We were actually considering doing some object detection in a next run.

It feels like there could potentially be some town planning applications like finding the distribution of rubbish bins vs litter on the floor

There are around 50 results for Crystal Palace, Ill have a look through the logs to see what might have gone wrong

Sadly no R Soles though (A shoe shop formerly in Chelsea but now online) - however, just searching for profanities does bring back some graffiti

Only 2 examples for "gay", no "ferodo", suspiciously few for "jaguar".

Hi Author here,

This doesnt really answer your question but hopefully gives some insight into our process.

The main bottlenecks were breaking the fisheye-style panoramas into different perspectives (so text was more readable), passing it to OCR and acquiring the panoramas as there isn't an official API.

Because of the above, we constrained ourselves from the outset. For example, the spacings between panoramas was 50m, we didnt traverse residential roads that were less likely to have signage, we only used the most recent panorama for a location etc

If I interpret global as without those constraints (5m spacings, every road, all historic panoramas) then I think the first problem you'll run into is being rate limited by Google. Compute may be able to solve the other problems but it would be very expensive.

It’s perhaps a bit better now, but back when trip-sharing features were first added to third-party mapping and delivery platforms, there was a real tendency to overshare. Many early implementations generated public URLs with sequential or low-entropy IDs that could be guessed or brute-forced. Anyone who knew the pattern could enumerate live or historical “shared trips,” exposing routes, addresses, and other metadata that were never meant to be public.

I documented a few examples of this a while ago, which demonstrate how easily these systems could leak journey data.

https://dfworks.xyz/blog/online_stalking_citymapper/ https://dfworks.xyz/blog/pizza_order/

I made this - https://london publicinsights.uk as well as operate a public records aggregator that has indexed, amongst other things, planning applications. I wonder if it could be of use?

I have a London one also if anyone is interested!

https://london.publicinsights.uk

Nice! If you want to email [email protected] we could send you a repost invite for https://news.ycombinator.com/item?id=44664046 - but please wait a while first. The trick is to let enough time go by for the hivemind caches to clear. Then everything old becomes new again :) - usually 2-3 months is a good interval...

After recently reading several concerning articles about MAID data, I decided to simulate some device activity (because buying it is too expensive!).

I then modelled how these fictional devices might vote to demonstrate how harmful/useful aggregated and analysed MAID data can be.

If anybody found this interesting and would like some further reading, the paper below employed a similar strategy to analyse inauthentic content/disinformation on Twitter.

https://files.casmconsulting.co.uk/message-based-community-d...

If you would like to read about my largely unsuccessful recreation of the paper, you can do so here - https://dfworks.xyz/blog/partygate/

If anyone found the above interesting, I wrote a short article mapping plane activity on FlightRadar's 'blocked' list (i.e FlightRadar had agreed to remove the ADBS data from their dataset following probable legal pressure).

https://dfworks.xyz/blog/hnwi-osint-private-jet/

Slightly tangential so feel free to remove if irrelevant

The article was interesting alone, simply for the Google Dork technique explanation. Have not heard the "unusual, yet specifically frequent" search technique described that way previously. Very similar to what's necessary for searching StackExchange and similar, such as "site:https://aviation.stackexchange.com/ tracking private planes"

The Bombardier Global Express 6000 GLT6 result is interesting, as it's a plane with a known large number of military conversions. https://en.wikipedia.org/wiki/Bombardier_Global_Express#Mili...

Known Conversions: GlobalEye, Project Dolphin, Raytheon Sentinel, Saab Swordfish, PAL Aerospace P-6, E-11A, HALOE, PEGASUS, Hava SOJ, CAEW, HADES.

Actually has a tie-in with the article, since the Hava SOJ is an air stand-off jammer configuration for the Turkish region.

Otherwise, if I still worked for the government contracting, I'd probably offer you a job, although you're apparently British, so there might have been citizenship issues.

Apparently people now call using Google's advanced search operators Dorking, neat! I guess I've been dorking for a while.

Most of us know about "site:" since it's extremely handy, but there are a lot more. For some reason I had it in my head that many of the documented operators didn't work properly -- or at least I couldn't get them to work properly the last time I tried to experiment. I'll have to try again.

There was a very recent "bug" in Search where the site: operator stopped working for a little bit and everybody in the OSINT community had a bit of a meltdown - https://www.digitaldigging.org/p/search-alert-google-filetyp...

The date operators from: to: I think have been unsupported for a while and replaced with a dropdown in the UI

filetype: is a fave and has been working for as long as I can remember

AROUND(number) is pretty useful too although I find that might be a bit buggy sometimes

There is a good list here https://www.exploit-db.com/google-hacking-database showing how dorks can be used for pentesting and/or generally finding insecure stuff

Thanks, had no idea there were that many specific operators and combinations of operators.

At least in the last year, looks like "inurl", "intitle", and "intext" have all been getting a lot of use.

Also, a lot of "index of". "db.py", "store", "secret", "ec2 -aws", "mysql inurl:./db/", ect... in combination. Must be a lot of low hanging fruit in the orchard.

Google dorking has been a thing for more than 20 years: https://kit.exposingtheinvisible.org/en/google-dorking.html

(Your comment downplaying someone else's work, while simultaneously showing your lack of historical knowledge on the topic about which you're commenting, based on my specific googling to find the date of coinage, might make you eligible to be "a foolish or inept person as revealed by Google".)

Yep, British for my sins, as a US soldier once described to me, we are your least worst enemy

That's LADD (Limited Aircraft Data Displayed), which requires that aircraft marked as such in the FAA's database to be removed from the official data feeds used by the commercial flight radar sites.

Crowdsourced data isn't subject to LADD, so adsbexchange and other such sites can and do display such aircraft.

For flights within the US, there's also a private address program that allows an ADS-B equipped plane to broadcast an alternate address.

https://www.faa.gov/air_traffic/technology/equipadsb/privacy

Every day is a learning day!

That was interesting, thanks. I liked the co-location analysis idea.

Planning applications in the UK are publicly available and many have architectural drawings/site plans attached with varying degrees of detail.

There are millions of applications and each local authority has a different database so it may take a bit of digging to find what you are searching for.

Application example - https://publicaccess.tewkesbury.gov.uk/online-applications/a...

Drawings example - https://publicaccess.tewkesbury.gov.uk/online-applications/f...

Same in Denmark, you can either look them up on https://weblager.dk or if a house you interested in isn't available there you can normally request the drawing from the city, for a small fee.