https://en.wikipedia.org/wiki/Berners_Street_hoax

As a taxi service, I believe I would want to know if I'm about to have a shortage of taxis in any one area of town, and I'd better only have a concentration in one area of town for an event the entire world is talking about, like a reunion tour or a championship game.

Even with the hack, the moment all of the taxis started converging on one area of town, alarms should have been going off and managers should have been asking questions. But that's not what happened, because we say yes the moment money enters the conversation, without bothering to ask what it says about you as a person if you'll do anything for money, or for that matter if the money is even real or just a trick to get our attention.

Yandex has thousands of cars here in Moscow. There were around 60 in this jam on the prospect.

So most likely not "ordered all avaiable", but "the order was forwareded for all available in the radius" or something like that.

Surely you can't order a car in Yadex Taxi much less order all of them or even a car from another part of the city.

Without knowledge of Russian or context this could just be taxis on some sort of protest rally.

individual drivers or individual taxi firms in a market due to their decentralization are much more robust to any kind of individual failure.

People often ask "is the car smarter than the driver?" but the correct question would be if the car, or system is more diverse than the aggregate knowledge of all the participants.

jammr.com: It's like Uber for Traffic Jams!

This is the first time this has happened and the total cost of it is at most a few hours revenue. They’ll likely add safeguards to prevent such a thing now, but if they ran the company preparing for every possible way things could go wrong, they’d get absolutely nothing done.

It also happens to have the side benefit that an operator watching the flagged zones would be able to see this kind of an issue happening in advance and maybe check into why every cab is suddenly bee-lining it to zone 3.

A real taxi firm would notice and stop taking new calls to the address, but Yandex.Taxi aren't really 'dispatching' taxis, they're just advertising jobs, and letting drivers respond in real time.

In fact, I'd imagine that almost none of the orders placed are reviewed in realtime, and the only indicator that anyone would have had for this to begin with would have been a higher than average number on the dashboard for 'trips requested today' - an interesting metric, but not something that I would expect to be monitored closely in real time.

I'd imagine there's a 'no show' procedure that doesn't involve human oversight, so the first couple of drivers likely arrived at the address, waited a few minutes, then coded in the no show and moved on to different jobs.

This is also likely a metric on a dashboard which would have been the second indicator - booking cancellations/no-shows/driver rejections. But again, it's an analytics metric, rather than realtime actionable business intelligence, so it's the sort of thing that gets put into weekly reports. Maybe someone would have seen it and thought 'huh, that's a bit high', but probably didn't trigger any alarms.

Eventually a curious taxi driver would start to question why there are so many taxis outside this address, and would get out of his car and chat to his colleagues. They'd identify that they'd all been asked to the same address, and probably all cancel together and drive off.

MAYBE the third indicator here would be a call from one of the drivers to customer support, letting them know about the 'system glitch' that meant multiple taxis were waiting at the same address, but it's equally possible that the drivers just moved onto their next fare without reporting any issue.

So potentially, the first time that anyone at YT realised there was a serious issue was already 10-15 minutes after the incident occurred, by which time, it's already late. On top of that, it's unlikely that they have a way to easily and effectively cancel all bookings to a particular address.

I don't have any details on the hack itself or YT's infrastructure, so it may have been very difficult to identify and cancel the fraudulent bookings en masse (e.g.: fuzzed addresses, booking times, different users, card details not stored or different card numbers used, etc.).

By the time it got escalated to any technical teams, we're already likely 30-40 minutes into the incident itself, at which point they have to analyse what is happening, trace how it happened, and identify a fix.

With the immediate nature of taxi booking (I want a taxi NOW, not in 45 minutes), it doesn't surprise me that an incident like this can occur before any technical measures can be put in place to stop or mitigate it.

No one wants this single pair of instances in a Tier 4 datacenter that host a single key-pair authenticated process with dual manual approval and an air-gap that dispatches one taxi (and precisely one taxi) every 30 days on a route where it can be guaranteed to hit its time prediction.

Any fool can build a bridge that stands. It takes an engineer to build a bridge that barely stands.

My prediction: Ransomware hits self-driving cars.

You're locked in the car until you Venmo the bad guys some credits.

To encourage compliance, the stereo starts playing the sound of running water.

> In July 2015, IT security researchers announced a severe security flaw assumed to affect every Chrysler vehicle with Uconnect produced from late 2013 to early 2015.[120] It allows hackers to gain access to the car over the Internet, and in the case of a Jeep Cherokee was demonstrated to enable an attacker to take control not just of the radio, A/C, and windshield wipers, but also of the car's steering, brakes and transmission.[120] Chrysler published a patch that car owners can download and install via a USB stick, or have a car dealer install for them.[120]

> https://en.wikipedia.org/wiki/Chrysler#Chrysler_Uconnect

The worst part is they were never really transparent about what the issue was.