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AI in training and learning: the next experiment

Cue the track, because 🎵 it's been a while 🎵 The 'ol blog may have gathered dust, but the mouse and keyboard did not. Life has been full of changes and challenges over the last couple of years, but one thing that has remained is my commi…

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Cue the track, because 🎵 it's been a while 🎵



The 'ol blog may have gathered dust, but the mouse and keyboard did not. Life has been full of changes and challenges over the last couple of years, but one thing that has remained is my commitment to exploring the future of learning and training. What was once the future is....still, in very many ways "the future" as the vicious enemy of "reactive training" still very much persists. At this point, we may as well add it to the list of certainties in life alongside death and taxes, because as much sense as it makes to try and get ahead of your training or learning needs, it's far more common to not realize what you need until you end up realizing you needed it.



In my 10+ years now of trying to understand and support training initiatives, I have seen this problem with EVERY business I have worked with, regardless of the sector they are in. Sales are down? Time to train the sales team! Glassdoor says your company culture stinks? Let's do some ultra fun games in our training! Let's select images and colors that give less "corporate" and more "L-I-V-I-N". These decisions are often made with good intentions, but to move away from reactive training, you have to create a culture of continuous improvement. This is not the simplest task, and to be honest, most of the businesses I have worked with never had the team or resources required to pull it off on their own.



Enter AI. A tool that can truly empower small teams to do much bigger things, and an area that has tremendous crossover for those in learning and development right now. Every business, every team is trying to understand how to best use AI, and I feel like L&D/Training is the absolute epicenter of this convergence - because not only is AI going to be able to help you and your team, but you are also going to be vital to the adoption of any AI tools - so, as they say, "the more you know 🌠".



Over the coming weeks and months, I'm going to be sharing about the AI-integrated tools I am building, and many of them will be free to use for anyone interested. The focus is on empowering those smaller teams, or those teams with skill limitations to still create powerful and effective lessons, courses, programs - whatever it is you teach or train! Follow me to to follow this journey - it's going to be a fun one!

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - AI in training and learning: the next experiment
id: 69a4cf10-465b-4ca8-97fc-6ff5c792a7ab
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-26
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-26"
        description = "YARA Signature for "
    strings:
        $str = "AI in training and learning: t" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("AI in training and learning the next exp")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*AI in training and learning the next exp*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "AI in training and learning the next exp"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

CTI Threat Relationship Graph2 Knoten / 1 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich AI in training and learning: the next ex.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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