Can a Raspberry Pi 5 run Large Language Models? In this post, we share the results of our experiments, analyzing how LLMs perform on this low-cost hardware and exploring the challenges and performance trade-offs.
The complete automation of cyber-attacks has become one of the areas of greatest interest since the introduction of Large Language Models (LLMs) to the public. The creation of attacking LLM agents that can act independently is among the most popular options.
In this blog, we introduce a brand-new agent: ARACNE. We also share the results of attack tests and what they mean in terms of the agent’s current capabilities.
We are thrilled to announce that, for the first time, the Czech Technical University in Prague is offering the "Introduction to Security" course as a Massive Open Online Course!
This blog covers my ongoing GSoC project 2024. It provides information about the current progress of my work, as well as my experiences and lessons learned along the way.
In this blog we will describe how to install h0neytr4p [1] honeypot in a cloud server instance. This blog is divided in three parts: (i) how to create a new Digital Ocean instance, (ii) how to install h0neytr4p on it, and (iii) a brief walkthrough to some of the data captured by h0neytr4p.
We are happy to announce that Slips will be presented at BlackHat USA 2022 Arsenal in Las Vegas on Thursday, August 11, from 1:00 pm to 2:30 pm: https://bit.ly/SlipsBHUSA22.
Slips is a machine learning-based intrusion prevention system for Linux and MacOS, developed at the Stratosphere Laboratories from the Czech Technical University in Prague. Slips reads network traffic flows from several sources, applies multiple detections (including machine learning detections) and detects infected computers and attackers in the network. It is easy to extend the functionality of Slips by writing a new module. This blog shows how to create a new module for Slips from scratch.
In this blog we will describe how to install Glutton [1] honeypot in a cloud server instance. This blog is divided in three parts: (i) how to create a new Digital Ocean instance, (ii) how to install Glutton on it, and (iii) a walkthrough to some of the data captured by Glutton.
New Slips version 0.8.4 is here! Our team is excited to share the latest news and features of Slips, our behavioral-based machine learning intrusion detection system.
In the Stratosphere Laboratory we set out to address this challenge of detecting if a news article is propaganda by leveraging a new idea: find which other sites are linking/referencing the news article. In this blog post, we will show how we accomplished this by using SerpApi.
In the last couple of months we have been busy continuing with the development of Slips, our behaviour machine learning system. And finally we published version 0.8, with crazy amount of features! You can download it from here https://github.com/stratosphereips/StratosphereLinuxIPS. And read the documentation here https://stratospherelinuxips.readthedocs.io/en/develop/.
This is the eighth blog of a series analyzing the network traffic of Android RATs from our Android Mischief Dataset [more information here], a dataset of network traffic from Android phones infected with Remote Access Trojans (RAT). In this blog post we provide the analysis of the network traffic of the RAT06-Saefko [download here]. The previous blogs analyzed Android Tester RAT, DroidJack RAT, SpyMax RAT, AndroRAT, HawkShaw, AhMyth and Command-line AndroRAT.
This is the seventh blog of a series analyzing the network traffic of Android RATs from our Android Mischief Dataset [more information here], a dataset of network traffic from Android phones infected with Remote Access Trojans (RAT). In this blog post we provide the analysis of the network traffic of the RAT08-command-line-AndroRAT [download here]. The previous blogs analyzed Android Tester RAT, DroidJak RAT, AndroRAT RAT, SpyMax RAT, AhMyth RAT and HawkShaw RAT.
