endeavormac

Recently I found myself coming across numerous WPA-PSK encrypted wireless APs, with a desire to access them. I think it’s safe to say we all know about the WPA CoWPAtty tables, but these APs did not have names that were in the tables. To make matters worse, at the time the only available hardware I had available was my netbook, and I was attempting ~280 keys a second. With my massive dictionaries with millions and millions of real-world passwords to attempt, it was going to take hours for each AP.

I decided I needed to order my password dictionaries in a manner that would bring the more likely passwords to the beginning, and the least likely passwords to the end. I wasn’t aware of any program that did this, and figured I would write my own.

A few hundred lines of C later and I have a very fast password dictionary ordering program. It is far from perfect, but much better than nothing. It loads the entire dictionary into memory, creates all the information necessary for markov chains, and then uses this information to score each individual password. The passwords are then ordered by their score.

You can find the code in the rainbowsandpwnies googlecode svn repo.

Only about 1/4 of my projects ever make it to any sort of announcement or release. Usually, those releases are silent through svn somewhere. However, I’ve finally reached the time to take a look at the stock market, and have figured, naturally, my best bet is with tech stocks.

In any case, I thought tonight would be a good chance to share one of those many projects that never see foreign eyes. I thereby present you with my custom spin on what a tech stock tracker should look like. I’m not trading minute to minute, or hour to hour, so I don’t care about real-time stock quotes. What I do care about are new announcements that may tip a stock one way or the other, or stocks that look like they may be headed towards rapid change.

Right now, you’re looking a few hours in python, on a 10 minute cron. It grabs information, parses it, and generates static html. I have plans yet to continue to improve this project. More specifically, I’d like to delve deeper into the news articles, counting keywords that may indicate the direction a stock is about to head. I also planning on grabbing historical stock information and running some regression stats in an attempt to automate finding what stocks are very closely related to one another. If stocks A, B and C are all closely related, and news indicates good things for A and B, good things are most likely in store for C.