Posts

The blog you’re reading changed builders. The git push that publishes it is identical; what runs on the other end isn’t. It used to be a GitHub Actions job that built the site and served it from yourlocalunemployed.github.io. Now Cloudflare Pages builds from the same repo and serves it at billalrehmani.pages.dev. I didn’t move for speed or for a nicer dashboard. I moved because GitHub Pages won’t let me set HTTP response headers, and for a blog that’s meant to be a security portfolio, that was the one limit I couldn’t design around. ...

A flat network trusts every device on it equally. A smart plug, a guest’s phone, and the machine holding my important data all share one space — so if any one of them is compromised, the attacker can reach the rest. Network segmentation breaks that flat space into separate zones and controls what may cross between them, shrinking the blast radius of any single compromise. I wanted to build that properly — VLANs and a firewall — on VMware Workstation with pfSense CE, and design three zones at deliberately different trust levels: ...

My lab is deliberately isolated — an automation VM (CLAUDDEB) sits behind a virtual pfSense firewall on a segment (10.10.0.0/24) that my home network can’t reach. That isolation is great until you’re out of the house and want to check your Grafana dashboards, which only listen inside that segment. I already use Tailscale for casual remote access, and I’ll be honest up front: for pure convenience, Tailscale wins — it punches through NAT automatically with zero firewall work. But this project wasn’t about convenience. It was about building the thing Tailscale is made of. Tailscale is WireGuard under the hood; hand-rolling raw WireGuard on pfSense teaches you how VPNs actually work — keys, peers, routing, firewall rules, NAT — at a level the managed tool deliberately hides. So I built it from scratch, kept Tailscale as my daily driver, and got a genuinely brutal debugging lesson in the process. ...

My Debian automation VM already sits behind a pfSense firewall with egress containment — it can reach the internet but not my home network. So why harden the VM itself? Because “behind a firewall” is doing less work than it sounds. Two paths reach into the VM without ever crossing pfSense, and an honest audit of my own box turned up drift I didn’t expect. This is the write-up: what the audit found, what I changed, and the systemd sandbox mistake that quietly broke a service. ...

I run Claude Code on two machines: the Debian VM in my home lab (always on) and a Debian laptop (sleeps, roams, follows me to campus). I wanted the laptop to push notes, facts, and findings into a central store on the VM — from any network — so the home-lab agent could pick them up later. Claude Code’s built-in Remote Control turns a second device into a remote window onto one session. That’s not what I wanted. I wanted both machines to stay fully independent agents, linked through a shared tool. So I built a small MCP server on the VM and pointed the laptop’s Claude Code at it: the hub becomes just another tool the laptop can call. ...

My LaMetric display gives an at-a-glance read on the lab, but it’s a spot reading with no history — good for “is something on fire right now,” useless for “what happened overnight.” This project adds the layer underneath: a Prometheus + Grafana stack that scrapes my hosts continuously, stores the history, and draws real dashboards. Two targets: CLAUDDEB (my Debian automation VM) and my pfSense firewall, reusing the exact SNMP setup from the pfSense post — just pointed at something far more capable than a 37-pixel display. ...

In part 1 I got a LaMetric Time showing live health from my home lab over MQTT, so it worked across my network isolation — CPU, memory, disk, uptime, and the automation VM’s own traffic, all from a single Debian box. Useful, but those were really that box’s stats. The frame the display was named for is my network’s throughput — the traffic crossing my firewall — and that data lives on pfSense, not the Debian box. This is the follow-up: pulling real WAN in/out rates off pfSense over SNMP and putting them on the display. It’s shorter than the MQTT build, because the pipeline already exists; all I’m adding is a new data source. Getting numbers out of pfSense is the part worth writing down. ...

I picked up a LaMetric Time — an 8x37 pixel smart display — and after locking it down on an isolated guest network, the next move was to make it useful: live health from my home lab. CPU, memory, network throughput — the numbers worth a glance. The interesting part is that a constraint I’d deliberately built into my network dictated the whole architecture. This is the write-up: the design decision, the pipeline, and the gotchas — because the gotchas are the useful part. ...

This is my second SPT mod port — the first was BiggerBang, a full trader mod. This one is smaller in scope, but I ran the entire process through Claude Fable 5 in Claude Code: extraction, code review, the rewrite, and the debugging. My role was direction and judgement calls; the model did the implementation. The most interesting part of this post is what it found. ...

I wanted a small desktop tool that captures a snapshot of a machine — hardware, resource usage, network state — and writes it to a styled HTML report viewable in any browser. Useful for quick system audits and for keeping a record of a machine’s specs over time. I built it in one Claude Code session (Opus 4.8) on my Debian 13 laptop, then packaged it for Windows as well. ...