Machine Learning, Python, Slips, Stratosphere Linux IPS
Stratosphere IPS
HTTPS Anomaly Detection in Slips: Adaptive ...

The new HTTPS anomaly detection module in Slips builds per-host adaptive baselines in traffic time, then detects deviations at two levels: per-flow (for bytes to known servers) and per-hour (for host behavior like new servers, unique servers, JA3 changes, and flow volume). It uses online statistics and z-scores for transparent scoring, plus controlled adaptation states (training_fit, drift_update, suspicious_update) to keep learning while reducing poisoning risk.
The result is explainable, operational evidence in clear human text: what changed, confidence, and why it is anomalous.

HTTPS Anomaly Detection in Slips: Adaptive Baselines for Real Traffic
Education, publications, Python, Slips, Stratosphere Linux IPS
Stratosphere IPS
Rethinking Cybersecurity Defense: Principles ...

Our research identifies sixteen fundamental principles of biological immunity and translates them into cybersecurity defense architectures that emphasize multi-dimensional coordination over single- point tactics.

Rethinking Cybersecurity Defense: Principles from Biological Immunity
Maria Rigaki
AI Attackers in Your Pocket: How Small Language ...

We are pleased to announce the publication of our latest paper, “Building adaptive and transparent cyber agents with local language models,” in the Journal of Expert Systems with Applications.

Slips
Stratosphere IPS
How Well Do LLMs Perform on a Raspberry Pi 5?

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.

How Well Do LLMs Perform on a Raspberry Pi 5?
Stratosphere IPS
Introducing ARACNE, a new LLM-based shell ...

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.

Introducing ARACNE, a new LLM-based shell pentesting agent

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HTTPS Anomaly Detection in Slips: Adaptive Baselines for Real Traffic

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HTTPS Anomaly Detection in Slips: Adaptive Baselines for Real Traffic

The new HTTPS anomaly detection module in Slips builds per-host adaptive baselines in traffic time, then detects deviations at two levels: per-flow (for bytes to known servers) and per-hour (for host behavior like new servers, unique servers, JA3 changes, and flow volume). It uses online statistics and z-scores for transparent scoring, plus controlled adaptation states (training_fit, drift_update, suspicious_update) to keep learning while reducing poisoning risk.
The result is explainable, operational evidence in clear human text: what changed, confidence, and why it is anomalous.

Installing and Running Slips in Docker

Installing and Running Slips in Docker

The Stratosphere Linux IPs, for short Slips, is a free software intrusion prevention system that uses machine learning. Slips allows analysts to quickly sift through large network captures as well as real live traffic, highlighting what is important to analyze. The analysis we do as part of the Emergency VPN service at Civilsphere relies heavily on Slips.

Protecting the civil society through high quality research