The Infection-Monkey team for GSoC 2018 wrote this post as a project summary of their GSoC 2018 experience

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Abhinav Saxena wrote this post as a project summary of his GSoC2018 experience.

After successfully participating in GSoC between 2009 and 2017, 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 2018. Read more »

The Honeynet Project annual workshop is just few days away, members and security folks from all over the world will gather in Canberra, Australia November 15th-17th. Every year the Honeynet Project, with the support of Google, funds a bunch of students that were admitted to the Google Summer of Code program and successfully completed their project assignments. They will have a chance to travel to the workshop and meet face to face with honeynet members and grown up experts in the security field. Read more »

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 »