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An interesting Tailscale + Docker gotcha

2026-01-29T00:00:00Z

As I’ve written about before, I use Tailscale for a lot of things. I thought I had it set up in a reasonably secure manner, but I recently noticed a problem.

I use Tailscale’s ACLs to limit what each node can access, based on the tags I apply to it. So an app node can’t access anything via Tailscale, while an integration or server node can access things tagged with either app or integration. This is expressed pretty simply in the Tailscale ACL JSON:

{
	"tagOwners": {
		// Servers that can be SSH'd into
		"tag:server": [],
		// Applications that are exposed on tailscale but never connect out
		"tag:app": [],
		// Things which talk to other services over tailscale (connecting to apps etc)
		"tag:integration": [],
	},
	"grants": [
		{
			// Users can access everything
			"src": ["autogroup:member"],
			"dst": ["*"],
			"ip":  ["*"],
		},
		{
			// Servers and integrations can access integrations and apps
			"src": ["tag:server", "tag:integration"],
			"dst": ["tag:integration", "tag:app"],
			"ip":  ["*"],
		},
	],
}

Over the past week I’ve been setting up a private Forgejo instance behind Tailscale, complete with an actions runner that runs things using a docker-in-docker container. I didn’t want the runner knowing anything about Tailscale, so I had it configured to speak to Forgejo direct over HTTP (forgejo:3000) instead of using full Tailscale HTTPS URL that I use when accessing it (http://git.example-net.ts.net/)¹.

Everything was going fine, until I forgot to do that translation… and it worked. My Forgejo action runners could access anything on my tailnet. I run several things on Tailscale that just have authentication turned off, on the basis that only authorised devices can access them. Things like the admin interface for this website. I definitely didn’t intend for any workflow I run on my git server to have access to edit my website!

This wasn’t just limited to Forgejo, either. Any docker container I was running could access the tailnet. In hindsight it’s fairly obvious why: the host is running Tailscale, connected as a node tagged with my server tag. That creates a tailscale0 interface, and automagically sets up iptables rules to route Tailscale traffic over the interface. Docker also automagically sets up iptables rules to bridge traffic, and apparently these two sets of rules interact in such a way that traffic from Docker containers is allowed to route via the tailscale0 interface.

I say it’s fairly obvious in hindsight — there’s no reason why Docker would special case any particular host interface after all — but it still feels pretty surprising. Because both bits of software inject their own iptables rules, I never really had a good mental model for how they interact. The host Tailscale node was a completely separate building block to Docker. It would be a pain to use either of them if they didn’t do these rules, but it’s also one of the reasons I don’t really like “magical” things².

There are lots of ways to fix this, but none of them feel particularly great. You can configure both Tailscale and Docker to not automatically fiddle with iptables and handle the rules yourself, but I really hate dealing with iptables³. As a stopgap I did hold my nose and add some iptables rules to drop traffic to the tailscale0 interface if it originated from the IP ranges that Docker was configured to use:

iptables -I DOCKER-USER -s 192.168.0.0/16 -o tailscale0 -j DROP
iptables -I DOCKER-USER -s 172.17.0.0/12 -o tailscale0 -j DROP

The DOCKER-USER chain is a nice little escape hatch; it comes before the main auto-generated DOCKER chain, and Docker leaves the rules in it alone.

So I added these rules, and felt pretty good about myself, and then… everything started breaking in weird ways. After some debugging I realised the problem was DNS⁴. The server’s DNS resolver is 100.100.100.100, a special Tailscale address. This is so that it can resolve tailnet hostnames via MagicDNS (and so I don’t have to configure my custom DNS servers manually on each device; Tailscale does it for me). My new iptables rules inadvertently dropped all the DNS packets coming from docker containers. D’oh.

Obviously the solution here is to double down and add MORE iptables rules:

iptables -I DOCKER-USER -s 192.168.0.0/16 -d 100.100.100.100 -o tailscale0 -j ACCEPT
iptables -I DOCKER-USER -s 172.17.0.0/12 -d 100.100.100.100 -o tailscale0 -j ACCEPT

This got DNS working again, but it all feels a bit gross. Not least because to actually make these persist you need to use iptables-save, and then you also get all the rules that both Docker and Tailscale have inserted. I came across a script to filter out the Docker ones, but… yuck⁵.

I realised a cleaner idea might just be to lock down what server tagged nodes could access within Tailscale itself. That way I can avoid touching iptables at all. It’s handy to be able to curl services from the host when debugging, but it’s not really necessary. So I removed that access, and… stuff broke again. I’m using my Forgejo instance as a registry for some of the docker images I run, so the docker daemon needs to be able to reach it. I ended up making a new tag for infrastructure, which can be accessed from server devices. This does still allow all the docker containers to reach Forgejo, but I already have it set up with appropriate access controls and public/private repository splits. Forgejo is a service designed to run publicly, so this seems a reasonable trade-off for convenience. I used the tests feature of Tailscale’s ACL config to make sure I’d got the rules right:

{
	"tests": [
		{
			// Servers can only access infrastructure
			"src":   "tag:server",
			"proto": "tcp",
			"allow": [
				"tag:infrastructure:8080",
			],
			"deny": [
				"100.84.16.43:8080",
				"me@example.com:8080",
				"tag:server:8080",
				"tag:app:8080",
				"tag:integration:8080",
			],
		},
	],
}

The whole situation still feels a bit messy. If I ever get around to switching to nftables I might loop back and manually craft some rules for routing traffic, instead of leaving Tailscale and Docker to do their own thing.

I discovered later on that logging into the container registry at forgejo:3000 actually issued a redirect to https://git.example-net.ts.net/ so this was all basically for naught… ↩︎
I didn’t use Tailscale’s MagicDNS for a long time just because the word “magic” put me off. Only when I eventually got around to learning how it worked, and seeing that it wasn’t really that magical under the hood, did I change my mind. ↩︎
nftables seems far better in lots of ways, but I can’t really be bothered migrating. Maybe next time I reimage the server for whatever reason… ↩︎
It’s always DNS… ↩︎
Again, nftables would almost certainly help here. It actually has (gasp) configuration files. But again, I really didn’t want to spend the time migrating. ↩︎

10 Weeks with an Apple Watch 10

2025-09-09T00:00:00Z

My watch. Yes, I am available for wrist modelling opportunities.

Around ten weeks ago¹ I picked up an Apple Watch 10, and have been wearing it almost constantly since. It’s not my first Apple Watch — I had a Series 5 for a bit back in 2020 — but it’s the first time I’ve actually stuck with it. Ten weeks seems like an apt time to reflect on it.

Firstly, why did I even bother? Well, for a couple of years I’d been wearing a Xiaomi Smart Band 7, mainly to monitor my sleep stats and set alarms that won’t wake up everyone else nearby. Its battery life was fantastic — with notifications and other things turned off, I got about a month of use between charges — but actually using it felt like trying to order food via the medium of interpretive dance.

My biggest gripe was the screen lock. If I didn’t have the screen locked then I’d periodically trigger it during the night when I moved around and it came in contact with my chest or leg. With the lock enabled you had to deliberately swipe up from bottom to top to enable interaction, but it didn’t work reliably. When I wanted to adjust an alarm, I’d be stood swiping repeatedly trying to get it to respond. When you finally get it unlocked, the whole interface is just fiddly.

The other issue was the data quality. There were some nights when I’d been woken up, sometimes even getting up and moving around, and it just didn’t show it in the data. If it can’t even get whether I’m asleep right, can I trust anything else it says?

I spent a while researching the best devices for sleep tracking. The Oura ring came highly recommended, but it was expensive and required a subscription to do anything useful. No thanks! The Apple Watch was consistently rated pretty well, and I reasoned I could pick up a refurbished older unit. I’ve been using an iPhone as my daily driver for a while, so it’d fit right into my begrudged walled garden.

The Series 10 has a significant advantage, though: it charges much quicker than all the previous generations. On a 30-minute charge, the Series 10 can go from 0 to 60%; the 9 can only make it to 40%, and my old 5 a measly 30%. Shorter charge times means I’m far less likely to leave it on charge and wander off without it. In some ways the daily charging is more convenient than monthly: the wireless charger sits on my desk, and I plop the watch on it for a little while in the evening; I don’t need to dig out the weird pogo-pin connector that has vanished sometime in the last four weeks, then carefully arrange it so it stays attached.

How a watch maybe saved my life

One of the big features of the Apple Watch, like many other wearable devices, is health and fitness tracking. I didn’t think much about this, beyond the sleep data I wanted, at first. I’ve never had a particularly good relationship with exercise², but I do like some good statistics. I started going for walks more often to get more data and see the graphs of VO2 max and HR recovery gradually inch up. That wasn’t the most profound effect on my health, though…

The recent versions of the Apple Watch have a feature that monitors for sleep apnea, a disorder where you don’t breathe properly during your sleep. I knew I wasn’t sleeping great — that’s why I was paying attention to sleep tracking data — but was still a bit surprised to get a notification from Apple Health after wearing the watch for 30 days. It gives you a graph to print and take to your doctor. So I diligently booked an appointment and a few weeks later went to see my GP.

The appointment went about as you’d expect: talking about referral to a sleep centre for a study, and so on. Towards the end, the doctor took my blood pressure (sleep apnea can be caused by, and can cause high blood pressure, in a lovely little vicious cycle). I don’t think either of us expected anything; it was just one of those standard checks for a related problem. After taking the reading, the doctor looked at me and said, “I can’t let you leave with a BP like this”. Yikes!

Blood pressure readings are split into stages: normal is under 120 mmHg³ over 80 mmHg⁴, stage 1 is up to 140/90, stage 2 is up to 180/120, and above is simply called “crisis”. Guess where I was? Also, fun fact: depending on how exactly you count and attribute things, hypertension comes out as the single largest cause of death in humans. It doesn’t kill you outright, but contributes to strokes, coronary artery disease, heart failure, and lots of other lovely things you don’t want on your CV.

After doing a few more readings, it settled down to just under the “crisis” stage and into the “holy crap, start treatment immediately” stage instead. I won’t labour on much more about this, but things are definitely moving in the right direction now⁵.

While the Apple Watch didn’t literally save my life, it triggered the chain of events that led to this diagnosis and treatment. Who knows what would have happened had it remained undetected? Probably nothing good. Also, go check your blood pressure! It’s simple to do and simple to treat if there is an issue, but so many people are walking around with hypertension and not even realising.

Building gates in the walled garden

Even though the watch is arguably a life-saver, not everything is rosy. It’s an Apple product, so you’re firmly locked in a walled garden, jealously guarded by people wearing black turtlenecks. Fortunately, there are a few ways to make it less painful.

All the health and fitness data is stored in Apple Health. You can export data as a big messy file, but it’s a very manual process to do so and the data format is gnarly. Luckily, there’s an app for that! Health Auto Export can, well, automatically export health data. It does what it says on the tin. It can send the data to Home Assistant, over MQTT, or dump it in some cloud file services, but I just have it post it all to a REST endpoint on a service I wrote. Then I dump it all in a database and can do whatever I want with it!⁶

Another tool that’s more useful on the watch itself is Apple Shortcuts. This is their no-code “if-this-then-that”-type thing. You can make automations or shortcuts that run a number of tasks. I have a whole slew of them I access via a complication⁷ on my watch face: one which prompts for input and adds an item to my to-do list (swiping to write letters is surprisingly not horrible), one which lets me select from a bunch of pre-written ones (“charge kindle”, “take laundry out in 1 hour”, type things), one to log my weight into Apple Health, one which can open and close the blinds in my room, and so on. It’s a surprisingly robust and easy-to-use system and offers just enough freedom that I’m not constantly grating on the edge of the walled garden.

Shortcuts being able to initiate arbitrary web requests is the real killer feature for me. Anything I can’t do on the watch itself, I can just farm off to a web server and connect it up with a shortcut. No need to learn Swift or pay Apple for the privilege of being a developer! For a lot of things, like controlling the blinds or adding to-do items, I already had a HTTP endpoint available and exposed over Tailscale⁸. Adding it to the watch was just a case of entering the right things in the Shortcuts app.

Daily nitty-gritty

There are lots of other little bits and pieces that come up when using the watch daily. I don’t think I can bundle them up into a pleasing narrative arc, so instead please enjoy some disjointed paragraphs of observations.

The Apple Watch has a lot of nagging abilities. It can notify you about your fitness “rings”, prompt you to stand up every hour, count how many seconds you wash your hands for, etc. I think I’d dislike these just on general principle, but the way it does them is so condescending it’s painful. I think there’s probably a cultural divide issue here, but there is no way in British English to say “Great job! You washed your hands for 30 seconds!” without it sounding like you’re being amazingly sarcastic or like you’re talking to a young child. So I turned all of that nonsense off. It’s meant to be a tool not a wannabe life coach.

You can access Maps directly on the watch and even do navigation. It works really well. The navigation mode has some nice haptic feedback: it does a short pulse as you’re approaching a turn, and then a long pulse at the actual turn. I like it a lot more than having to dig out my phone or have the directions read out. You get one pulse, glance down and see where you need to go, then it reminds you a little later when it’s time to do it. It’s a delightful user experience.

Watchfaces aren’t quite so delightful. There’s a limited number of built-in ones, and some are “exclusive” to the Ultra Series, and you can’t use them on a peasant watch like a Series 10. Annoyingly, there’s not one that does exactly what I want: a plain analogue clock with an inset date and four complication slots around the outside. Instead, I have to use one of the slots to show the date. There are third-party watchfaces, but they have issues. Firstly, there’s no actual API for making watchfaces⁹, so what they do is bodge it horribly by using a photo background that has fake widgets on it. On top of that they’re almost universally subscription-based. Again, no thanks¹⁰.

The issue I had with the Smart Band triggering when I was sleeping is solved trivially on an Apple Watch, by virtue of it having a physical button in the crown. When you put it in sleep mode, you have to double-press the crown to unlock it before it’ll do anything else. It hasn’t misfired once while I’ve been using it.

Sleep data; spot when I swapped devices!

Finally, a special mention for the gesture controls. If you raise the watch it reliably wakes up (switching from a low refresh rate, dimmed screen to an active, brighter one); you can then double-tap your index finger and thumb together and it will scroll down or page through whatever you’re looking at. The killer feature for this is navigating recipes: you can advance to the next step in a recipe while your hands are covered in flour. It’s also handy for reading notifications: when one pops up, you can double-tap to expand it, then, when it gets to the bottom, it’ll outline the default button (often “Dismiss”) and you can double-tap again to click it.

The verdict

I normally don’t like writing an actual labelled conclusion, but it feels like one is needed here! Overall, I’m happy with the watch. The daily charging doesn’t bother me, the data gathered seems reliable, the health monitoring has obviously paid dividends already, and the walled garden isn’t too chafing. It’s a straight upgrade over my old Smart Band, and I think it was worth the cost.

The original reason for getting the watch was better sleep tracking, though, so how well did it do? I’m much happier with the data: it seems to more accurately represent when I was awake in the night, and overall the sleep phases just seem to make more sense. You can see in the graph that the old data switched frequently between phases, and they didn’t quite line up for some reason; towards the right when the Apple Watch is supplying the data instead there’s a much more consistent pattern of sleep phases that repeat over the course of the night.

I’m not going to advocate that you go out and buy one, though. I know my requirements and usage aren’t typical, and I’ve also not got experience with any recent Android Wear alternatives or the new version of the Pebble watch that’s coming soon. You should definitely get your blood pressure checked, though!

OK, it’s more like 14 now, it’s taken a while for this post to make its way from my brain into text. ↩︎
Exercise for the sake of exercising just seems so overwhelmingly tedious and boring to me. And other types of exercise generally require social interaction, coordinating with people, and so on. ↩︎
Who decided to use “millimetres of mercury displaced” as a unit? You can’t just put random chemical symbols in units! That’s not how this works! ↩︎
Blood pressure readings have two parts: systolic (the pressure when the heart is beating) and diastolic (the pressure between those beats). They’re generally presented with the systolic reading on top and the diastolic reading below, and read as “X over Y”. Now you know what some of the random numbers they shout in medical shows mean! Yay learning! ↩︎
No thanks to how much salt is in everything. I’m pretty sure I’ve had at least twice the recommended daily amount of salt in a single serving before. Don’t even get me started on the things that are “low salt” but are still full of sodium from other sources. I don’t have a problem with ionic compounds, I have a problem with sodium! ↩︎
This mainly looks like drawing graphs that are slightly different to the graphs in the Apple Health graphs, for reasons I’m not sure I can explain. Making graphs is fun, OK? ↩︎
Complications are basically just home screen widgets, but with a fancy name because they’re on a watch. ↩︎
Tailscale actually causes me some problems here: everything works fine when the watch is connected to my phone, as the phone handles the Tailscale part, but if I’m not carrying my phone the watch will try to connect over WiFi directly and doesn’t understand anything about Tailscale. It happens infrequently enough that I’ll just live with it; it’s not much worse than having no signal on a phone. ↩︎
Yay walled gardens… ↩︎
I don’t object to subscribing to things in general, but it has to be something that’s worth the ongoing cost and offers something in return for the subscription. A watchface doesn’t need enough ongoing maintenance to justify subscribing to it, it’s just a cash grab. ↩︎

Home Automation Without the Megacorps

2025-05-21T00:00:00Z

I first experimented with home automation in 2016, by picking up a Samsung “SmartThings” hub. It was terrible. The UI to configure things was slow and clunky, firmware updates were applied whether you wanted them or not, and everything stopped working if their cloud services stopped. You were also locked into whatever integrations they deigned to support, of course. After that broke for the umpteenth time I scaled back and for years the closest I got to home automation was a couple of Hue bulbs.

Recently I’ve been building it out again, though. This time using off-the-shelf components that interop using Zigbee, open-source software, and some code I wrote myself. It’s great; it runs entirely locally and has had basically zero downtime. The Zigbee ecosystem lets me integrate all sorts of things without having to spend lots of money on “smart” alternatives. I think I’ve spent less on this incarnation than I did on the original SmartThings hub all those years ago (even without adjusting for inflation!).

My current setup

I run everything on a Raspberry Pi 4, with a Sonoff USB Zigbee adapter based on the CC2652P chipset¹. Interfacing with the Zigbee stack is handled by zigbee2mqtt (z2m for short), an open-source project that basically bridges your devices to an MQTT broker². When a device reports some data, it will send a new message over MQTT; when you want to make a device do something you just post a message back. It’s incredibly lightweight, but supports a huge array of devices out of the box. And as it’s just using MQTT, it’s trivial to integrate with other software or build on top of.

I know a lot of people building out this kind of home automation use Home Assistant, but I don’t get on with it terribly well. It felt incredibly sluggish, and the entire project is just a bit… much. I want a binary or package or docker image I can just run, not an entire operating system. That’s not how computers are meant to work! In contrast, z2m is simple to set up, super light weight and responsive.

Anyway. z2m exposes Zigbee devices over MQTT, so I wrote some code in Go to connect to the MQTT broker, and listen to the messages. It’s grown a bit beyond this now, and I’m skipping some boring bits like error handling and JSON parsing, but at first I had something like:

for {
    message, topic, err := c.ReadSlices()
    
    if string(topic) == "zigbee2mqtt/desk-button" {
        if strings.Contains(message, "single") {
            c.Publish(nil, []byte("{\"state\": \"TOGGLE\"}"), "zigbee2mqtt/room-lights/set")
        }
    }
}

I think I actually made this harder to read by trying to simplify it here, but hopefully you can follow that it was relatively straight forward to listen for a particular action to happen (in this case me “single”-pressing on the device called “desk-button”) and then make another device do something in response (toggling the state of the “room-lights” device).

So what actually are these devices? At present in z2m I have the following:

Some generic buttons
An air quality sensor (USB powered), and a separate temperature sensor (battery powered)
A light switch
Some 240V relay modules, that I use to turn non-smart devices on and off
Some USB relay modules, for the same purpose
Some “smart” plugs that I mostly use to monitor power usage
A motorised blind roller

I think all of these are either Tuya or Moes branded, and were all sourced from AliExpress. You can get the same things from Amazon or elsewhere, but they tend to be 3-4x more expensive for the same product.

One of the cool things about Zigbee devices is that the powered ones work together to create a mesh network, so you don’t have to worry about network repeaters or signal strength like you do with Wi-Fi networks. z2m even makes a map showing the connections:

The network map produced by z2m. You can see how all the powered devices form a mesh that the lower power ones can connect to.

Some interesting automations

A Zigbee relay spliced into the power cable for the fan

So what do I actually do with all of this? Some of it is just what I’ll call “laziness automation”: I want to be able to turn on the lights without getting up and walking to the light switch. So there’s a Zigbee button on my desk that does it. Then there are some less manual automations: my blinds are automatically closed at sunset³, for example. It feels a bit trivial, but it’s surprisingly nice just not to have to think about that at all.

Another nice quality of life automation is the light I have above my monitor. It’s USB powered, and I now have it going through a Zigbee USB relay that lets it be toggled on and off. Then I have a small agent running on my desktop that turns the light on when the computer is unlocked, and off when it locks or shuts down. I keep meaning to make a “film mode” that detects when I’m watching a film, and turning all the lights and blinds down, but I haven’t got around to it yet.

The most complex automation is probably for a window fan. It’s not smart in any way, so I cut the power cable and inserted a Zigbee relay. The whole thing is housed in a little project box to keep it secure. The relay basically acts as a switch: the live wire leading to the fan runs to the “normally open”⁴ contact, while the upstream power goes to “common”. When the relay is told to turn the fan on, the two get connected and the fan gets power. Oh, it’s also not actually a window fan, but I designed and 3D printed some adapters so that it sits right in the window.

So now we have a window fan that can be turned off and on automatically. But I don’t want to have to press a button to do that. I’m lazy, remember? Instead, I made it so that the Go code constantly monitors the temperature reported by the air quality sensor, and queries the free OpenWeatherMap API to get the rough temperature outside. It can then turn the fan on if the room is too hot, and outside is cool enough to make a difference (there’s no point in blowing hotter air in!).

A graph of room temperature, showing the effect of the fan being turned on and off

I don’t want it to do that all the time though. The room doesn’t need to be cooled if I’m not around. There are various Zigbee presence sensors you can get, but the cheaper ones seem to be of dubious quality. Instead, I wrote some code to guess whether I’m present. It uses the state of the monitor light as a proxy for “is the computer in use”, and then makes some guesses based on the last time the computer was used and the current time (if I turn the computer off at midnight it probably means I’m going to sleep; if I turn it off at 2pm it probably means I’m going out somewhere).

You can see in the graph that the fan has a decent impact on temperature. I coded it to cool the room to 19 degrees, but then not turn on again until it was above 20. This prevents it flip-flopping on and off constantly. You can clearly see the pattern in the graph, as it actively cools and then slowly the room warms back up. This arrangement is much better than being woken up at 5am because it’s painfully cold. Trust me.

Bonuses: metrics and 3D printer

One of the things my custom Go code does is collate all the various stats reported by the Zigbee devices, and inserts them into a VictoriaMetrics database. I originally hosted this on the Pi itself, and it performed fine, but I’ve since moved it onto a server so that I can use it for some other things as well.

I set up Grafana to point to VM, and can create dashboards showing power usage, what devices are turned on when, and a bunch of environmental conditions. This also makes it easy to spot how good the data coming from the devices are. For example, the air quality sensor reports a figure for the amount of Carbon Dioxide in the air, as well as the amount of Volatile Organic Compounds (VOCs). The graphs are basically identical, but on a different scale. It turns out this particular device has no actual way of detecting CO₂, so it just “calculates” it from the VOCs figure. Useful to know if you want to actually use that data.

Recently I came across a go library for interacting with Bambu Lab printers, so I’ve also hooked that into my automation. It exports metrics about the printer, so I now have a way of seeing what’s going on when I’m not physically present⁵. I even added a HTTP endpoint (exposed over Tailscale) that shows pictures from the built-in camera.

On the automation front, I’ve made it automatically turn off the printer’s light when it finishes a print, and also added push notifications via PushOver whenever the state changes. No longer will I be sat in another room blissfully unaware it ran out of filament seconds after I walked out the door!

Was it worth it?

These days you could probably just buy some kind of ‘smart home’ hub that works well enough, and do most of what I’ve done with a lot less effort and no coding. I’m still of the opinion that for something so essentially local, it should itself be managed entirely locally. I don’t trust companies like Google or Amazon not to kill their products, or change or remove an API I rely on.

Obviously the “Not Invented Here” approach of coding everything yourself doesn’t suit everyone, but as someone who enjoys coding and enjoys having things work just so it works very well for me.

It turns out the chipset is important. I initially used a similar Sonoff dongle that used a CC2531 chipset, and its performance wasn’t great. It often failed to pair with new devices, and dropped links to existing ones. The zigbee2mqtt docs do explicitly advise against the CC2531 chips for that reason. At the time they recommended CC2652Ps, so that’s what I went with. If you’re starting new I’d go with whatever their latest recommendation was. ↩︎
MQTT is basically a network protocol for publishing and subscribing to arbitrary messages. A broker is the thing that sits in the middle and routes the messages. I use Mosquitto but any will do. ↩︎
They originally also re-opened at sunrise but that was a terrible mistake. Who knew the sun rose so early?! ↩︎
“open” meaning “there’s a gap so it doesn’t work” not “open for business”. This confusion in terminology also extends to drawbridges. ↩︎
I use the printer in LAN mode, which means there’s no way to monitor it from a phone, even if you’re connected to the same network still. ↩︎

Adventures in IPv6 routing in Docker

2022-10-24T00:00:00Z

One of the biggest flaws in Docker’s design is that it wasn’t created with IPv6 in mind. Out of the box Docker assigns each container a private IPv4 address, and they won’t be able to reach IPv6-only services. While incoming connections might work, the containers won’t know the correct remote IP address which can cause problems for some applications. This situation is obviously suboptimal in the current day and age. It’s a bit like not supporting HTTPS on a website — you might not have any issues because of it immediately, but you’re fighting against the currents of progress and are making life worse for your users.

Thankfully, it’s now relatively easy to make Docker behave a lot nicer. The docker-ipv6nat project has been around since 2016, and uses an IPv6 overlay network and some iptables magic to route traffic to and from containers in a sensible fashion. It uses NAT to emulate the behaviour Docker employs for IPv4 traffic; while using NAT with IPv6 is an anathema, I think it makes sense for containers. You could give each container a publicly routable IPv6 address, but that brings with it a lot of headaches: you’re basically going to be forced to implement service discovery and some kind of DNS management to deal with the fact that your containers will be popping up on randomly assigned IP addresses. That is completely overkill for people running a small number of services on one or two physical boxes; and if it’s not overkill for you then you’re probably already looking at more complicated orchestration solutions like Kubernetes.

More recently, similar functionality has been built into the Docker daemon itself. You can now edit the config file to enable ipv6 and each container will be assigned an address in the range specified when it uses the default bridge network. This gives more-or-less the same functionality of docker-ipv6nat — you lose a little flexibility as you can’t disable IPv6 on the default bridge, but that’s a very worthy trade for having the functionality built-in.

So far this all seems very simple. Hardly worthy of being called an “adventure”. Enter stage left: the wicked witch of destination address selection…

Destination address selection and you

When a computer program tries to connect to an address such as google.com, it first resolves it in to an IP address. That’s DNS 101, but what happens if the address resolves to multiple IP addresses? For example, google.com resolves to both 142.250.74.206 and 2a00:1450:4001:82b::200e. You might just assume there’s a simple “prefer IPv4 / prefer IPv6” toggle somewhere that decides, but it’s actually a lot more complicated. With IPv6, devices are likely to have many addresses - a link-local address, a unique local address, a normal public address, various privacy addresses, and so on. To deal with this, a number of RFCs define a series of rules that most implementations follow. These are called the destination address selection rules. RFC6724 gives the rules as:

Avoid unusable destinations
Prefer matching scope
Avoid deprecated addresses
Prefer home addresses
Prefer matching label
Prefer higher precedence
Prefer native transport
Prefer smaller scope
Use the longest matching prefix
Otherwise, leave the order unchanged

Applying these rules will re-order the list of IP addresses such that (in theory) the most likely one to work will be first. Most of them are fairly niche rules; the ones that do the heavy lifting are rules 5 and 6, which rely on a policy table to make their decisions. The policy table ‘SHOULD’ be configurable by system administrators to allow them to tweak how traffic is routed. In the absence of an admin-provided policy table, the RFC gives the following defaults:

Prefix	Precedence	Label	Notes
`::1/128`	50	0	Loopback address
`::/0`	40	1	Any IPv6 address
`::ffff:0:0/96`	35	4	IPv4 addresses mapped as v6 addresses
`2002::/16`	30	2	6-to-4 gateways
`2001::/32`	5	5	Toredo tunnels
`fc00::/7`	3	13	Unique Local Addresses (ULAs)
`::/96`	1	3	IPv4 compatible addresses (deprecated)
`fec0::/10`	1	11	Site-local addresses (deprecated)
`3ffe::/16`	1	12	6bone (deprecated)

The policy table is a bit complex, but you can see that normal IPv6 addresses are preferred (have a higher precedence) over IPv4 addresses, which are preferred over the various tunnels, local addresses, and various deprecated ranges.

We can see the result of this when I run ping google.com on a box that has a native IPv6 connection as well as a native IPv4 connection:

PING google.com(fra07s29-in-x200e.1e100.net (2a00:1450:4001:802::200e)) 56 data bytes
64 bytes from fra24s01-in-x0e.1e100.net (2a00:1450:4001:802::200e): icmp_seq=1 ttl=119 time=5.11 ms
64 bytes from fra24s01-in-x0e.1e100.net (2a00:1450:4001:802::200e): icmp_seq=2 ttl=119 time=5.28 ms
64 bytes from fra07s29-in-x200e.1e100.net (2a00:1450:4001:802::200e): icmp_seq=3 ttl=119 time=5.31 ms
^C
--- google.com ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2003ms
rtt min/avg/max/mdev = 5.114/5.235/5.311/0.086 ms

The address selection in this instance has been a result of rule 6: the IPv6 address has a higher precedence (40) than the IPv4 address (35).

However, if I run the same command in an IPv6-enabled Ubuntu container then it seems to prefer the IPv4 address:

PING google.com (172.217.16.206) 56(84) bytes of data.
64 bytes from fra16s08-in-f206.1e100.net (172.217.16.206): icmp_seq=1 ttl=59 time=4.86 ms
64 bytes from fra16s08-in-f14.1e100.net (172.217.16.206): icmp_seq=2 ttl=59 time=4.86 ms
64 bytes from fra16s08-in-f14.1e100.net (172.217.16.206): icmp_seq=3 ttl=59 time=5.03 ms
^C
--- google.com ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2003ms
rtt min/avg/max/mdev = 4.860/4.916/5.027/0.078 ms

If I force ping to use IPv6 with the -6 flag then it works the same as on the host, but when left to its own devices it prefers IPv4. What’s going on there? The key difference between the Docker container and the host is that the host’s network interfaces have public addresses, but the container has a private IPv4 address (172.19.0.7) and a private IPv6 address (fd00:dead:beef::7). My first reaction to this was to think “Ah yes, fc00::/7 has a lower precedence than native IPv4, that makes sense”, but that’s not quite right. These are the destination address selection rules; rule 6 doesn’t care about the source addresses. This is actually rule 5 at work: the label of source IPv6 address is 13, but the label of the destination address is 1; meanwhile both the source and destination IPv4 addresses are 4. This sorts the IPv4 address before the IPv6 one, and rule 6 becomes irrelevant.

Adjusting the policy table

Thankfully, the RFC says the policy table should be configurable by system administrators, so those of us who are doing unorthodox things like NAT’ing IPv6 can customise the behaviour to fit our weird environments. The configuration is done via the /etc/gai.conf file (‘gai’ standing for getaddrinfo, the function in the standard library responsible for dealing with all these rules). The gai.conf file by default (if it exists) will likely just contain comments and examples; if there are no uncommented “label” or “precedence” lines then the library will use its built-in defaults based on the RFC requirements.

To make our container happy, we need to cause fd00::/8 to have the same label as a public IPv6 address. To do this we can uncomment the default labels in gai.conf and then add a single extra line, like so:

 label ::1/128       0
 label ::/0          1
 label 2002::/16     2
 label ::/96         3
 label ::ffff:0:0/96 4
 label fec0::/10     5
 label fc00::/7      6
 label 2001:0::/32   7
+label fd00::/8      1

Because fd00::/8 has a longer prefix than fc00::/7 it will match our addresses and give them a label of 1, the same as a public IPv6 address would get. This makes rule 5 leave it alone, and the default precedence table used by the standard library will put the IPv6 address above the IPv4 address. (They don’t bother giving fc00::/7 a separate precedence as listed in the RFC because rule 5 would have already de-prioritised those addresses, as we discovered.)

Making this small change to the gai.conf file in our Ubuntu container makes it start preferring the IPv6 address for google.com:

PING google.com(fra16s65-in-x0e.1e100.net (2a00:1450:4001:806::200e)) 56 data bytes
64 bytes from fra15s29-in-x0e.1e100.net (2a00:1450:4001:806::200e): icmp_seq=1 ttl=118 time=5.00 ms
64 bytes from fra15s29-in-x0e.1e100.net (2a00:1450:4001:806::200e): icmp_seq=2 ttl=118 time=5.10 ms
64 bytes from fra16s65-in-x0e.1e100.net (2a00:1450:4001:806::200e): icmp_seq=3 ttl=118 time=5.08 ms
^C
--- google.com ping statistics ---
3 packets transmitted, 3 received, 0% packet loss, time 2004ms
rtt min/avg/max/mdev = 5.002/5.058/5.098/0.040 ms

A fairly complicated problem, but a simple fix!

But wait, there’s more…

Unfortunately, this fix won’t work on containers that use alpine. And that is a lot of containers. Alpine uses musl as its standard library, rather than the much more common glibc. There is very little documentation on the subject, but if you browse the source code for musl you will see that it doesn’t implement any way at all to configure the policy tables. In network/lookup_name.c we can see the sorting logic:

	/* The following implements a subset of RFC 3484/6724 destination
	 * address selection by generating a single 31-bit sort key for
	 * each address. Rules 3, 4, and 7 are omitted for having
	 * excessive runtime and code size cost and dubious benefit.
	 * So far the label/precedence table cannot be customized. */
	for (i=0; i<cnt; i++) {
		int family = buf[i].family;
		int key = 0;
		struct sockaddr_in6 sa6 = { 0 }, da6 = {
			.sin6_family = AF_INET6,
			.sin6_scope_id = buf[i].scopeid,
			.sin6_port = 65535
		};
		struct sockaddr_in sa4 = { 0 }, da4 = {
			.sin_family = AF_INET,
			.sin_port = 65535
		};
		void *sa, *da;
		socklen_t salen, dalen;
		if (family == AF_INET6) {
			memcpy(da6.sin6_addr.s6_addr, buf[i].addr, 16);
			da = &da6; dalen = sizeof da6;
			sa = &sa6; salen = sizeof sa6;
		} else {
			memcpy(sa6.sin6_addr.s6_addr,
				"\0\0\0\0\0\0\0\0\0\0\xff\xff", 12);
			memcpy(da6.sin6_addr.s6_addr+12, buf[i].addr, 4);
			memcpy(da6.sin6_addr.s6_addr,
				"\0\0\0\0\0\0\0\0\0\0\xff\xff", 12);
			memcpy(da6.sin6_addr.s6_addr+12, buf[i].addr, 4);
			memcpy(&da4.sin_addr, buf[i].addr, 4);
			da = &da4; dalen = sizeof da4;
			sa = &sa4; salen = sizeof sa4;
		}
		const struct policy *dpolicy = policyof(&da6.sin6_addr);
		int dscope = scopeof(&da6.sin6_addr);
		int dlabel = dpolicy->label;
		int dprec = dpolicy->prec;
		int prefixlen = 0;
		int fd = socket(family, SOCK_DGRAM|SOCK_CLOEXEC, IPPROTO_UDP);
		if (fd >= 0) {
			if (!connect(fd, da, dalen)) {
				key |= DAS_USABLE;
				if (!getsockname(fd, sa, &salen)) {
					if (family == AF_INET) memcpy(
						sa6.sin6_addr.s6_addr+12,
						&sa4.sin_addr, 4);
					if (dscope == scopeof(&sa6.sin6_addr))
						key |= DAS_MATCHINGSCOPE;
					if (dlabel == labelof(&sa6.sin6_addr))
						key |= DAS_MATCHINGLABEL;
					prefixlen = prefixmatch(&sa6.sin6_addr,
						&da6.sin6_addr);
				}
			}
			close(fd);
		}
		key |= dprec << DAS_PREC_SHIFT;
		key |= (15-dscope) << DAS_SCOPE_SHIFT;
		key |= prefixlen << DAS_PREFIX_SHIFT;
		key |= (MAXADDRS-i) << DAS_ORDER_SHIFT;
		buf[i].sortkey = key;
	}
	qsort(buf, cnt, sizeof *buf, addrcmp);

We can see if the address labels match, the sort key is adjusted using the DAS_MATCHINGLABEL constant. But where do the labels come from? For that we need to investigate the policyof func:

static const struct policy {
	unsigned char addr[16];
	unsigned char len, mask;
	unsigned char prec, label;
} defpolicy[] = {
	{ "\0\0\0\0\0\0\0\0\0\0\0\0\0\0\0\1", 15, 0xff, 50, 0 },
	{ "\0\0\0\0\0\0\0\0\0\0\xff\xff", 11, 0xff, 35, 4 },
	{ "\x20\2", 1, 0xff, 30, 2 },
	{ "\x20\1", 3, 0xff, 5, 5 },
	{ "\xfc", 0, 0xfe, 3, 13 },
#if 0
	/* These are deprecated and/or returned to the address
	 * pool, so despite the RFC, treating them as special
	 * is probably wrong. */
	{ "", 11, 0xff, 1, 3 },
	{ "\xfe\xc0", 1, 0xc0, 1, 11 },
	{ "\x3f\xfe", 1, 0xff, 1, 12 },
#endif
	/* Last rule must match all addresses to stop loop. */
	{ "", 0, 0, 40, 1 },
};

static const struct policy *policyof(const struct in6_addr *a)
{
	int i;
	for (i=0; ; i++) {
		if (memcmp(a->s6_addr, defpolicy[i].addr, defpolicy[i].len))
			continue;
		if ((a->s6_addr[defpolicy[i].len] & defpolicy[i].mask)
		    != defpolicy[i].addr[defpolicy[i].len])
			continue;
		return defpolicy+i;
	}
}

So the policyof func simply uses the defpolicy array to find the policy that applies to an address. This defpolicy array contains a number of hardcoded entries which correspond exactly to the ones provided in the RFC. The one causing us problems is { "\xfc", 0, 0xfe, 3, 13 } which matches fc00::/7 addresses.

Unfortunately, without recompiling musl from source there’s not much we can do to address this directly. The only way we can make the containers work as desired is to give them a different address range. Ideally this would be a range that you control and that is otherwise not used, but there’s a good chance you won’t have such a range. One possible alternative is the 2001:db8::/32 range which is reserved for documentation purposes. This doesn’t feature in any of the policy tables, so is treated like a normal public IPv6 address. It doesn’t feel great to misuse a reserved range like that, but it’s probably the least of all evils, at least until musl allows configuring the policy table.

Reverse engineering an Arctis Pro Wireless Headset

2021-06-12T00:00:00Z

The Arctis Pro Wireless Headset.

For the last year and a bit, I’ve been using a SteelSeries Arctis Pro Wireless Headset for gaming and talking to friends. It’s a fine headset, but because there’s an always-on receiver there’s no way to detect if the headset is turned on or not from the desktop.

Whenever I start using the headset, I set my desktop’s sound to go to the headset, and then when I stop using the headset I set it to go back to speakers. It doesn’t take more than a second, but some days I might put the headset on a dozen times as I’m on calls, or if it’s noisy outside, etc. That means it’s probably worth at least a few hours of my time trying to automate it.

At first, I hoped I’d be able to tell from the state of the USB device whether there was a headset connected but nothing at all changed when flipping it on and off. Then I went hunting for existing open source tools that might work with it and found that while people have reverse engineered many of the older Arctis headsets, no one has done the same for the Pro Wireless. I finished off with a search to see if anyone had documented the wire protocol even if there was no nice open source software to go with it; I came up short there, too. Looks like I’d have to do it myself.

Capturing data with WireShark

The headset exposes a Human Interface Device (HID), and the wire protocols for earlier versions of the Arctis series looked to be very simple messages passed over the HID connection. It should therefore be fairly easy to use WireShark to capture the data being sent and received by the official SteelSeries application¹.

After setting up WireShark and making it record only the headset’s HID connection, it quickly became apparent that the software was sending three different requests each second, over and over again:

Wireshark, showing a packet capture of a SET_REPORT request from the host to the headset

The packets we’re interested in are the SET_REPORT Request frames sent from the host to the device. Wireshark understands the HID protocol, so it nicely shows us the raw HID data; in the screenshot this is 0x40AA (ignoring the trailing zero bytes). The other requests sent immediately after have 0x41AA and 0x42AA payloads — clearly the first byte is indicating which piece of data is being requested.

The responses to these requests come back in an URB_INTERRUPT in frame:

Wireshark, showing a packet capture of the headset’s response to the earlier request

So the answer to our first request appears to be 0x04. The second response is 0x0402 and the third is 0x04 again. The first thing I tried doing was popping the spare battery out of the charger. The response to the 0x42AA request changed from 0x04 to 0x00 - that’s certainly clear enough! After a bit of waiting around, the battery in my headset dropped from full on the display to three bars, and at that point the 0x40AA response dropped from 0x04 to 0x03. The display on the receiver shows battery state as four bars, and it appears the wire protocol directly corresponds to that particular representation.

That left the 0x41AA request as an unknown. I tried everything I could think of, but it stubbornly kept returning 0x0402. I enlisted a friend who has the same headset to run some hacky Go code and report his values, and he also got a 0x0402 response. As I explained that I couldn’t figure out what these values are, he reported back that turning his headset off made the response change to 0x0202. In all my testing, I’d forgotten to try turning the headset off! That’s the one thing I was actually trying to detect, as well. Thanks, Simon, for helping me get past that bit of stupidity!

I still don’t know what the second byte of the response is, or whether there are other values than 0x04 for on and 0x02 for off, but I’m happy enough to label it as “device status” and move on.

Exploring other features

The software allows you to tweak a bunch of different settings:

SteelSeries Good Game software, showing the advanced headset settings

I went through each one and fiddled with all the values, recording the requests in WireShark as I did so. It turns out the protocol is very simplistic - the wire protocol directly corresponds to the UI elements in the software (or on the receiver, if you navigate through its menus). For example, the software allows you to set the “Headset auto shutoff” value in increments of 10 minutes. You might usually expect this to be converted to seconds or something similar before being passed to the device, but on the wire it’s actually sent as 0x00 for off, 0x01 for 10 minutes, up through to 0x0C for the maximum of 120 minutes.

All the dropdown options seem to function this way — if you pick the 6th option then the request payload will be an 0x06 byte. The sliders have fixed positions they snap to and function similarly: for the two brightness sliders pictured they snap to 11 positions and on the wire these range from 0x00 for off to 0x0A for the maximum.

At this point I was well past my goal of being able to detect whether the headset was on or off, and I was now just trying to see if I could figure out enough of the protocol that I could reimplement the control software on Linux if I ever wanted to. Just as I was about to close the app, something caught my eye: there are integrations with games and other software that can display information on the receiver’s OLED display!

There’s an official API for this, but it involves sending JSON to a webserver which runs as part of their app². That doesn’t feel very nice, and definitely won’t work for me on Linux, so I started a new WireShark session and took some captures while I spoke to myself on Discord.

Decoding pixels

The frames sent to the device whenever Discord showed a notification had a 1060 byte payload. The display on the receiver is 140 pixels wide³ and each pixel can only seem to be on or off, so I figured each bit in the payload corresponded to one bit of the output. I exported the data to binary in the hope that I could visually see what was going on - in theory if I line wrap the data at 140 characters it should look vaguely like the final output. Unfortunately, it did not. There was roughly the right number of high bits, but no amount of fiddling with them in a text editor could give me a coherent picture.

Instead, I wrote some code to write different values to the device. Starting with a payload of all zeroes and gradually increasing a bit at a time every second. After the first few seconds, I saw a line of pixels being drawn downwards on the left of the screen; had I just got the axes the wrong way around? After the first eight pixels lit up, though, they jumped over to the next column. The actual addressing scheme looks something like this:

Diagram of how pixels are addressed on the receiver’s OLED display

So the first 140 bytes given the pixels for the first 8 rows, the next 140 bytes fill in the 8 rows below that, and so on and so forth. Armed with this information I wrote a simple program to read an image and output it to the display:

Headset receiver displaying a custom Hello World message

At this point I was thinking about trying to get Doom rendering on the screen, but I couldn’t find anything nicely hackable that would let me grab the output and pass it on to the receiver. Instead, I decided to try a GIF decoder and before very long had a nice little animated display:

Protocol reference

All the HID messages have a single byte that determines the message type, then an 0xAA byte, then any payload required by the command. These are the ones I’ve figured out:

Byte	Command	Payload
`0x09`	Save changes	None.
`0x10`	Request firmware version(?)	None.
`0x27`	Volume limiter	`0x00` for off, `0x01` for on.
`0x2E`	Equalizer preset	ID of the equalizer preset to use.
`0x39`	Sidetone level	`0x00` for lowest to `0x09` for highest.
`0x3C`	Set headset timeout	Timeout, as a number of 10 minutes. `0x00` for off to `0x0C` for 120 mins.
`0x3E`	Mic mute LED brightness	`0x00` for lowest to `0x0A` for highest.
`0x40`	Request headset battery	None.
`0x41`	Request device status	None.
`0x42`	Request receiver battery	None.
`0x51`	Surround sound mode	`0x00` for off, `0x01` for on.
`0x62`	Auto-start Bluetooth	`0x00` for off, `0x01` for on.
`0x63`	Auto-mute game audio during calls	`0x00` for off, `0x01` for on.
`0x85`	OLED brightness	`0x00` for lowest to `0x0A` for highest.
`0x83`	Equalizer	(Not yet decoded)
`0x89`	Screensaver mode	`0x00` to dim, `0x01` for off, `0x02` for screensaver.
`0xD2`	Render image	Pixel array as described above.

Some of these I’ve not dug too much into because they didn’t seem very interesting. If you have an Arctis Pro Wireless and figure anything more out, let me know, and I’ll update the list.

If you just want to check device state like I originally did, I’ve contributed support for this headset to the excellent HeadsetControl project. It should be in the next release.

Unfortunately (as you’d expect) their application only runs on Windows, so this process involved an annoying amount of rebooting to Windows, fleeing back to Linux, and then realising I hadn’t actually recorded enough to figure it out and repeating. ↩︎
You can also send lisp to the webserver, and it will execute it. No comment. ↩︎
I know this not because it’s mentioned in the technical specs (it’s not), but because I took a photo and counted them out one by one. ↩︎