Hey, kudos!
You don't run arbitrary scripts either!

My apologies for the JS on this page…
it's prettify.js for syntax highlighting
in code blocks. I've added one line of
CSS for you; the rest of this site
should work fine.

      ♥Ⓐ isis

code.

Defcon Report Back, Part II

Saturday 6^th^ August 2011, Defcon 19, Las Vegas

Smartfuzzing

I missed Smartfuzzing the Web: Carpe Vestra Foramina, by Nathan Hamiel et. al., which I had wanted to attend. I went through the pdf of the presentation just now, and I wouldn’t exactly call it smartfuzzing, but I did note the cleverness of the presenters’ idea to use wordlists comprised of words taken from the robots.txt file of websites for fuzzying purposes. Their new tool, RAFT, is being released soon, though it is currently available as an svn checkout.

Creating Cracks and Keygens for .NET Applications

The first presentation I attended was Hacking .Net Applications by Jon McCoy. He detailed the extensive uses of his GreyWolf and GreyDragon tools, including the production of cracks, keygens, and malware. GreyWolf, which is currently in Beta, is a reverse engineering tool which allows extraction of source code from .dll files, and GreyDragon is a .NET injection tool. It was astounding how little actual security is put into authentication of enterprise applications. The funniest use of GreyDragon was an instance in the demo in which McCoy altered a Boolean string controlling a password check from var a=true to var a!=true, which meant that only wrong passwords would allow access to the program. He was also able to extract source code from .dlls, find the security and authentication mechanisms, and then create a keygen for the demonstrated program – a commercial keylogger – within five minutes.

VoIP Botnetting

The presentation which might possibly rank as the most impressive was Sounds Like Botnet by Itzik Kotler and Iftach Ian Amit, on VoIP botnetting. The idea is that certain networks which do not allow active connections to the outside internet usually do allow VoIP traffic, and these packets are not often paid much attention. Basically, SIP (Session Initiation Protocol) is quite similar to HTTP and has little security built in. SIP supports TSL, but even with this type of encryption enabled the traffic can be easily sniffer. What this means is that SIP traffic can easily transverse firewalls, and SIP-to-PSTN (Public Service Telephony Network, a.k.a. standard telephone lines) can be used to relay commands to botnetted machine within a closed network, or a network which does not allow internet access.

Researchers Kotler and Amit used an Asterisk server hosted in the cloud as the Command-and-Control (C&C). Conference calls were used to link botnetted boxes together and issue commands from the botmaster, which also allows for more anonymous direction of the botnet with conference call bridge numbers. Moshi Moshi, an open source VoIP botnet, was used to communicate with the botnet using Text-to-Speech engines for output to the botmaster and DTMF tones for input. DTMF stands for Dual-Tone Multi-Frequency signalling, and, if you remember the adventures of phreaker Captain Crunch and his 2600Hz whistle tones which allowed for free telephone calls, you’ve basically got the idea. With DTMF, standard keyboard inputs are mapped to certain tonal frequencies, and when a machine with such translation software installed, complete binary files and commands can be sent over the wire through music. Seriously. You make techno music out of a binary file, play it to your zombies, and they execute the binary. Fucking awesome. So, the botmaster calls into the conference call on the server, and receives Text-to-Speech information on the number of machines connected. During the demo, when the presenters called into the Asterisk server, they were greeted with a robotic voice saying, “There are currently two others in this conference room.” Next, they played a .wav file of DTMF tones, and the machines went off to do their bidding.

I really, really, really want Botnet to become a new EBM subgenre. Really badly.


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