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Malicious actors often reuse code to deploy their malware, phishing website or CNC server. As a result, similiaries can be found on URLs path by inspecting internet traffic. Moreover, deep learning models or even regular ML model do not fit for inline deployment in terms of running performance. However, regexes ( or YARA rules ) can be deployed on a proxy and work in real time on all the traffic. LUDA can take a set of malicious and benign URLs and return a list of regexes ready to be deployed inline !

ludicrousdb

LudicrousDB is an advanced database interface for WordPress that supports replication, failover, load balancing, & partitioning

ludumdare30

This is the game I created for the Ludum Dare 30 competition

ludwig

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.

ludwig-docs

Ludwig's documentation

luerl

Lua in Erlang

lufa

LUFA - the Lightweight USB Framework for AVRs.

luffa

A gem for testing the Calabash Toolchain

luhn_checksum

Fast implementation of the Luhn checksum algorithm for detecting credit card numbers

luhnybin

luigi

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.