Author Archives: Patrik

Looking into Cox Panoramic Wifi:s backend

Some brief follow up on the looking-into-things this hearing about a few new router vulns caused over here..

The “main” Cox modem (Panoramic Wifi Gateway, rentable only) is actually a poorly white-labeled Technicolor CGM4140, same as Xfinity Xfi. Those run Broadcom BCM3390 processors (in all it’s MIPSy glory), just like the vulnerable ones (https://fccid.io/G95CGM414X/Internal-Photos/Internal-Photos-Part-1-3423780).
The FW seems a little different, in part because it’s been revamped to handle all the network config via Cox:es main server rather than via a normal web interface (though that’s partly still there too). However, the image is pretty clearly based on XFinitiy Xfi. The actual direct interface on the lan (192.168.0.1) self-identifies as such:

HTTP/1.1 200 OK
X-Frame-Options: deny
X-XSS-Protection: 1; mode=block
Date: Mon, 13 Jan 2020 00:42:28 GMT
Server: Xfinity Broadband Router Server

There are several more places where they forgot to change to Cox. But that’s not all – the backend of the whole control-your-router-from-your-cable-login *runs at comcast*:

Request URL: https://siorc.xfinity.com/account/**number**/gateway/7C*******82/group/cpeConnectedDevices/?signature=<244_byte_base64_blob>

When entering wifi.cox.com (aka MyWifi), it goes through a cox auth-sequence (or verifies your prior from cookies). Then a pile of js (https://wifi.cox.com/bundles/critical-path.d47e6d08c4c59a64ef86.js) writes up a nice Authorization Bearer header, and calls https://siorc.xfinity.com/ with it:

“name”: “Authorization”,
“value”: “Bearer <base64 dot-separated blob>”
.. decodes into ..
— Part 1 —
{ “kid”:”sat-prod-k1-1024″, “alg”:”RS256″}
— Part 2 —
{ “jti”:”65cd1d65-6449-466b-a9af-3e71843901e5″, “iss”:”sats-production”,
“sub”:”x1:smartinternetclient:1c6952″,
“iat”:1578849026, “nbf”:1578849026, “exp”:1578852629,
“version”:”1.0″,
“allowedResources”:{
“allowedPartners”: [ “cox” ],
“allowedServiceAccountIds”: [ “******number*******” ]
},
“capabilities”: [
“x1:xfi-orc:read”,
“x1:xfi-orc:read-secrets”,
“x1:xfi-orc:write”
],
“aud”:[]
}
— Part 3 —
<128 byte blob>

So, a fairly typical signed JWT letting Comcast know that Cox ok:ed this, what we’re down for, expiration, etc. After, siorc.xfinity.com starts including a singature chunk in it’s URLs:

https://siorc.xfinity.com/accountX/?accountUri=*******************&signature=<112 byte urlenc base64>

https://siorc.xfinity.com/account/***********/configset/
fb96d22a-51d4-48b0-8ac8-ba3f30ddb62a/more/?
gatewayMacAddress=7C******82&
hasPlumeDevices=false&
signature=<blob>

https://siorc.xfinity.com/gateway/7C******82/checkReachability/?signature=<blob>

https://siorc.xfinity.com/account/***/gateway/7C******82/group/cpeConnectedDevices/?signature=<blob>

Together with a number of selected JS loads from cox, it dumps over most of the front page definitions, to be handled by React. It also gives values, defaults, labels, URLs to activate to change them, etc – basically relaying a normal modem front end but in json.

Much of the definitions are given types via “_type”:”https://github.comcast.com/pages/CPE/SmartInet/NetworkConfig”
Apparently comcast has a github. I doesn’t answer to customer connections though. I think there’s a relay baked into this, but I haven’t dug it up.

Haven’t found the specfic endpoints they found to be vulnerable, but it’s big enough and has so much awkward interop I have a hard time thinking all this is airtight (especially since there’s rarely a reason to look at it). I’d be slightly surprised if everything enforced XSS to the point of needing DNS Rebinding (lots of responses sprinkle in hapazard Origin allows) but I’d be even more shocked if it balked at being called by a non-IP name (like Host: some.other.host instead of Host: 192.168.0.1). Not sure how vulnerable they might otherwise be. They seem to be removing options bit by bit, like no longer allowing setting your own DNS, forwarding dangerous ports, and so on. Perhaps I look again when I’m less facinated by the strange Cox/Xfinity gangbang going on here..

Oh and they also throw in xerxessecure (https://xerxes-sub.xerxessecure.com/xerxes-ctrl/keys/jwks for instance) for putting out keys for the signatures and similar auth:y things. Whois says it’s comcasts. There’s also a “diagnostic signaler” (hyperactive snitch-logger on a 3-5s timeout) sending stuff to “https://melee.sed.dh.comcast.net/v2/event/sic”. Seemingly just to be nosy, but there might be other reasons.

I poked a little at the JWTs to see if they accepted other algos (some implementations take your word for what it’s supposed to be validated with, so you can swap out RS256 for, say, MD5). No immediate success, but I probably messed it up.

Quick test of nmaps new RDP scan script

After seeing this:

Using Nmap to extract Windows host and domain information via RDP

 
# Nmap 7.70SVN scan initiated Fri Jun 14 13:57:47 2019 as: nmap -p 3389 --script rdp-ntlm-info -oout 192.168.200.0/24
Nmap scan report for wolfsbane (192.168.200.1) # router, runs a (likely ancient) Samba + accompanying auth
Host is up (0.00022s latency).

PORT STATE SERVICE
3389/tcp closed ms-wbt-server
MAC Address: 60:38:E0:77:F0:61 (Belkin International)

Nmap scan report for DESKTOP-GOO4FB1 (192.168.200.13) # Slightly aging desktop, runs win 10 preview build, set to "weekly or so" updates
Host is up (0.00011s latency).

PORT STATE SERVICE
3389/tcp filtered ms-wbt-server
MAC Address: 00:0F:FE:EB:D0:3F (G-pro Computer)

<several unrelated devices deleted>

Nmap scan report for LAPTOP-UR57MFD8 (192.168.200.156) # Fujitsu touchscreen/wacom tablet laptop for ZBrush/Photoshop, runs Win 10 Home, defaults on everything. Supposed to be legit upgraded from Vista, but if it gave me crap about it, it's cracked. I don't remember how it went.
Host is up (0.038s latency).

PORT STATE SERVICE
3389/tcp filtered ms-wbt-server
MAC Address: 90:CD:B6:70:50:02 (Hon Hai Precision Ind.)

<more devices deleted>
# ---- TehEdn

# There's at least three more laptops with Win 10, one of which is booted and running right now. Win 10 Home OEM (legit came installed on it - I've done nothing afaik). The two others are very similar to the Fujisu, but they're very likely asleep/off.

# That sucked, so Redo, after I flip on RDP on the Desktop (I remember turning it off specifically, not sure why the others are off).

root@joe:~# nmap -p 3389 --script rdp-ntlm-info 192.168.200.13
Starting Nmap 7.70SVN ( https://nmap.org ) at 2019-06-14 14:11 UTC
Nmap scan report for DESKTOP-GOO4FB1 (192.168.200.13)
Host is up (0.00022s latency).

PORT STATE SERVICE
3389/tcp filtered ms-wbt-server
MAC Address: 00:0F:FE:EB:D0:3F (G-pro Computer)

Nmap done: 1 IP address (1 host up) scanned in 0.65 seconds

# Huh? Perhaps it's the internal firewall thing. <check> Doesn't seem to be - 3389 has two rules - allow any TCP and allow any UDP. Trying to RDP to myself, it complains that I have a console up to the "remote comnputer" already.
#
# Installed "rdesktop" and attempted to connect, which timed out (very slowly) so perhaps something is blocked on another level somehow.
#
# nmap (and rdesktop/X) here runs on Ubuntu 18.04.2 LTS. Nothing particularly out of the ordinary on it, has X (xfce desktop) and virtualbox, both sort of unusual but not rare, has docker (exec environment, for dev/test, nothing running in it). nmap is Nmap 7.70SVN, built from repo linked in the article ("./configure && make && make install", added flex and libpcap (this is a *really* green install, used to be alpine, couldn't run vbox) and reran, built 2nd pass).
#
# So I dunno - I'm probably messing something up, might mess w/ more later.
root@joe:~# cat out
# Nmap 7.70SVN scan initiated Fri Jun 14 13:57:47 2019 as: nmap -p 3389 --script rdp-ntlm-info -oout 192.168.200.0/24
Nmap scan report for wolfsbane (192.168.200.1) # router, runs a (likely ancient) Samba + accompanying auth
Host is up (0.00022s latency).

PORT STATE SERVICE
3389/tcp closed ms-wbt-server
MAC Address: 60:38:E0:77:F0:61 (Belkin International)

Nmap scan report for DESKTOP-GOO4FB1 (192.168.200.13) # Slightly aging desktop, runs win 10 preview build, set to "weekly or so" updates
Host is up (0.00011s latency).

PORT STATE SERVICE
3389/tcp filtered ms-wbt-server
MAC Address: 00:0F:FE:EB:D0:3F (G-pro Computer)

<several unrelated devices deleted>

Nmap scan report for LAPTOP-UR57MFD8 (192.168.200.156) # Fujitsu touchscreen/wacom tablet laptop for ZBrush/Photoshop, runs Win 10 Home, defaults on everything. Supposed to be legit upgraded from Vista, but if it gave me crap about it, it's cracked. I don't remember how it went.
Host is up (0.038s latency).

PORT STATE SERVICE
3389/tcp filtered ms-wbt-server
MAC Address: 90:CD:B6:70:50:02 (Hon Hai Precision Ind.)

<more devices deleted>
# ---- TehEdn

# There's at least three more laptops with Win 10, one of which is booted and running right now. Win 10 Home OEM (legit came installed on it - I've done nothing afaik). The two others are very similar to the Fujisu, but they're very likely asleep/off.

# That sucked, so Redo, after I flip on RDP on the Desktop (I remember turning it off specifically, not sure why the others are off).

root@joe:~# nmap -p 3389 --script rdp-ntlm-info 192.168.200.13
Starting Nmap 7.70SVN ( https://nmap.org ) at 2019-06-14 14:11 UTC
Nmap scan report for DESKTOP-GOO4FB1 (192.168.200.13)
Host is up (0.00022s latency).

PORT STATE SERVICE
3389/tcp filtered ms-wbt-server
MAC Address: 00:0F:FE:EB:D0:3F (G-pro Computer)

Nmap done: 1 IP address (1 host up) scanned in 0.65 seconds

# Huh? Perhaps it's the internal firewall thing. <check> Doesn't seem to be - 3389 has two rules - allow any TCP and allow any UDP. Trying to RDP to myself, it complains that I have a console up to the "remote comnputer" already.
#
# Installed "rdesktop" and attempted to connect, which timed out (very slowly) so perhaps something is blocked on another level somehow.
#
# nmap (and rdesktop/X) here runs on Ubuntu 18.04.2 LTS. Nothing particularly out of the ordinary on it, has X (xfce desktop) and virtualbox, both sort of unusual but not rare, has docker (exec environment, for dev/test, nothing running in it). nmap is Nmap 7.70SVN, built from repo linked in the article ("./configure && make && make install", added flex and libpcap (this is a *really* green install, used to be alpine, couldn't run vbox) and reran, built 2nd pass).
#
# So I dunno - I'm probably messing something up, might mess w/ more later.

Review of Kandy Pens RUBI + SALT BAE Red Mango 50mg/30ml

Kandy Pens RUBI box, device, and bottle of juice

Kandy Pens RUBI Box, assembled device, and bottle of juice from Salt BAE

Disclosure: I received free product. I’m not sure from whom or to what exact end – I agreed to receive them and verified myself as a 21+ aged smoker to a non-descript intermediary, and if you give me seventy bucks worth of merch send it thought a cutout, I’ll happily respect your privacy. So let’s say some online influence campaign who respected appropriate laws did it, because that’s all I know.

I’m in my 40s, long time ~pack a day smoker. I’ve used three or four different e-cigarettes at various points, never very long nor even briefly to the exclusion of normal tobacco. I filled out a bunch of eligibility forms for smokers, mostly hoping to get some coupons, and along with them, got this offer. I have two daughters in HS and college respectively, whom I have not massively alienated and from whom I’ve heard of the rise and later mild stagnation of JUUL, but my roots are firmly planted in Gen-X rather than millennials/gen-y, and while I’d like to think I have a measure of respect in said groups, I only aspire to be an occasional bridge, cheerleader, and dropper of devastatingly bad dad jokes, not to join them or be “with it”.

I open the box pictured to find a small refillable pod, a battery/device, a small rubber stopper, and a short flat charging cable. The cable is a perfectly average USB micro-B,  as used by nearly all non-iPhones. After three decades of refilling ink cartridges, unlocking cell phones, and soldering bizarre adapters, supplying an intentionally refillable pod and using a standard cable give me an instant “These are my people!” vibe. The packaging is study feeling. The pod snaps in with a nice “click”, seemingly to stay in place. The device is kind of light, and appears to be made of aluminum. It’s Rose Gold (other colors were available) which matches my daughters iPhone and is obviously cruise control for cool (unless they changed that again).

It charged in 30 min, a little K on glowing red, then white to show full charge. In use, same deal – white mean charged, red means running low. I’ve never ran it completely out of power, so I don’t know exactly how the “red K” keeps working, but two-ish cig breaks seems ok. At my pace, it appears to last 6-12 hours or so.

Filling the pod was uneventful, open bottle, push juice into pod, push silicone stopper back into pod. Drawing on it automatically triggers the heat (a high-ohm coil, meant for nicotine salt solutions, I’m told). After a few false starts of not pulling long or hard enough and tinkering a little with the two “air carb” holes on the side that can limit fresh air mix, I get it to work and successfully inhale big clouds of faux-smoke. It’s not nearly as harsh as other e-cigs I’ve tried, about on-par with normal cigarettes but much smoother if inhaling directly instead of the “suck-inhale” cycle of cigarettes. It tastes strongly like ripe mango, which is nice. I can’t really offer a comparison to other mango flavors (non-cough*JUUL*non-cough) but I like it. I do like that I am clearly inhaling *something* that isn’t air, but it isn’t overly harsh seeming to throat or tongue.

The pod holds ~1ml, which, after some quick calculations that appear to jive with so-far field testing appears to be roughly equivalent to 1 pack or full-flavor filter shorts, possibly a little less. If you were hoping to cut back on nicotine and eventually quit, there’s apparently options for that. I’ve tried to quit a few times, but my heart isn’t really in it – at this point I’m hoping to perhaps transfer the addiction onto something less harmful, then regroup from there. Price wise, that works out to 70-80 cents a “pack equivalent” had I bought the juice as $20 (approximate online price), which is excellent both compared to actual packs (~$6 and on the way up) and pre filled pods for other vapes.

I’m on day three, so an evaluation might be slightly premature, but midway through day two, something interesting happened. I misplaced my vape, and didn’t notice for long enough that I was clearly wanting it. I thought “Oh well, I’ll just smoke a cig” to which my subconscious immediately recoiled with “NO! FIND VAPE!”. Now, that’s astonishingly fast, as well as unexpected – all other e-cigs, gum, patches, etc have been “I want a cigarette. Ok, FINE, I’ll do/chew/use this thing for a while, I *guess* I don’t quite want one as badly now”, never even remotely realigning what it is I’m addicted to let alone actively wanting the replacement rather than the original. I’ve smoked a total of six cigarettes in the days since I got it (normally, ~30-35 would have been typical), intentionally putting for absolutely zero effort into it – if I want to smoke, I smoke – which I’m quite impressed by. I’m in no way at all less addicted to nicotine, but while none of the other delivery systems were close, I really feel like this is cementing itself in as “the nicotine source”, for better or worse.

If I had paid for it, I’d feel a little hesitant about the starting kit price ($50), though really that puts the entire startup at around a carton of cigs, which it will, if nothing else, absolutely mange to replace over time in my case (likely in a week or two, certainly within a month), quite likely much more than that. I’m not really sure how I feel about it as a nicotine cessation aid, but if you’re not sure about kicking nicotine, you probably won’t anyway and moving to a safer delivery system is almost certainly a huge cut in harm, even if it’s not a safe alternative as such.

Pros:

  • Exactly the size of two 100s cigs laid side by side, which is convenient.
  • Actually succeeded in reducing my smoking by 95% in two days, without any particular effort on my part
  • Intentionally refillable pods, no hacking/modding for use with arbitrary vape juice, putting the operational costs not just firmly below cigarettes or cigars, but all the way down to cheaper than any other tobacco product ever
  • Good fit if you’re really not ready to quit smoking, but would like to not wreck your lungs inhaling a continuous stream of tar and partially burned leaf

Cons:

  • Hasn’t magically made me want to give up nicotine, and probably won’t
  • Wouldn’t hurt to have slightly longer lasting battery and/or user replaceable battery (I haven’t actually tore it down, so this is partially still up in the air – it may be hackable. There’s an element of a pro here, for once the device did pretty much everything I wanted, to the point where having it continue to work overwhelmed my urge to tear it down to see how it worked)
  • Possibly a little too appealing to non-smokers who might want to “try” (and, in some cases I’m sure, still be “trying” It decades later) a convenient, safer, form of nicotine. Not that that’s really my problem or anything.
  • It’d be nice to have some kind of gauge on how much you’ve used it just then, equivalent to a cigarette running out marking a “normal” stopping point

Ultimately, racking up pros doesn’t really amount to much if one of the cons are “Didn’t actually have a noticeable impact on my smoking habits”, which is just a kinder way of saying “Didn’t work”. As an end user, I’m not really in a position to determine which, if any, of the cons might put this one vital pro in jeopardy. So in a sense, the short version would be “Pros: Didn’t not work – Cons: None that outweigh the pros”.

On AlphaZero

DeepMind, a subsidiary of Alphabet, the company spun off from Google to contain all the edgy research things (self driving cars, huge AIs, whatnot) has showed off another Go engine, that is also a chess engine. It’s extremely good. Here’s an article:

https://www.newyorker.com/science/elements/how-the-artificial-intelligence-program-alphazero-mastered-its-games

Perhaps unfortunately, there’s no real normal threshold to cross here – AlphaGo (an earlier but different engine by Alphabet) has already beaten the top human Go players. DeepBlue, IBMs monster chess engine, beat Kasparov at chess in 1997 – we’re 21 years out from top humans dominating at chess, and we throw out phones with enough computing power to school grandmasters because they’re annoyingly slow. So the news this time isn’t so much that AlphaZero won over someone new (though it beat all other top software), but that it did it in a different way.

When DeepBlue won, some people pointed out that we didn’t learn that much about intelligence, or humans, or chess. It was a fair enough criticism. Machines tend to be better than people at things on the basis that they have more power. Pushing harder, moving faster, completing more calculations more quickly, that sort of thing. In a few areas, that’s an easy (by modern standards) win – you can’t outrun a car, or outdig a backhoe. But you might be able to, say, paint a nicer looking flower, or determine another human beings emotions by sight more accurately. Or, formerly, play better chess, and read distorted letters to prove your non-robot-ness online. But those that fell like the last two didn’t fall to machines and software becoming smarter. They fell to shuffling the problem around until having more power thrown at it helped *just a tiny little bit*, and then throwing *mountains* of power at it. DeepBlue (and AlphaGo, the former Go champ) would pound through million after million of potential game board positions, trying to sort out which ones might hold a slight advantage. Humans don’t do that, and never did, and still play very well. Way better than any machine with a hard limit of evaluating perhaps a few dozen different moves, looking at most a few back-and-forth moves deep along each. There was, and still is, something about humans that still make them better, on an apples-to-apples level. It’s as though a human could run faster than a vehicle with the same size, weight, and energy intake – sure, we could still do what we’ve always done and just grunt and build a bigger one, and it’d be useful, but there would be a nagging questions of *why* we needed to. What is it that makes us faster? Well, nothing, because vehicles can move much faster using less energy, and we know why (for starters they don’t heat themselves to 98.7 degrees and stay that way 24/7 or instantly stop working forever), but with intelligence.. we kind of really don’t. We get the core mechanics of the deal, it’s a network of nerves, sending signals to other nerves, triggering some layers of chemicals with some back and forth. It’s not especially fast. It’s rather big, but not *that* big, not so that it’d win by sheer size. But the actual details are hard to see and rather obscure, too intricate and surrounded by too many parts that do nothing but not be in the way.

Algorithms improve, though. The best chess or Go engines couldn’t be what they are without some improvements in more generally evaluating positions without running them all to ground. That’s where AlphaZero has now made a serious advancement. It’s only trained against itself, and its evaluations are significantly shallower than prior engines, and it’s still better. In other words, it’s taken a significant step toward learning the way humans learn, and winning the way humans win. It’s not there yet, of course. The actual playing part of the engine is still closer to traditional engines than it is to humans, and the learning part is so computationally demanding that it’s not even worth trying to recalculate it into centuries of PC time or some other metric that’s supposed to sound impressive – it’s just above human visualization stupid lots of power. But even so, it’s a step *toward* functioning more like a human. It used to be that human intelligence had a 1,000,000 to 1 advantage over brute computational power, and we built winning machines by making them 1,000,001 times bigger. AlphaZero takes a small step in the other direction, throwing the power behind tuning up a system that can only needs to be 100,000 times bigger, and still win. And while doing so, it also manages to somewhat highlight what is different about a top human player (intuition, elegance, insight) as opposed to a robot (unyielding borg-like repetition, cold, unimaginative depth-and-precision strong arming).
This is still not the type of path that we can all explore, not with this level of demands. But it’s going to be very interesting to see what else it can do, when the same tactics get to hit other problems we solve by sheer force. Integrated circuit designs, road network routing, street light timings, turbine blade shapes, stealth airfoils, six-axis-unstable flight.. there’s a lot of things we build that are only possible because we can crunch numbers at them until something works. Because human imagination and intuition isn’t enough to “see” the elegant, clever, beautiful solution, and machines can only find the cold, pragmatic, by-the-numbers, sufficient one. What we see here is a step toward a remedy for that, a sort of finder of solution finders, and as a proof-of-concept finding at least a few that are much more like the ones we wish we could build rather than the best we can do while working on abstract problems that are too complex to reel back into human visionary space no matter how we try to reformulate them.

The international dateline

Someone asked me to write a description of why the international dateline makes sense. I didn’t totally get why it would as a kid, but eventually figured out a way to look at it that made sense to me. Apparently they were in the same situation, and it worked for them as well. Anyhow..
The international dateline is a particular North to South line (slightly zigzagged for bureaucratic reasons) that works like a time zone line, except instead of gaining/losing an hour or two, crossing it gains or loses 24 hours. It’s located mostly around 180 longitude (diametrically opposite 0, i.e. Greenwich, England), location chosen to interfere as little as possible with normal things, which is probably a thinly veiled synonym for “English things” or “European things”.

There is a reason we’re stuck with it, provided we use local time at all. Local times are set so that the sun is approximately as high in the sky as it will go at 12:00 noon. This used to be a lot more useful, but it’s still the norm. Moving with the earths rotation will make that occur sooner (as opposed to just standing there waiting for the earth to move you along), so moving east will put local noon sooner. Going “counter rotation”, i.e. west, will do the opposite. Since pegging “noon local” at exactly when the sun peaks isn’t precise enough to coordinate some things, so rather than define it as noon wherever you are, blocks of area will agree to follow a certain exactly synchronized time. The edges usually follow national or in-country borders of some kind, and usually agree on an even to the hour offset (but not always, 30 minutes off zones exist). Within these time zones, the sun will usually peak less than half an hour before or after noon, sometimes the desire to be “on the same time” as a larger block has larger offsets, but rounding it off a little.

So, lets suppose you stand at a spot, and then travel eastwards, a whole 360/24 degrees along the earth. You’ve moved over the equivalent of one hour, and indeed local time is now one hour forward from when you started. If it was noon when you started (and you didn’t spend any time moving) it’s now 1 pm. Sweet, things are going according to plan. Move another equally-sized chunk, bam, 2 pm. You’re two hours ahead, and all is well. Keeping it up, after 23 times, you move yet another time and.. you’re 24 hours ahead, and back where you started. And it’s true too – you did spin around the earths axis one more time than those around you who just stayed there. But you can’t have your own 24-hours-offset timezone. Well, you can perhaps, but the area you’re in can’t ambiguously be two separate zones at once – if everyone in your local zone is to agree on a time, including date and year, you must somehow come to terms with that you’re not 24 hours ahead – you must at some point *not* go one more hour ahead, but instead 23 hours *back*. It’ll all be the same to you if you’re merely looking at a clock (no date) – you’ll be at (say) 4am, then it’ll be 5am, but it’ll really go 4am, Tue Aug 7 to 5am, Mon Aug 6.

Or, if you don’t feel like overly complicating certain time zone boundaries (they were so nice and understandable after all) you could just designate a specific pseudo time zone line for just that – go east, lose those 24 hours of illogical offset you’ve built up the rest of the lap, go west, add them on. And that’s what they did – thus the international dateline.

Python reimplementation of cryptonights hash function

This has been a while coming. Like many others, after bumping into cryptonight, the memory intense hash function behind Monero, I’ve been trying to optimize it. As a first step to doing this, I started to rewrite it in full, and then immediately realized that involves quite a lot of fairly stock stuff that really isn’t time critical. And like (almost) everyone else, I thus dropped that and started messing with other aspects. But then, off and on, I did rewrite parts of it, until I decided to just gather it all up, fill in the left-out parts, and put it together. So here it is:

slow-hash.py

FAQ

What is this?
This is an implementation of cryptonights slow-hash in python. It has no dependencies, reimplementing AES, Keccak, Blake, JH, Groestl, and Skein in pure Python. It also comes with a small main() that runs an example case and checks it. It can be adjusted for before and after the upcoming Apr 2018 hard fork.
Why?
Mostly to have a single, self-contained implementation to base other things on.
Is it fast?
Goodness no. As mentioned, it runs everything in pure python. It’ll do a little less than two hashes a minute on a machine that typically does around 50-70 hashes per second using a typical implementation.
Can I mine with it?
As presented, no. It doesn’t implement a full daemon, nor a way to fetch work from pools. There isn’t much point, since it’s extremely slow. If you mean “am I allowed to mine with it?” then sure, feel free to, but there isn’t much point.
Can I base other implementation on it?
I don’t know, can you? (rimshot) Yes, certainly, that’s the point here. I don’t know how much easier to follow it ended up being, but by all means learn from it and use it to implement it in other ways.

On the new social media outrage

Since the temperature is rising fast on the need to regulate/modulate/curb the online information flow, social media in particular, I think it’s time to take a deep breath and think through a few things before narrowing the blinders even further and recklessly barreling forth.

Your media is filtered. It always has been, always will be, and in fact it *must* be. If you heard all seven billion humans at once, you would hear nothing. Somewhere, somehow, a choice was made. Drafts were drafted, editors edited, librarians curated, the deafening feedback screech of the world quieted, and you received information. It’s both the largest conspiracy in the world and no conspiracy at all, because it’s too decentralized to really be wielded by mortals.

You can’t just “choose yourself”. You can’t eat everything on the menu to decide what to eat. That isn’t an artificially imposed limit. You must, to some degree, go meta on it – choose people who will choose for you, or even choose people who will choose people who will.. and so on. But one thing used to be quite clear – to greatest extent possible, you should be free to do just that, not have it done for you. Unless, and this is where the clear ethical lines suddenly get squashed, you chose someone that role. But either way, some of these choices have gotten a little more accessible.

I say “a little”, because if you’re alive, it was never that hard. You could read the New York Times, or the St Petersburg times, or the Beijing Times, or your choice of a thousand other carefully collated chunks of data. You could hit a local library and read about almost any subject. You could change the TV station. You could flip through the back pages and have scores of very enthusiastic wingnuts drown you in Xeroxed zines with lots of ALLCAPS opinions. You can walk into an overpriced coffee shop at your local college, or at Berkeley, or NASA, or Yale, and partake in vibrant discussion. You could direct-dial any consulate, corporation, or even a random number, and ask if they’d mind sharing their opinions. You could write a really mean-spirited letter to your favorite government official and mail that bad boy right to their office. It was all there, and making them marginally less inconvenient changes nothing in principle. You weren’t information starved, nor silenced, nor in any position to just “pick all of it”. So what did change? Something must have changed, right?

There were a few subtle changes. You were usually guided (mostly consensually) by making you incur some form of cost, inconvenience.. for lack of a less dramatic term, pain. Pay for it, sit through a sales pitch, unravel the spin to make it useful, return your books, don’t hog the mic, renew your subscription.. They’re minor, but they’re there, and most of the choices are made by not choosing due to them. New media, instead, usually guides you (with your implicit consent) with rewards. Facebook found a person they think you’ll really like. Google is so convenient it can often literally give you what you were just about to look for before you typed it. Keep your snapchat streak going and we’ll brag to your friends about how much we like you. Tumblr will only show you the very finest funny cat videos. Carrot beats whip, and then candy cane beats carrot, and all of a sudden you wonder why you’re eating codeine-syrup-soaked cotton candy, and why no one is stopping you.

No one is stopping you because that’s kind of your job. Yes, FaceTubeInstaSnapGoogle could, and probably should, help you with that a bit by making your choices more explicit, more accessible, and more nuanced in terms of “I’d like for you to be *this* aggressive when you make my choices”. But you still pick the picker, and you need to own that. Just like before, the choices aren’t exactly medieval. Don’t chase facebook content you didn’t come looking for. Use duckduckgo once in a while. Hit some aggregators with more explicit and less fine-grained choices, reddit, blogger, reuters, stumbler.. Pick some RSS feeds, hang in some chatrooms. By all means, be judgmental, but take it up a notch and aim it at whom or what presented you with the information, not the little cherry picked atom of data and the random person behind it. Do what you did before – endure a little inconvenience, intentionally, in exchange for experiencing something actually new. Get used to the new telltale signs that you’re getting cornered or snowed. You know the reaction you get from millennials when you ask them to use a dictionary? Don’t be like that to their tools either – they require a slightly difference skill set to wield, but OMGWTFBBQ rein in the drama – it’s a tiny bit uphill, not a rabid squirrel gnawing your left <blank> off. Are you seriously wanting to ban candy because you can’t quit eating it? We’re supposed to be the generation of inner fortitude and character FFS, can we maybe act a little more like it?

Odd TX in the XMR blockchain

Just noticed these. The numbers kind of speak for themselves, started 16h ago, rare prior:

(reddit post where I say slightly more about it, and others may hopefully weigh in)

[EDIT]It keeps going, another 4000, still 3%%. Added another table, times will be odd since it’s “time since”.

Age (dd:hh:mm:ss) blockheight tx fee
00:28:39 1469607 73dbb62e9b5ba0a20eaf44c10d7dcec0766992205fea978805f8d4c1a5983a50 0.522
00:28:39 1469607 aa6574188ecb8d7722ffe11c0e8a6064ceeff8e726fb63a094a7996732e45925 0.522
00:45:01 1469598 ca4dc9b30bf6ba7e243d82cdf44080086aa214a1b0a296d3fc851022b4864317 0.522
00:45:01 1469598 54656b9068eed167f0a5cdc5ca12abacc7a92e7da9c802ebb66a2bd0fd45f370 0.522
00:45:01 1469598 ca4dc9b30bf6ba7e243d82cdf44080086aa214a1b0a296d3fc851022b4864317 0.522
00:45:01 1469598 54656b9068eed167f0a5cdc5ca12abacc7a92e7da9c802ebb66a2bd0fd45f370 0.522
01:00:52 1469595 a8624091c6cb41d73dab25b1a10fe043ac9805907184e5a139c80b8687a9878d 0.522
01:00:52 1469595 1ed74d2a613a1a42bf3c8c688b36de6de1ca04459d9db90ee9150837592cca99 0.522
01:08:46 1469590 0a6661a118611172c74d2895317af61f62553965e0c9ce424293922be9ebf3d6 0.522
01:10:52 1469589 a6b09c0142877f70abefffd7daa7356bf3b01b00c459e14039ea3055adc6bcfb 0.522
01:17:38 1469585 7ea6d970920e69b9a96796cdc3e6598eb7dcac2e9e344f39b10fef5bcd5355f5 0.522
01:24:08 1469582 258c4746023cc86fa095178f3ebb390cf1d4c5d3d80d8ee74cd1378a63d3bc37 0.484
01:27:36 1469580 b52d24532239cd65b461150f71e459aaf55908ef901cb2be1d1128222d1f9aee 0.522
01:31:35 1469578 43b5c9ac4f7d11da6c4644aeb4d756aef12cae311be8a00ed74239beae8dab80 0.484
01:33:48 1469575 bad18a3579c9bbac2ffe00d54fe40f958754c348c89709be66376da59bfd339f 0.484
01:33:48 1469575 301bb0b88aa24d06d693526fc33bf4e6a462b950b93a20618002b66a60206b6f 0.484
01:33:48 1469575 eb6015fef5bb3ccb4330fa503b9858826eb5a056a437228786992efc36430838 0.484
01:33:48 1469575 5cfa632e2849eb01f97297f877bf68460dfa16a110aa89a3f29946926bd83636 0.484
01:33:48 1469575 af4689b8af1ab4503f7e5dbb35e11ab47b7174a81c1db2781b52728802f4c6ed 0.484
01:40:34 1469573 5c825a29a7f3bd2beb68651e71a9bb94c0279a2108b66261fdcb0e0a2f967225 0.484
01:40:34 1469573 6ad0dfd11e239ffbaa6cfcf7c38854abecf7b1d57e2076ce160c94d3279d416d 0.484
01:40:34 1469573 d3e6941eeb80434d5441013896ef7be8a7e349a98b479de304df7c151c1adae1 0.484
01:46:33 1469570 6b4857c0e3cde072f5683698c8046c1b3a012763186cc27458bdab91e9fe4c2e 0.484
01:46:33 1469570 fd34a44f600b5f86483d89a834c8e23e7818613ce7dc4e156bbd82595fc0a71e 0.484
01:46:33 1469570 6f464ac41e7a9db0ca553fbd449351a58f0e7681dd4212a39eacc3ac2a5be519 0.484
01:52:11 1469568 f103cc1b857111961e99a5fbcfd9083558ac5458f63899ea8a1f3581e727c144 0.522
01:52:11 1469568 c08d7712f409af155915d7e0d24e018c11f2a4cfb65b0b5caaedad2b0ac63483 0.484
02:03:41 1469563 3ebf45fc5f8fd683037807384122817d5debfa762c7a7845cb7ccfe9ee20940b 0.559
02:03:41 1469563 ac0e66a1943547bda0519ac43d8f44f211c43560bc6edfd3dac8931972e50ea1 0.484
02:03:41 1469563 bf74753eaca995a54f12dfb405bb48b5127dd8a66d6b2dadc7a5c21ce497e296 0.484
02:03:41 1469563 e285cafefe6457ba060349dd9390fcf0c4cc36ded479a2aeb50aaaf475595bcc 0.484
02:03:41 1469563 2f6a81c0b2292dd0554f997de4d89428c96493efe62fe3810084c752bdcbad74 0.484
02:10:52 1469562 63ec4aa6f3d344740fb5edc2d579b4dffc576006d6d73123670097c70ebd0c27 0.522
02:10:52 1469562 c858baedc23e29ed3db77dd37d02ff9ea44f09de0002b4449b71a6356abd0ba9 0.484
02:10:52 1469562 df56211f001102ea0180be466e942818fba0a72fa9851e12f792022c82bf0804 0.484
02:10:52 1469562 1c4dcb673312b9833a090c0699bcece8a999cbf8eabef7742012dc174ad75a7b 0.484
02:10:52 1469562 2190f3562f859d3877c57bd500d1f70713896b6a0edfded25c3eaa3e1b5bcb68 0.484
02:10:52 1469562 4be3518d3a56f4274256e491e2ee495993fa3e7a6ad2df7e87d999bcd9959e2c 0.484
02:16:49 1469561 fd15e816ddd2b1a48769b43b178fc5c8f764faefd202bd5eef6b39513cbea384 0.484
02:16:49 1469561 0e34711e2d35adb0d3093134e5a2e8a568e2604380840b42d5f51cd3ab147f39 0.484
02:18:10 1469560 4b56de77b234c386820ce93b096089cf3d45dbc1c5a480973ca30451aab69601 0.484
02:18:50 1469559 c926a0cb77302dd299f246eb60e0a1fd410ad5529d6a2bf5c179a4d3504ff251 0.484
02:18:50 1469559 ca899ef51f557ae69b26b3b9a9b700716cade30729279c6ba1f9aa4cd2f54d17 0.484
02:20:04 1469558 901ed7e92f5faae07529fbe0dd229a413f44a27fd2116b84d09e0b4647b3ed43 0.522
02:20:04 1469558 a25ec3c21985b44485d89bd8e85aca567b0aa0712630539fde793bc9b0647e6f 0.484
02:20:04 1469558 44086e4fcac97cf7ee372bce5d9db75517a72b367759faa5899f45e4375520bd 0.484
02:39:31 1469550 5e22664b91344f4e32188e0dfc230a177b66b889b8e8a31534103afaa6a1f264 0.522
02:41:55 1469549 7dabac1b866ba6a4acd767f5c2e0aa32202aac1d2394f7bb42b90cc45d21b2fe 0.484
02:42:27 1469548 3595569d5f6b43a240539c77828930f9e4fba02a6bdc515f3f23ace6840caf88 0.484
02:42:27 1469548 ab2465147958507ee30144a1f5e0b6ee5a2cc6232ae4e312be0fdfc606eaba9b 0.484
02:42:27 1469548 0fb5e7578a7b7ccc6edd47b6a65735a5502109445bcecd30b18b8e9ec0e40d8a 0.484
02:42:27 1469548 1004e3db93f8caef54c15be85a202f736a14870e3504e4db286477951de91e9c 0.484
02:42:27 1469548 4530c5821dc81ccdffebf652edcbf7da6058459492f770b110529d502795896c 0.484
02:46:28 1469547 ecbf3fbaa2d2950981e066f4ce228f44bd402a1cf19e431207a41f903f4ee239 0.484
02:46:28 1469547 6496a31c201e974cf646b827a46769985abe5c3a12dc0426c6dc9206e55437d9 0.484
02:48:22 1469546 1fdf186e7234a4f2c20e87452bdbe3c34aace62eb404df32979514c03f922a0b 0.484
02:49:01 1469545 8051eb4d5b0440d14b5a598d01fdd1d6427ce68bce59bcc71b900a58c65ce4c2 0.484
02:49:01 1469545 be27665ca46bb855d8f5de6c31fa4d8a3e82ede004d33f95cfc8ae852ce67b76 0.484
02:49:01 1469545 e9412f73d6b4471ca9822efaf0addf7c734dc3b40466a11894d98a5b384b0e7a 0.484
02:49:01 1469545 dd06097b884f0a377e7d71f7f22e92c909ea13db1a0e59dc09e21f9b00825599 0.484
02:49:01 1469545 2e00a0d1005797d1b5655398acfe0362143b68d5984634fa14d712f9b7cc2033 0.484
02:49:01 1469545 dc9e5d962ac9df18cd6e2343522b4eaeb2076ba4aabd9083fc825bae283696a8 0.484
02:49:01 1469545 f22ac7c41a18f5e1050f4a447972618a3fa44986a7c7ba9998dafe296fbad4dc 0.484
02:49:01 1469545 ccc156ca519ff602ef19670b53ba9126b1935da31feb07f7aa9187ee749d1243 0.484
03:03:47 1469541 9bc72e996e5404b9816160dc397893830933b29c6e617a486f12730125198a91 0.484
03:13:43 1469535 b7a522b1ee16a650b62aa4a01cfb54696b1000344e958d8b153536c984bb25d4 0.484
03:13:43 1469535 ef3ce934067993d4527e00ebbe7c5f551d85b59c49c0e32106731f5a9a73de82 0.484
03:13:43 1469535 df8e1c8827cf19953184ae66ae30e1f13dc07cf65a2871764223f5120ee649cf 0.484
03:16:55 1469534 c787fc5aeca2d5b8ed8de8b3aef2e85147120b48fa474f1de73bbcbe607577d2 0.484
03:16:55 1469534 324f84fa5b24432c2bd64e2aad2d875a3409075b79c9cfce2e52668630e0a218 0.484
03:16:55 1469534 88d663f35ef449fbf05bc92b6ab487c95a3b105da8a99ccf174dde2b3d4eae37 0.484
03:16:55 1469534 22fd02a8685d1c93edc5ed70b84a575a4c9da8447bf288f21baa30e5d5e7b973 0.484
03:16:55 1469534 4858b4df5afd5d614cf8c1f0031aff7cd69c454237cfaae252240e357bd53160 0.484
03:20:39 1469533 4921ffad7b141d7a50ddaf8d2f04c637d3273d67906c4960c17e8c5031f97824 0.522
03:20:39 1469533 4dc8805a6ad864ab4b72bc2d808bca0d630c5bf8b26587d2891d866c5ca85e0a 0.522
03:20:39 1469533 a1693db02faba90c8f381c4ab4cea9e39916188c9e87bfbf2213be29376c6934 0.522
03:20:39 1469533 049882f362c1802b60d4d65dcebc7fe6f6b25e3b58d7b7dfcc17523e1f759fb2 0.522
03:20:39 1469533 b4b59ac3ffbe0fce38b232f9f18d55f68d2b8ad7a7adf34e2dbf967fc63c9518 0.522
03:20:39 1469533 e4feb9fc2779b4ff21954756f25362634ffb5a022c0dd052277797a5003575ef 0.522
03:20:39 1469533 d47b75e4939d9f4651bd5b35134dc30434e9aae7a0cdc07c32c7ff8d4018f7a3 0.484
03:20:39 1469533 c748f697bd1f222df5b38f70d347e7ad236b6809a4bc380aafa6edeed0260edc 0.484
03:20:39 1469533 70cb8e27a66ef1da22c4bf579912742ca36240f846fe4905e3a8f81ed095c714 0.484
03:56:07 1469513 72fa2f761a423b537094f6b6f8f430871604e87bd1029895dfb1808e22f197f0 0.522
03:56:07 1469513 d238c444547f245c4274142726841219827e6df909701e89debc3e17da8e4018 0.522
03:56:07 1469513 9823d601b131c06a05296562ff3441d3e3f1917682f933f193e1a330a8dcd155 0.522
04:00:24 1469512 6090c0574f61bdc66c36b097981a9449258e9d030cff26b488c4db0f56b1b5af 0.522
04:00:24 1469512 7b5d1113c267b986131c8697138f8c5e6099270854fcb59a5afd757a979a0c30 0.522
04:01:44 1469511 03b004775e9f323e1e5a844eb71caaad3c92fd7b618b780cba7fd5a97f9153f9 0.522
04:01:44 1469511 bad051a8cf0244c8c4989a697b922c3b39b307a0de8adfe698f782ca68280b2d 0.522
04:01:44 1469511 6d500cac6fe121bfab0d3a59a56e07e3c3ad25a333e11a56cfbdfe77e7f669c6 0.522
04:01:44 1469511 75d1652a95575e8fce6f50cf818a2e22e141692a3848cfd9cb6738f58d24bb33 0.522
04:01:44 1469511 0d6ad265572960a0a91efccc30468dde54f11d59b85f25b59f5214fb0a55a038 0.522
04:01:44 1469511 eb7dd55b9800e5729fa44cc4eb231bb38e26a504ed3425df1846071bbaaae1cb 0.522
04:01:44 1469511 883c9558bc6d7e76dd3c288d0f2523b96c8ccbe3e2c3377284eed035af6d2efe 0.522
04:01:44 1469511 ae70bc661cbc4198d47f558c0d066f0a0c4595912fca72e93766597316a1c13c 0.522
05:01:33 1469494 951a56061fa274efaaa7832ff14fc5df86fcf5d8d3a796066498ede77ac44d20 0.522
05:15:45 1469487 fa0fee90b0f315ce7d76c9995d54d27789366d3195a9227ef4132d833b6d634d 0.522
05:15:45 1469487 672cb7963488d82699dc270410a1960e10f0de7cea2dfa2d8816452531dc0bba 0.522
05:27:46 1469480 bad1adc03e3f790ee6d6d8605a38cdcfb0c53c19bfc808d5edf5854f76af5e5d 0.522
05:27:46 1469480 50012062b0eece3828c86fa67cbade3d9d4f96570bbf192228d524a48770513f 0.522
06:50:03 1469441 ae60d56cb6aa24674b9ea76a67b0a7a099655ba034d4d26ad8706b9df6798a50 0.522
07:15:46 1469429 7a0920508136d9764c5e2749f8fb031979f2f64325f067c215dc62b6824f1b87 0.522
07:33:35 1469417 d3727473f722202459e5168c1abd95c0a2c13de260182a174aad4d4fb9e6c25a 0.522
07:52:39 1469406 60cf857f76898f107c3423fad058a445f9e9f262ddf550a67553338c33cf3335 0.484
07:53:28 1469404 d6f51f1b52bb98eed9241e2b2b4a8bcddd506c5868c5a67eb493acfeb1e724ef 0.484
07:53:28 1469404 4ed611cd1f5755f87f5eaf3193df27b29ad1fb0d375bbf164b7f0b13b5e9b41b 0.484
08:14:57 1469399 6ef37df5859b61fe333975855705d36033deab8ddec96218913693c2c8bdae4c 0.522
08:14:57 1469399 7a609d2793307ac1e4385e192ee3fe176af273d5698cc14b9f979a7787bd101b 0.522
08:14:57 1469399 03333224640660d8c0a4e25ee42d46185de762e68e2494b903bb9f06cb143ed4 0.484
08:14:57 1469399 906fd41ca12c497c521f5e65a448611875ecef11630f4f8623cdfb6a97a28b8a 0.484
08:14:57 1469399 69bc6171de98bff14dd89b7bccb5b38ff8edefc21b17624b80cc6985429385ac 0.484
08:14:57 1469399 a443f5b20d013d0c4fb6578383b417bb110173b0128f4a08513e70534078fb81 0.484
08:27:26 1469398 33453890560db9dd511db3ec16c5917ad301f39d5abd437e1618ebf2b7a33d98 0.484
08:27:26 1469398 8d2742b9a1c44c63e0955f4bcf47c200fa0ab35c6cccaedb6c9c073b92cfa9cf 0.484
08:30:22 1469397 d4788eace14351375ba627609862386bdf813fbd2aea0ce9e3362cb2aba48ba0 0.484
08:30:20 1469396 746bcd11988f562c30e886954435c51fb611c226dc914d1e05accbf715f93561 0.484
08:30:20 1469396 3602d32eaf09e998fda6597a7263e6c5e88a0d7c425575a5e931e4ae66804023 0.484
08:30:20 1469396 99c59450d50db1c21ac79ce1b90373361cd0fd97f3588a587ac4e95ef625cb71 0.484
08:33:18 1469395 7cddfde3318a6966b9fd2cd2bef5b05a24259aa9b5e5406cb745914c82f5a245 0.484
08:33:57 1469394 027f74eb9be84411171e1a065ccc197321872a2e9a36f92daa76e2715d25343a 0.522
08:33:57 1469394 16d5893817e61f158ef5c775e4e76aa33e9792bbc5a0cd35753cb8ef18fc1cac 0.522
08:34:56 1469393 0a3c4434c2b48e5c1c22adc69d47d3f34796a399b44e8cd41d096ca43df69159 0.484
08:34:56 1469393 a70f03698243e853fd93176c35263ba0fd31f05d80a41c27ab405aac2c9c2ec7 0.484
08:34:56 1469393 0450b668c562d73a12ff083f45a218ada6e109ea48c4f2fb094f497174da09cd 0.484
08:34:56 1469393 4776dab2abc5643ed4e6a5cb2fcdcce28e8939febc9e5bb29354c89ffcbabe34 0.484
08:42:49 1469388 bb3f4b83dfabbde4e38bcfbe0cc59e85c77008408ad6a429eb45282a3a256172 0.522
08:42:49 1469388 3aee63d5ad879994290de9a90e1131539234abbcd490ff664d8d776d4f090f27 0.484
08:42:49 1469388 1f73eb7acef2551acea24e8bdf1369d9fa831359847519173441f436d8e38810 0.484
08:42:49 1469388 9d083a1833864e39281431cfe7cb33e0f3b6cad28f9dd3372a770319cb986929 0.484
08:42:49 1469388 8a897158c409b6f61817ac845d1e0c597f30b7f2349b45d2eea7fd240df457cc 0.484
08:49:36 1469384 def535a5bdc4a3316a71932d65a32361c6b9f2735de25d22a5f936a12e4b4470 0.484
08:49:36 1469384 455b5f51fd85140eeedbc97ee964f8f4003cb6a87fd3fe0f337409611038129d 0.484
08:49:36 1469384 37705c50eafc8c26dedc56fe4ee0e410a285e99585b07725328a4f4f31257c01 0.484
08:49:36 1469384 f8aa6e4d35a157f4b1dac4070be5b43aaa7e132f9682704de23183f2eeadf8ff 0.484
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15:36:22 1469176 6e6fe937122c10420583f164ff5d4cdb5a6101539d9945955875ddd34e211d9d 0.522
15:37:49 1469175 0e12198c73b65a6bfcb0434722dbc5a9c256b23fed4d816cef4d1e5e77235b6c 0.522
15:37:49 1469175 bfb1aeeea06228b5318756b8491e07f7c71d386f57d2d0911585ae4ced9d2bde 0.522
15:37:49 1469175 7b0739ae63c3dbc11450513d33f74f8b7823166d174ce50b8f720c7f6fe1bdbc 0.522
15:37:49 1469175 e3f62d5e45f937d446b9fdf5999afef3a237d4970149378c950dbac8f6932b39 0.522
15:37:49 1469175 fdaf1647addba015e75ce442d4ec9d9fd668b4dae36f043b1ec2a5331f0ddea7 0.522
15:37:49 1469175 49664a894e65266f55035b967f7d222e388b4e27419360fc571971853c6d604b 0.522
15:37:49 1469175 cd361b046dbe10ddbc0a186a2ca19b7521d43748a553e238ffb35223b6cc072e 0.522
15:37:49 1469175 477a7e136da00f2a8884acd47497af134e0d87ef178bf0d414cfcebb2ee4bf9a 0.522
15:37:49 1469175 983f0166764b1cde9e6c9cf1536dd0ee05849c62f21e6705744d9437e39bc0e1 0.522
15:37:49 1469175 db404e18b179975f1eef0609fc711f3e899d62402043bb04363b709c7804d99a 0.522
15:45:36 1469174 b076fb23eeb38ccac77cd3d7999729142cba681e67dfcc20e62548bb8a43325b 0.522
15:45:36 1469174 d72dbfb3e727bf64fa895c946c17d4bbea9283daa3a5b515d0ce96eab2152b54 0.522
15:46:34 1469173 9bd38638a44c79be38b594ef23ecd1e99ca5d45641d6c26740e22c42ad3de180 0.522
15:47:26 1469172 437db3c81feb1683b2c125fac6ef4731066be591b410271c7647d7a43526f2d9 0.522
15:47:26 1469172 6d618067fb02050903d244a8f6561eb86c1bec1805dadb233c44224b729dea98 0.522
15:47:26 1469172 5a58a04c9021eddb636bb427920e2946bba459d96ae382219a8ee5a37b53d4c3 0.522
15:47:26 1469172 af9a7b14b0146bf0131822095f86e0230b55a1c3fa8635da5614971dda43b503 0.522
15:47:26 1469172 f4ce6b1ee442b11ea2637f290641890d969a0cf13a7673349e126f8431bc1f24 0.522
15:47:26 1469172 83fc3803516c0ff0386074b7aca4d61e6861da1109d722df16a14e95dbb0b3c2 0.522
15:51:07 1469171 d0b7f4249a0952411a66b673485cd180396b4066e2471ef3bbadf2d03aa06da8 0.522
15:51:07 1469171 854fb5520b1333b26c0ac5b9e735e0c41539c33e4e463577c68e56978e48ae78 0.522
15:51:07 1469171 92d649c83dc1a5b78fd25a9ee305b933a2efcf3ea9d01e0f5c396423f793146b 0.522
01:01:17:29 1468877 2ad74a0247b6ec2c632bed7971bd7b23c03894e43903eb2986fc7c8fc832cc3f 1.082
01:01:17:29 1468877 ee6e10f5de947def599eaf001a3db318eec4f168e11207a924ba644cd9b7e48b 1.119
01:01:23:46 1468875 175a803b80369c0ecbd3b59a88536993401ab6aa8ba08b60fdc1ab3ce0dc5066 0.522
01:01:23:46 1468875 142bbd16e823fda1c77ae1ef1e01aed11f99a21567bc2e65315020a829fba884 0.522
01:01:23:46 1468875 943f458475f695d352af959f41ca6512c41710b64c4ffaf5b0d8b72ca3aa2b4d 0.522
01:01:27:50 1468874 d6867b9ccf91624aa52e1e9095eb3f2f060362dfca7e1a75e035fa690730de72 0.522
01:10:36:20 1468586 6ef15717267f00f0c951e6fc2eb606e4801df8c224383e8488c33b6b4200b2e7 0.523
01:15:10:20 1468484 270dc7d66528308fbac0691968c452c8c3bff9fd4c8999b997481ca818a3943b 0.523
01:16:24:28 1468442 2ebdd7d7c325584459d6ccd44c2836ca07d3917f43df3aef2b4e9e1517176b8b 0.523
01:16:24:28 1468442 69363a1b7ac6e1324d38ce3dc61804f66af1c1a39b63d1511a00ba6494c96278 0.485
01:16:24:28 1468442 5fb8dce83d8695f8efd06a605655b564d19d1ca6dbc69bcdb015f6702ced1e8f 0.485
01:16:37:23 1468440 2c471dc7bc037e3ad052377b951fba1657da1f347fc232f9736ce270e3ac01ce 0.485
01:16:38:05 1468439 a1933d03a1f59f4ec5bd8b74749027a49ff64611cda30fec0230e20b41f90d76 0.523
01:16:38:05 1468439 048ffbaaed79d6c3b3421ad6b8ca7473488769a547a99b89f7ebeb6235ef4e5a 0.523
01:16:39:39 1468438 ca73e9ca5e45f1432b5f5ab06b3f8683fe1cb1f86cfd01a0546b72f2f1d97ea2 0.523
02:02:42:35 1468125 cc4c094ebd9d79f180d23ca1b727e6df4165cf9176059d07889b861bc8f2c5c8 0.523
02:02:44:15 1468124 19beb38f6d4f191940f42800c72da3f8ba7579f21a4e820090b75371edb5d3d9 0.523
02:02:44:15 1468124 b0c5e05e2dd5e44af4bf43dd973d3e34bb4146a11189cb191956ce9f065a8ab6 0.523
02:02:44:15 1468124 a7309342e41580c65d41e3244fe4f59833254a592edeccaf66b3a4c47ea7058c 0.523
02:18:08:18 1467684 3b0d7ac4f17399a8b6de39df43a670436ac42bf824f56a565a87cc9ae31259b7 0.523
03:07:14:51 1467268 69e31b973a9726b071d9b44b447f9c005f7a893111f6d0351cba87733e9fa03d 0.486
03:16:13:52 1467011 4c0205de7ec2245fa41adf336864989f3e2588dd604e5b25364ac50080ff4502 1.423
04:10:59:15 1466441 3e120b71e0b377a05890751a4e8a825e0ee3d519a1528289212175368ae2e086 0.487
05:19:45:35 1465444 5eb60b912891625dca5d0acbdee034bb51eca344713655657e5ce92c6e8fc560 0.526
05:19:49:24 1465442 ac93f2e71780e36eed79bc3140c6ff8ea3f1f59a10ecc4f2276d308a90ba4db3 0.526
05:19:49:24 1465442 4b0ed6741d7cb64261612013a28d97807b5d825fec328554fe2b2e02b586d8ea 0.526
05:19:49:24 1465442 86702becc912c3606fe49be476170667bb411a4f88120edd60d45944f328032a 0.526
06:07:45:36 1465036 3a4127f6e3b3ee7e0cb426b1edea6892eafddf5e24fbcba3ded72f199417f1d0 0.564
06:08:11:21 1465016 5a51a8fa1375817efe45a35618ec0b3eacec75f67ebd1ba1bb445aff483faca7 0.489
06:08:37:43 1465001 b30715fba380b2d1801505a251583d312be3d6c0869f5710fe60b44d25272433 0.714
06:14:26:59 1464805 422b40d87d42ec9c3ebbb229525ec97209b5f8e3e9728c0e6cb2c81165146645 0.526
06:14:26:59 1464805 5fd0151ee72e97c4f45dde8e3a4a468fdae7ab99947507f9b8a4f2996b4bf273 0.526
06:14:51:11 1464798 5c6fc9a4c34f90b0c4a3669f5cd585af9ee8bf1c00227d779ab296369f752e49 0.526
06:14:51:11 1464798 84f97ea6dcbcbc0175df718dbae3994133554e9a0a697f6d39df8c11c61493ac 0.526
06:15:51:10 1464765 6ebb39817a457d5e74b83f371378a1c36fd7836463ca122ab0e7aba1a5ce5446 0.489
06:18:36:15 1464691 938bcfdc2269038da53dfd7727eb903c67295db0673f3e85010951c8e753ebcf 0.489
06:18:59:04 1464679 f2354671ed405eb3a9fade7f8388e7fd4ec3978bdfa1d48d471e14b2226157af 0.489
06:19:23:23 1464666 27af22d92e3ae587b1ecc560f2554003cc95dabd12437f2eed79df057e56c54d 0.526
06:19:40:58 1464660 fa58aeb999f91c9413750ca6c5a09f0a333946491479dff8228bf273fe0438c4 0.489
06:21:51:08 1464585 6be16de815fed2cece4e75e8cc85008c77cb129bb736c1f44ea1abda767dcf9b 0.489
07:18:41:04 1463976 f06b8ba467504facb3bbf867908c3c96b520a0138f2074572c1dd5eeca9a36d9 0.527
08:00:17:57 1463824 9f8c5462ec35a397f5243b8d1d455de2778add009c7d5a1de6ddb9828a7f5607 0.490
08:10:24:55 1463516 a60e91e2817f580baa4c97ff3206eec2ea4be90490e050754831d4c943825109 0.528
08:13:40:27 1463421 6919a7910d6778918dcd69f3367c541fe78cb2b7e23f0579fc450c0ce2bf1154 0.595
08:18:15:33 1463284 2ae5a64fd8f28610c61bfc4ae159effa6fa91976b6765fd0db4d3fb6a30d85e3 0.566
08:20:18:35 1463224 26b74b9bf19d586102cfdd481a02921fa1ecbed99384ee15bccd93eacc653514 0.528
09:00:31:51 1463092 f72a320b2941292ed66d12edf1facc31a022597b6e14e9d2a97380653675dfe5 0.528
09:15:19:02 1462642 bb55e8464da9d4c1953de44fb7269c8dc8cad6966a8c0693e8d6534c39e96806 0.528
12:01:26:08 1460904 cde5d861bb29dce12cdf2a5e41e7f6f17f8fc7290e801472a2e081944b4875a4 0.795
13:18:58:55 1459699 4a1305ff66d4de169e48ce1b9f804ecbe7b24f7ed0703781bae0830006e2c523 0.389
13:21:25:31 1459627 4c31d53b787a8d972d583acb6d76fedadc649fc579a04a32a6a636a6431ce8ad 0.532
13:22:05:23 1459614 297a394a03d31ccf15ec28ac13ddbaf4f180e2e1eafd9603c3972b5f2507b8c0 0.532
13:22:10:40 1459612 2d8c179ef6c9a4316bd6f0738eefe3265732d9867c4553f81e4574b66b7c199e 0.532
13:22:57:51 1459591 c059d2cec4d848be4e5084abb3ed510e7be9f12c093ae91e339e159bfaa02aaa 0.532
13:23:16:48 1459577 2c924af977814183c8b8f7c20614fa3995ec8c497f3e3c3afd4216da5ca75e38 0.532
14:00:03:10 1459543 51115e373454ea7de15b8ea430e941fcae212e6212cf225c83961af7feb3a34a 0.532
14:13:34:42 1459089 dce9fb468a5c9cfd5d60946a6f8f66708f7d4adcc5134cce39cba4b1a8731c52 0.553
14:20:41:47 1458886 6e12055de0eeea3fe65d79c658a5837fb1615286a7795706ed2549b80d5796a6 0.608
14:23:12:55 1458809 24c3457bc5842092ca39e909c1d7d41f067632defcae877ae7ad4dd93372b5cc 0.596

(.. and some more, these from the perspective of 10 hours later)

Age (dd:hh:mm:ss) blockheight tx fee
1469607 00:28:39 73dbb62e9b5ba0a20eaf44c10d7dcec0766992205fea978805f8d4c1a5983a50 0.522
1469607 00:28:39 aa6574188ecb8d7722ffe11c0e8a6064ceeff8e726fb63a094a7996732e45925 0.522
1469598 00:45:01 ca4dc9b30bf6ba7e243d82cdf44080086aa214a1b0a296d3fc851022b4864317 0.522
1469598 00:45:01 54656b9068eed167f0a5cdc5ca12abacc7a92e7da9c802ebb66a2bd0fd45f370 0.522
1469598 00:45:01 ca4dc9b30bf6ba7e243d82cdf44080086aa214a1b0a296d3fc851022b4864317 0.522
1469598 00:45:01 54656b9068eed167f0a5cdc5ca12abacc7a92e7da9c802ebb66a2bd0fd45f370 0.522
1469595 01:00:52 a8624091c6cb41d73dab25b1a10fe043ac9805907184e5a139c80b8687a9878d 0.522
1469595 01:00:52 1ed74d2a613a1a42bf3c8c688b36de6de1ca04459d9db90ee9150837592cca99 0.522
1469590 01:08:46 0a6661a118611172c74d2895317af61f62553965e0c9ce424293922be9ebf3d6 0.522
1469589 01:10:52 a6b09c0142877f70abefffd7daa7356bf3b01b00c459e14039ea3055adc6bcfb 0.522
1469585 01:17:38 7ea6d970920e69b9a96796cdc3e6598eb7dcac2e9e344f39b10fef5bcd5355f5 0.522
1469582 01:24:08 258c4746023cc86fa095178f3ebb390cf1d4c5d3d80d8ee74cd1378a63d3bc37 0.484
1469580 01:27:36 b52d24532239cd65b461150f71e459aaf55908ef901cb2be1d1128222d1f9aee 0.522
1469578 01:31:35 43b5c9ac4f7d11da6c4644aeb4d756aef12cae311be8a00ed74239beae8dab80 0.484
1469575 01:33:48 bad18a3579c9bbac2ffe00d54fe40f958754c348c89709be66376da59bfd339f 0.484
1469575 01:33:48 301bb0b88aa24d06d693526fc33bf4e6a462b950b93a20618002b66a60206b6f 0.484
1469575 01:33:48 eb6015fef5bb3ccb4330fa503b9858826eb5a056a437228786992efc36430838 0.484
1469575 01:33:48 5cfa632e2849eb01f97297f877bf68460dfa16a110aa89a3f29946926bd83636 0.484
1469575 01:33:48 af4689b8af1ab4503f7e5dbb35e11ab47b7174a81c1db2781b52728802f4c6ed 0.484
1469573 01:40:34 5c825a29a7f3bd2beb68651e71a9bb94c0279a2108b66261fdcb0e0a2f967225 0.484
1469573 01:40:34 6ad0dfd11e239ffbaa6cfcf7c38854abecf7b1d57e2076ce160c94d3279d416d 0.484
1469573 01:40:34 d3e6941eeb80434d5441013896ef7be8a7e349a98b479de304df7c151c1adae1 0.484
1469570 01:46:33 6b4857c0e3cde072f5683698c8046c1b3a012763186cc27458bdab91e9fe4c2e 0.484
1469570 01:46:33 fd34a44f600b5f86483d89a834c8e23e7818613ce7dc4e156bbd82595fc0a71e 0.484
1469570 01:46:33 6f464ac41e7a9db0ca553fbd449351a58f0e7681dd4212a39eacc3ac2a5be519 0.484
1469568 01:52:11 f103cc1b857111961e99a5fbcfd9083558ac5458f63899ea8a1f3581e727c144 0.522
1469568 01:52:11 c08d7712f409af155915d7e0d24e018c11f2a4cfb65b0b5caaedad2b0ac63483 0.484
1469563 02:03:41 3ebf45fc5f8fd683037807384122817d5debfa762c7a7845cb7ccfe9ee20940b 0.559
1469563 02:03:41 ac0e66a1943547bda0519ac43d8f44f211c43560bc6edfd3dac8931972e50ea1 0.484
1469563 02:03:41 bf74753eaca995a54f12dfb405bb48b5127dd8a66d6b2dadc7a5c21ce497e296 0.484
1469563 02:03:41 e285cafefe6457ba060349dd9390fcf0c4cc36ded479a2aeb50aaaf475595bcc 0.484
1469563 02:03:41 2f6a81c0b2292dd0554f997de4d89428c96493efe62fe3810084c752bdcbad74 0.484
1469562 02:10:52 63ec4aa6f3d344740fb5edc2d579b4dffc576006d6d73123670097c70ebd0c27 0.522
1469562 02:10:52 c858baedc23e29ed3db77dd37d02ff9ea44f09de0002b4449b71a6356abd0ba9 0.484
1469562 02:10:52 df56211f001102ea0180be466e942818fba0a72fa9851e12f792022c82bf0804 0.484
1469562 02:10:52 1c4dcb673312b9833a090c0699bcece8a999cbf8eabef7742012dc174ad75a7b 0.484
1469562 02:10:52 2190f3562f859d3877c57bd500d1f70713896b6a0edfded25c3eaa3e1b5bcb68 0.484
1469562 02:10:52 4be3518d3a56f4274256e491e2ee495993fa3e7a6ad2df7e87d999bcd9959e2c 0.484
1469561 02:16:49 fd15e816ddd2b1a48769b43b178fc5c8f764faefd202bd5eef6b39513cbea384 0.484
1469561 02:16:49 0e34711e2d35adb0d3093134e5a2e8a568e2604380840b42d5f51cd3ab147f39 0.484
1469560 02:18:10 4b56de77b234c386820ce93b096089cf3d45dbc1c5a480973ca30451aab69601 0.484
1469559 02:18:50 c926a0cb77302dd299f246eb60e0a1fd410ad5529d6a2bf5c179a4d3504ff251 0.484
1469559 02:18:50 ca899ef51f557ae69b26b3b9a9b700716cade30729279c6ba1f9aa4cd2f54d17 0.484
1469558 02:20:04 901ed7e92f5faae07529fbe0dd229a413f44a27fd2116b84d09e0b4647b3ed43 0.522
1469558 02:20:04 a25ec3c21985b44485d89bd8e85aca567b0aa0712630539fde793bc9b0647e6f 0.484
1469558 02:20:04 44086e4fcac97cf7ee372bce5d9db75517a72b367759faa5899f45e4375520bd 0.484
1469550 02:39:31 5e22664b91344f4e32188e0dfc230a177b66b889b8e8a31534103afaa6a1f264 0.522
1469549 02:41:55 7dabac1b866ba6a4acd767f5c2e0aa32202aac1d2394f7bb42b90cc45d21b2fe 0.484
1469548 02:42:27 3595569d5f6b43a240539c77828930f9e4fba02a6bdc515f3f23ace6840caf88 0.484
1469548 02:42:27 ab2465147958507ee30144a1f5e0b6ee5a2cc6232ae4e312be0fdfc606eaba9b 0.484
1469548 02:42:27 0fb5e7578a7b7ccc6edd47b6a65735a5502109445bcecd30b18b8e9ec0e40d8a 0.484
1469548 02:42:27 1004e3db93f8caef54c15be85a202f736a14870e3504e4db286477951de91e9c 0.484
1469548 02:42:27 4530c5821dc81ccdffebf652edcbf7da6058459492f770b110529d502795896c 0.484
1469547 02:46:28 ecbf3fbaa2d2950981e066f4ce228f44bd402a1cf19e431207a41f903f4ee239 0.484
1469547 02:46:28 6496a31c201e974cf646b827a46769985abe5c3a12dc0426c6dc9206e55437d9 0.484
1469546 02:48:22 1fdf186e7234a4f2c20e87452bdbe3c34aace62eb404df32979514c03f922a0b 0.484
1469545 02:49:01 8051eb4d5b0440d14b5a598d01fdd1d6427ce68bce59bcc71b900a58c65ce4c2 0.484
1469545 02:49:01 be27665ca46bb855d8f5de6c31fa4d8a3e82ede004d33f95cfc8ae852ce67b76 0.484
1469545 02:49:01 e9412f73d6b4471ca9822efaf0addf7c734dc3b40466a11894d98a5b384b0e7a 0.484
1469545 02:49:01 dd06097b884f0a377e7d71f7f22e92c909ea13db1a0e59dc09e21f9b00825599 0.484
1469545 02:49:01 2e00a0d1005797d1b5655398acfe0362143b68d5984634fa14d712f9b7cc2033 0.484
1469545 02:49:01 dc9e5d962ac9df18cd6e2343522b4eaeb2076ba4aabd9083fc825bae283696a8 0.484
1469545 02:49:01 f22ac7c41a18f5e1050f4a447972618a3fa44986a7c7ba9998dafe296fbad4dc 0.484
1469545 02:49:01 ccc156ca519ff602ef19670b53ba9126b1935da31feb07f7aa9187ee749d1243 0.484
1469541 03:03:47 9bc72e996e5404b9816160dc397893830933b29c6e617a486f12730125198a91 0.484
1469535 03:13:43 b7a522b1ee16a650b62aa4a01cfb54696b1000344e958d8b153536c984bb25d4 0.484
1469535 03:13:43 ef3ce934067993d4527e00ebbe7c5f551d85b59c49c0e32106731f5a9a73de82 0.484
1469535 03:13:43 df8e1c8827cf19953184ae66ae30e1f13dc07cf65a2871764223f5120ee649cf 0.484
1469534 03:16:55 c787fc5aeca2d5b8ed8de8b3aef2e85147120b48fa474f1de73bbcbe607577d2 0.484
1469534 03:16:55 324f84fa5b24432c2bd64e2aad2d875a3409075b79c9cfce2e52668630e0a218 0.484
1469534 03:16:55 88d663f35ef449fbf05bc92b6ab487c95a3b105da8a99ccf174dde2b3d4eae37 0.484
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Tello.com

General FYI – I’ve dug through the mess of wireless providers (as I try to do on a biannual-ish basis) and this rounds winner is.. tello.com (currently +coupon 15OFFAFF -> 15% off)

Cheapest possible “has a working number”: $4.98/month ($5 (plan) + $0.73 (BS surchrages/tax) – $0.75 (15% off)
(give 100 minutes, unlimited texting)
“Internet of Things”-slave device: $5.98/month ($7 (plan) – $1.05 (15%) + $0.73 (BS))
(give 200 mb 4G/LTE (~5Mbit) then indefinite 64kbit 2G/1X, unlimited texting, no calling at all)
Resonable minimalist use: $13.48/month ($17, -15%+BS)
(unlimited text/voice, 200 Mb 4G)

All functional sprint phones work, most get in even with unsettled accounts/sprint blacklist (no official word on what’s what, had a few denied, a few accepted). Boost phones with more than 6 months cumilative on-network use work, some decrepidly old never activated work.

Pros:
Tethering explicitly allowed, including while on 64kbit. USB, bluetooth, on-phone hotspot – no problem, any data welcome.
Switch phones whenever, no human involvement. Just fork in IMEI online and wait two-three minutes, dial ##72786# (reset provider), bam, done.
Porting in number from Sprint continually went super smooth and without human interaction – acc # + pin + phone# + exact name and address, five minutes, reset provider, done.
Cons:
Autorenew required – needs disposable/virtual CC or cancel for one-off lines.
Asks for a phone number that can’t be the one you’re just now buying for billing (doesn’t appear to verify how real it is, but still corners you with “No, we need your phone number!” vs “I don’t have one, hence my intended purchase!”)

Pro or con depending:
Charges $10 for new SIM cards. Some Sprint SIMs transfer, some do not – those that do not costs $10 takes a 2-day mail round, plus exposes your real address (or locks you down to 3G or less data == no 4G/LTE burners). On the plus side, they do in fact 2-day you a functioning SIM no questions asked, no human interaction – Sprint usually requires you to speak to two-three levels of highly confused tech support before actually sending out a new SIM.

Not affiliated with nor get commission from these people, just what I ended up with this round.