I've been writing about cybersecurity, offensive security, AI in pentesting, and tooling for a while — and there's a lot more I can share. Rather than guess what's most useful, I'd like to hear from you.

Why I'm Asking

I have deep experience in red teaming, penetration testing, malware analysis, automation, and AI-driven security . That covers a wide range of topics. I could keep picking subjects on my own, but I'd rather focus on what you actually need: the guides that would help you most, the areas that feel unclear or undercovered, and the depth you want (quick tips vs. step-by-step labs vs. deep dives).

So: what do you want to read?

How You Can Tell Me

  • Comment below — Drop a line with the topic, area, or type of guide you'd like (e.g. "AD attacks," "API security," "AI + Burp," "beginner-friendly Nmap," "full lab walkthrough").
  • Send me a private email — If you prefer not to comment in public, email me directly. I read everything and take suggestions seriously.

There are no "wrong" answers. Whether it's basics or advanced, a specific tool, a methodology, or a use case (e.g. "how I'd approach a cloud pentest"), your input helps me choose what to write next.

What I Can Cover (Just a Sampling)

To give you ideas (or to point at something close to what you want), here are areas I can write about:

  • Offensive security & red team — TTPs, attack chains, AD, lateral movement, reporting.
  • Penetration testing — Web, network, cloud (AWS/Azure/GCP), wireless, methodology from recon to report.
  • Threat hunting — Hypothesis-driven hunts, pivoting methods, baselining, anomaly detection, and how to turn hunts into repeatable playbooks.
  • Detection engineering & monitoring — Writing detections, reducing false positives, alert tuning, dashboards, SLIs/SLOs for security, and "detection-as-code" workflows.
  • Blue team telemetry & log strategy — What to log (Windows/Linux/K8s/cloud), collection architecture, normalization, enrichment, and retention strategy that actually supports investigations.
  • Detection content for real platforms — Practical detection rules, parsing, and enrichment examples for SIEM / log platforms (plus how to validate detections with test data).
  • Environment & lab building — Designing reproducible labs for offensive + defensive research: AD labs, cloud labs, Kubernetes labs, and realistic traffic/log generation.
  • Attack simulation for validation (purple-team style) — Running controlled simulations to prove detections: mapping behaviors to MITRE, generating evidence, and measuring coverage.
  • Monitoring pipelines & automation — Fluent Bit/agents, log shipping, parsing, correlation, alert routing, and automated enrichment (IP/ASN/Geo, threat intel, asset context).
  • Tools — Nmap, Burp Suite, Metasploit, Hashcat, John, BloodHound, C2, and many others — with or without AI/MCP.
  • AI in security — LLMs for analysis, MCP, HexStrike-AI, Cursor workflows, automation ideas.
  • Malware analysis & reverse engineering — Static/dynamic analysis, tools, workflow.
  • Forensics — Memory, disk, logs, timelines, tooling and process.
  • Automation & scripting — Python, Bash, integration with security tools, small utilities.
  • Career & learning — How to get started, what to learn first, certs, building a lab.

If what you want isn't in this list, that's fine — tell me anyway. If you already have a rough title or a specific scenario ("e.g. I want a guide on X for people who know Y"), even better.

What Happens Next

I'll go through every comment and email, note the most requested topics and themes, and plan future articles and guides accordingly. You won't get a personal reply to every message, but your input will directly influence what I publish.

So: comment below or send me a private email with the guides and areas you want. I'm looking forward to your ideas.

You can comment on this post or reach me by private email. Thank you for reading and for your feedback.