Teaching
Stratosphere IPS
Registrations are OPEN for the “Introduction to ...

Two years ago, we launched the “Introduction to Security” class as a Massive Open Online Course with one ambitious goal: to make high-quality, hands-on cybersecurity education free and accessible worldwide. The response has been really beyond anything we imagined.

Registrations are OPEN for the “Introduction to Security” course 2026.
Slips
Stratosphere IPS
Adaptive Response in Slips IDS as Immune T Cells

The T Cell module was created to give Slips a stateful adaptive response layer on top of its existing evidence pipeline. While the original detectors already provide the innate immune component through PAMP and DAMP evidence, the T Cell module adds antigen recognition, co-stimulation, context evaluation, tolerance, activation, effector action, and memory. It does this by extracting structured antigens from live evidence, matching them against the accepted regex repertoire generated by RegexGenerator, and then combining that recognition with the cumulative danger signaled by recent PAMP and DAMP observations. This allows Slips to move from isolated detections to a more explicit immune decision process that can decide when to ignore, when to contain, and when to remember.

Adaptive Response in Slips IDS as Immune T Cells
Slips
Stratosphere IPS
Adapting Detections in Slips with Immune ...

The RegexGenerator module was created to give Slips an adaptive way to discover new string-based detectors for changing indicators such as domains, URIs, filenames, TLS SNI values, and certificate common names. It continuously uses the shared LLM service to propose one regex at a time, then applies local validation and negative selection against benign corpora to reject unsafe or overly broad patterns. The accepted regexes become a reusable adaptive recognition repertoire for other modules, especially the T Cell responder.

Adapting Detections in Slips with Immune Pseudo-Generated Regexes
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

Introducing Collectress: Consistent Threat Intelligence Feed Collection and Storage

Introducing Collectress: Consistent Threat Intelligence Feed Collection and Storage

This blog introduces Collectress, a new tool developed at the Stratosphere Laboratory. Collectress was born out of the need to have a certain feed for 30 days or 300 days to evaluate the feeds over time and make a reasonable comparison among feeds. 

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Slips and the AI VPN presented at the 20th DIMVA Tool Arsenal in Hamburg, Germany

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Slips and the AI VPN presented at the 20th DIMVA Tool Arsenal in Hamburg, Germany

The Stratosphere Laboratory focus on applied research at the intersection of machine learning, cybersecurity and helping others. As part of our research and social commitment we develop free software tools that can help the community. In this blog we will recount our experience participating in the 2023 (DIMVA) Tool Arsenal with two of our tools: Slips and the AI VPN.

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Google Summer of Code Updates from Week #4 (June 19th to June 23th)

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Google Summer of Code Updates from Week #4 (June 19th to June 23th)

Week 4 of GSoC is finished, and the work continues. The contributors keep working, and we keep mentoring using a weekly sync-up meeting, Monday for task management and Discord for daily chats.

The World of Malicious IPs: Creating Blocklists from Honeypot Traffic.

The World of Malicious IPs: Creating Blocklists from Honeypot Traffic.

A honeypot network is a security mechanism to detect and deflect potential cyber-attacks. It works by creating a decoy system that appears to be a valuable target for attackers. The honeypot is designed to lure attackers into interacting with it so that security researchers can monitor their activities and learn more about their tactics. By nature, the honeypots are hidden and do not form part of any production system. As they do not receive legitimate connections, all the interactions with the honeypots can be considered attacks.

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Google Summer of Code Updates from Week #3

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Google Summer of Code Updates from Week #3

Week 3 of GSoC finished, and some nice work has been done so far. The contributors keep working after classes, and we are conducting mentorship. The hard part of mentorship is to actually teach to do things in a certain way and not to provide all the answers.

Protecting the civil society through high quality research