py`, config, YAML and JSON files.
• It must run continuously, queueing new or updated sources and triggering Email notifications the moment a fresh leak appears.
• The architecture should make it painless to bolt on additional sources or languages later; think pluggable collectors, a central pattern-matching engine, and a lightweight storage layer for deduplication and history tracking.
Deliverables
1. Docker-ready codebase (Python) that pulls from at least three high-value platforms of your choosing.
2. Pattern library covering common API token formats and an easy way for me to add more.
3. Worker that schedules scans, persists matches, and fires Email notifications.
4. Brief setup guide plus examples showing a daily run successfully capturing sample tokens from test data.
If you have experience tapping into obscure repos, grey-hat paste archives, or search-engine dorks for hidden backups, tell me how you would wire those in; I’m open to fresh ideas as long as the system stays lean and extensible.
Please message me if you have read the description properly and feel you are capable of this task!
Key expectations
• The first release should concentrate on Python code, with the scanner recognising common token patterns inside `.py`, config, YAML and JSON files.
• It must run continuously, queueing new or updated sources and triggering Email notifications the moment a fresh leak appears.
• The architecture should make it painless to bolt on additional sources or languages later; think pluggable collectors, a central pattern-matching engine, and a lightweight storage layer for deduplication and history tracking.
Deliverables
1. Docker-ready codebase (Python) that pulls from at least three high-value platforms of your choosing.
2. Pattern library covering common API token formats and an easy way for me to add more.
3. Worker that schedules scans, persists matches, and fires Email notifications.
4. Brief setup guide plus examples showing a daily run successfully capturing sample tokens from test data.
If you have experience tapping into obscure repos, grey-hat paste archives, or search-engine dorks for hidden backups, tell me how you would wire those in; I’m open to fresh ideas as long as the system stays lean and extensible.
Please message me if you have read the description properly and feel you are capable of this task!