$21 raised out of $64,943

This is a revolution in home network security.


The internet has ushered in a new era, and in too many ways to count, it has made our lives smoother, easier, and more modern. There is another side to this, though: by and large, the internet connections in our homes fall far short of proper safety and security standards. While we go on using all of our smart devices – our phones, our tablets, our laptops, our smart appliances – they remain open to bad actors. Some standard routers are so ineffective at tracking and blocking attacks that they offer almost nothing in the way of security. Even if we are not looking at bad actors specifically, tracking is still a major issue – challenging the very idea of privacy as we know it.

Most solutions require, unfortunately, huge amounts of RAM and CPU, which cost a lot of money.

The status quo is simply not good enough. We need to do better.

We have engineered a solution that is going to change the way that people think about home internet security.

It’s called Fengg. Here’s how it works.

Via a groundbreaking intrusion prevention system (working on the BananaPi R2 board), Fengg verifies every network packet that passes through your internet connection. It makes sure that there is no malicious content anywhere in the packets, and if it finds anything, it acts. Every time it does so, it learns from your activity, our machine learning technology adapting to your needs so that it can protect you even more effectively.

That’s not all, either.

Fengg also blocks advertisements and the majority of tracking servers, helping you steer clear of the frustrations that have become a part of everyday life for most internet users. Parental controls and geo-based (location-based) IP filtering both come built into Fengg as well.

You can even take Fengg with you when you travel, connecting your Fengg box via a virtual private network (VPN) for an added layer of protection.

In short, this is the future of home network security. The time is now: we are proud to lead the way there.



Bringing Fengg to Your Home

Fengg will be an open-source system, and by the end of next year, it will be ready for home installations. You can use it as a security gateway or as a router replacement, selecting your settings via a user-friendly portal on your laptop or your phone – or choosing to go with the default, out-of-the-box settings.

Fengg is functional in its prototype version, but to offer it on a large scale, we would like to upgrade it even further.

Our goal is to raise ~65.000 € to cover all of the costs that we are facing as we scale up our operation and distribute Fengg to users worldwide.

To say thanks to everyone who makes this possible, we are offering some limited-edition rewards, including early access to Fengg.

Contribute and claim security for your home network today!

While you’re at it, go ahead and spread the word to all your friends and family. We appreciate your support, both monetary and non-monetary, and we thank you for taking the time to read about our plans.

Thank you.


Nowadays, almost every company buys security software which scans and checks network traffic for security reasons. This can be gateway protection, which uses intrusion prevention, anti-virus and proxy systems or endpoint protection like any regular anti-virus system and computer firewall. Those are sophisticated systems that require a lot of money and previous knowledge due to their complexity and need for maintenance. As a result, such systems are normally not used in smaller households.

But these days the threat does not always come from outside the network. Due to increasing use of IoT (Internet of Things) devices, security threats arise unknowingly within the network itself. Sonicwall is a leading security vendor and according to their threat intelligence data the IoT malware increased in the first three quarters of 2019 by 33 % and caused up to 25 million attacks in the same year.

Therefore, protection for end-users is as important as it has been for companies for a long time.

Still, the problem remains that most security software comes with a price. A security gateway is normally a big server with lots of RAM (Random-access Memory) and CPU (Central Processing Unit) power to meet the needs of heavy computing. This is normally expensive and additionally someone has to maintain and update it frequently. In most cases an expert or administrator is necessary.

That is why the motivation of this project is to create a cost efficient router, which incorporates modern security methods and at the same time, is easy to setup and maintain.


Machine Learning is the study of computer algorithms that improve automatically through experience – Tom Mitchell

ML (Machine learning) is related to statistical computation which tries to predict trends or make decisions. It is important for ML to achieve the goal of making predictions or decisions based on data learned over time without being explicitly programmed.

Fengg is capable to inspect the network and learn from its activity. In case a malicious client is added Fengg can block or warn about it.


To be able to achieve the mentioned goals the router must be capable of reading, inspecting, modifying and dropping network traffic. This requires certain hardware aspects. We use the BananaPi R2 board as our main hardware platform.

BananaPi R2

Whether this receives an upgrade or changes to the better depends on the outcome of this Kickstarter.


The following components require patterns or special rules which needs regular updating to provide full coverage:

  • The classical pattern matching engine which works with regular updated blacklists to detect and prevent known threats.
  • The Intrusion Prevention System (IPS) Snort 

In case of the predefined rules, patterns and other software parts, the product will update itself and its components via a package manager provided by the operating system. In case of the IPS pattern Fengg will use the Cisco community rules unless a subscription is used.


Fengg is a young startup located in Karlsruhe, Germany. We have over ten years of network security experience in the area of intrusion prevention and detection.


This project originated from a thesis which was published publicly.


It implements a detection system of malicious network traffic on an existing hardware platform, which is able to detect certain traffic not only with classical pattern matching, but also with the help of creating intelligent network profiles and identifying network devices. 

Bachelor Thesis: Design and implementation of an intelligent malicious traffic detection system for small hardware