The summer is coming to the end as well as my GSoC17 happy days. So, now it’s time to sum up the results and say goodbye to the GSoC until the next year.

My impressions about working on the Heralding project

Working on the Heralding project was awesome experience for me. I feel I did something helpful, fun and challenging at the same time. I hadn’t wanted anything else before the summer! Read more »

Hi, I’m Matthew Shao from China. This year, I got the honor to be selected as a Google Summer of Code student for the mitmproxy project. With the help of my kindly mentors Maximilian Hils and Clemens Brunner, I managed to improve the source code of mitmweb, which is a web interface for mitmproxy, and added some exciting new features for it. Here I’m going to present you the work I’ve done during this fulfilling summer. Read more »

At the end of February we were very happy to announce that The Honeynet Project had once again been selected to be a mentoring organization for Google Summer of Code (GSoC) 2017. Since then, there has a been a flurry of activity: We received more than 50 project proposals during the application phase, selected 14 fantastic students, set them up to work with us during the community bonding period, and now completed the first month of actual work! Now that the first tangible results are tickling in, it’s time to take a closer look at our students and see what they have achieved so far. Read more »

With Google Summer of Code (GSoC) 2017 being around the corner, we’d like to do a short flashback to 2016, our most successful GSoC year for mitmproxy so far! GSoC 2016 was mitmproxy’s fourth time participating in the program under the umbrella of the Honeynet Project. For the first time, we were able to mentor three students over the summer to work on both our Python core and the brand new web interface. As a major milestone, mitmproxy is now a Python 3 project and has a fantastic user interface that even works on Windows. Read more »

After successfully participating in GSoC between 2009 and 2016, and having created or extended many honeynet technologies that have since gone on to become industry standard tools, we are very happy to annouce that The Honeynet Project has applied to be a mentoring organization once again in GSoC 2017. Read more »

CuckooML is a GSOC 2016 project by Kacper Sokol that aims to deliver the possibility to find similarities between malware samples based on static and dynamic analysis features of binaries submitted to Cuckoo Sandbox. By using anomaly detection techniques, such mechanism is able to cluster and identify new types of malware and can constitute an invaluable tool for security researchers.

It's all about data..

Malware datasets tend to be relatively large and sparse. They are mostly made of categorical and string data, hence there is a strong need for good feature extraction approaches to obtain numerical vectors that can be feed into machine learning algorithms [e.g. Back to the Future: Malware Detection with Temporally Consistent Labels; Miller B., et al.]. Another common problem is concept drift, the continuous variation of malware statistical properties caused by never ending arms race between malware and antivirus developers. Unfortunately, this makes fitting the clusters even harder and requires the chosen approach to be either easy to re-train or be adaptable to the drift, with the latter option being more desirable. Read more »

At the end of February we were very happy to announce that The Honeynet Project had once again been selected to be a mentoring organization in Google Summer of Code (GSoC) 2016. Read more »

As I blogged two weeks ago, after some great student projects between 2009 and 2015, The Honeynet Project had applied again this year to be a mentoring organization in Google Summer of Code (GSoC) 2016. Read more »

Hi there, my name is Li Yuanchun and I'm glad to introduce DroidBot, a tool to improve the coverage of dynamic analysis.
As it is the case for malware targeting the desktop, static and dynamic analysis are also used for detection of Android malware. However, existing static analysis tools such as FlowDroid or DroidSafe lack accuracy because of specific characteristics of the Android framework like ICC (Inter-Component Communication), dynamic loading, alias, etc.  While dynamic analysis is more reliable because it executes the target app in a real Android environment and monitors the behaviors during runtime, its effectiveness relays on the amount of code it is able to execute, this is, its *coverage*. Because some malicious behaviors only appear at certain states, the more states covered, the more malicious behaviors detected. The goal of DroidBot is to help achieving a higher coverage in automated dynamic analysis. In particular, DroidBox works like a robot interacting with the target app and tries to trigger as many malicious behaviors as possible.
The Android official tool for this kind of analysis used to be  Monkey, which behaves similarly by generating pseudo-random streams of user events like clicks,touches, or gestures, as well as a number of system-level events. However, Monkey interacts with an Android app pretty much like its name indicates and lacks any context or semantics of the views (icons, buttons, etc.) in each app. Read more »

What is dpkt?

dpkt is a Python library that helps with "fast, simple packet creation/parsing, with definitions for the basic TCP/IP protocols". It supports a lot of protocols (currently about 63) and has been increasingly used in a lot of network security projects. It is 44x faster than Scapy2, and 5x faster than Impacket3. With Scapy no longer in development, dpkt is the only network creation/parsing library for Python that is active. Read more »