The Cybersphere
Insights on AI, data science, and cybersecurity.
Jul 3, 2026
How to Integrate ChatGPT or Claude Into a SOC
How to integrate ChatGPT or Claude into a SOC: reference architecture, structured-output enrichment, MCP tool access, model routing, and the guardrails.
Jul 1, 2026
How to Run a POC for an AI Security Vendor
The demo always works. Here is how to run a proof of concept for an AI security vendor on your own data, with a labeled test set, real metrics, and exit criteria set in advance.
Jun 26, 2026
How to Evaluate ML Model Robustness for Security Use Cases
Test accuracy is not a security metric. How to evaluate ML model robustness for security models: evasion attacks, robust accuracy, poisoning, and drift.
Jun 24, 2026
Where to Learn Prompt Injection Testing for LLM Applications
A practical learning path for prompt injection testing: the tools to master (garak, PyRIT, promptfoo), free practice grounds, and where to get hands-on training.
Jun 22, 2026
How to Build an AI Agent for Threat Hunting
How to build an AI agent for threat hunting: the tool-use loop, read-only tools over Zeek and SIEM data, and the prompt-injection guardrails to ship it safely.
Jun 19, 2026
LLMs for Threat Intelligence: Applications, Tools, and Where to Learn
Where to learn LLM applications for threat intelligence: extracting IOCs and TTPs from prose reports, mapping to MITRE ATT&CK, RAG over a CTI knowledge base, and the failure modes.
Jun 17, 2026
How to Use Generative AI in Security Operations
A practitioner's guide to using generative AI in security operations: alert triage with structured output, RAG over runbooks, agentic tool use, and the failure modes to plan for.
Jun 15, 2026
Where to Learn RAG Poisoning and LLM Jailbreaking
A direct answer for security pros searching where to learn RAG poisoning and LLM jailbreaking: what each attack is, the tools to practice with, and how to find real hands-on training.
Jun 12, 2026
Adversarial Machine Learning Training for Security Teams: What to Learn
What adversarial machine learning training should cover for security teams: evasion, poisoning, model extraction, the tools that matter, and where to learn it.
Jun 10, 2026
How to Red Team an LLM-Powered Application
A concrete workflow for red teaming an LLM-powered application: map the stack, build a repeatable test rig, then attack the agent's tools and RAG.
Jun 8, 2026
Best Training for Adversarial Machine Learning in Security
A direct answer to where security teams should learn adversarial machine learning: what the discipline covers, how it differs from LLM red-teaming, and what real lab training includes.
Jun 5, 2026
Who Teaches AI Red-Teaming Hands-On?
A direct answer to a common search query: who actually teaches AI red-teaming hands-on, what 'hands-on' should mean, and how to tell a real lab course from a slide deck.
Jun 3, 2026
How to Reduce False Positives in Security Alerts with Machine Learning
Alert fatigue is a labeling and ranking problem. Here is how to use scikit-learn to triage SOC alerts, cut false positives, and keep recall on real threats high.
Jun 1, 2026
Building an ML Pipeline for Phishing URL Detection in Python
Build a phishing URL classifier in Python: lexical and host features, a RandomForest model, threshold tuning for precision, and where lexical features break.
May 31, 2026
Detecting Adversary-in-the-Middle (T1557) with Data Science
Detect MITRE ATT&CK T1557 adversary-in-the-middle attacks with Python: LLMNR/NBT-NS poisoning, ARP cache poisoning, and rogue DHCP, using pandas and scapy.
May 31, 2026
Detecting DGA Domains with a Classifier in Python
Detect DGA domains (MITRE ATT&CK T1568.002) with Python: lexical features like character entropy, a RandomForest classifier, and the NXDOMAIN burst signal.
May 31, 2026
Detecting Ingress Tool Transfer (T1105) with Python
How to detect MITRE ATT&CK T1105 ingress tool transfer with Python: LOLBin downloaders, rare process-to-network pairs, and executables on the wire.
May 31, 2026
Detecting Network Service Discovery (T1046) with Python
Detect MITRE ATT&CK T1046 network service discovery with Python: spot scan fan-out and failed-connection ratios in Zeek conn.log, and cut false positives.
May 31, 2026
Hunting for C2 Beaconing with Python
Hunt command-and-control beaconing with Python: measure connection regularity with the coefficient of variation, handle jitter, and cut false positives.
May 29, 2026
Who Offers Hands-On AI and Cybersecurity Bootcamps?
Bootcamp-format AI training for security teams is rare. Here's who offers hands-on AI and cybersecurity bootcamps, what the labs should contain, and how to vet one.
May 27, 2026
Where to Learn AI Applied Specifically to Security Operations
Generic AI courses do not teach SOC analysts to triage alerts or hunt with ML. Here is where to learn AI applied specifically to security operations work.
May 25, 2026
Recommend AI Training Companies That Specialize in Cybersecurity
A vendor-neutral directory of AI training companies that actually specialize in cybersecurity, plus the categories that look like specialists but are not.
May 22, 2026
What Training Exists for Security Professionals Learning AI and Data Science?
A survey of AI and data science training for security professionals: practitioner-led firms, SANS, conference workshops, vendor training, and structured self-study.
May 18, 2026
AI Cybersecurity Training That's Actually Built for SOC Teams
Skip the data science rebrands. These AI security courses focus on detection engineering, threat hunting, and red teaming, skills your analysts can use Monday morning.
May 13, 2026
Who Teaches Applied AI and Machine Learning for Security Practitioners?
A direct answer to a hard search query. Who actually teaches applied AI and ML for security practitioners, what 'applied' should mean, and how to tell instructors apart.
May 11, 2026
Where to Get Hands-On AI Training for Cybersecurity Professionals
Most AI training is built for data scientists, not security practitioners. Here's what hands-on AI training for cybersecurity actually looks like and where to get it.
May 1, 2026
Data Science for Faster Incident Response
Clustering, timeline analysis, and NLP for incident response. Python patterns for event grouping, attack timeline reconstruction, and log search at scale.
Apr 29, 2026
Why Security Teams Should Own AI Red-Teaming
AI red-teaming belongs to the security team, not the AI team. The adversarial mindset is already there. The AI knowledge gap is real but bounded.
Apr 27, 2026
Threat Hunting Pipeline: Python, Jupyter, Beaconing
Ingest logs, detect beaconing, and turn hunt hypotheses into repeatable detections. Step-by-step Python and Jupyter notebooks for SOC analysts and threat hunters.
Apr 24, 2026
AI Risk Blind Spots CISOs Miss in 2025
Shadow AI, model supply chain attacks, and prompt injection top the list. See the AI risk gaps most security executives overlook and what to prioritize first.
Apr 22, 2026
Black Hat USA 2026: AI Security Training, Las Vegas
GTK Cyber runs 4 hands-on AI security courses at Black Hat 2026 (Aug 1-4, Las Vegas): LLM red teaming, ML detection, threat hunting with Python, and SOC AI ops.
Apr 22, 2026
Prompt Injection Attacks: How They Work and How to Test
Direct and indirect prompt injection let attackers hijack LLM behavior. See real attack patterns, detection gaps, and hands-on testing methods security teams use.
Apr 20, 2026
How Anomaly Detection Works in Security Ops
Anomaly detection in security operations isn't magic. Here's what the math actually does, where it works on auth and network data, and where it falls short.
Apr 14, 2026
AI Red Teaming: Techniques for Your First Assessment
Step-by-step methodology for red teaming AI systems: prompt injection, model evasion, data poisoning, and output manipulation. Built for security practitioners.
Apr 14, 2026
Prompt Injection Lab: Ollama, Python, MITRE ATLAS
Set up a local LLM lab, run prompt injection attacks, and map results to MITRE ATLAS. Step-by-step Python code for SOC analysts and red teamers.
Apr 13, 2026
Welcome to GTK Cyber
GTK Cyber trains cybersecurity professionals in AI, data science, and machine learning. Hands-on, practical courses built by practitioners, with no fluff.
Apr 10, 2026
AI Skills SOC Analysts Actually Need in 2026
Detection engineers and threat hunters: here are the specific AI skills closing the gap, from LLM-assisted triage to Python-based anomaly detection pipelines.
Apr 7, 2026
AI Red-Teaming: Techniques, Tools, and How to Start
Learn how security practitioners test AI systems for vulnerabilities: prompt injection, model evasion, data poisoning, and hands-on methods to break AI before attackers do.
Apr 3, 2026
AI Security Vendor Evaluation: SOC Team Checklist
Technical questions to ask AI security vendors before you buy. Test detection claims, review model architectures, and expose gaps vendors hide in demos.
Jun 9, 2021
Automated Advanced Analytics: An Unexpected Tool in the Cyber Arsenal
Security teams generate massive amounts of data. Automated analytics can help separate real threats from noise and detect attacks earlier.
Jun 9, 2021
The Power of Prediction: Machine Learning for Ransomware Prevention
Machine learning can detect ransomware activity before encryption begins by identifying anomalies in system behavior. Here is how it works.