Python scripts that filter, parse, mask, and analyze FileZilla Server Log files. Works on Windows, Linux, and Mac systems.
WARNING: NEW VERSIONS ARE BEING POSTED TO GITHUB HERE: https://github.com/Stunner/FileZilla-Log-Analyzer
Features
- Line-by-line log file interpretation
- Listed summary of all user actions
- Recreate log files with masked values such as IP, usernames, and files/folders
- Filter by user name, IP address, date, and port in any combination
- Parse logs by line number and/or user session
Project Samples
Categories
Log AnalysisLicense
GNU General Public License version 2.0 (GPLv2)Other Useful Business Software
Turn traffic into pipeline and prospects into customers
Docket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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