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When you browse Instagram and find Tony Abbott's passport number

mango.pdf.zone

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Re: When you browse Instagram and find Tony Abbott's passport number

#221

I still find it strange you can manage a booking with just a reference and name. About ~5 years ago someone I follow on twitter posted their boarding pass and I replied to them with a screen shot asking if I should cancel the booking. They removed their post and I removed mine. But all it took was the reference on the boarding pass and their last name...

What I've gathered left and right wrt the airline industry is that it was one of the earliest industries that went digital, and / but they have a lot of legacy going on. I mean in this particular case, they could have Abbott create an account on their website first, but then, someone else booked the ticket for him so that makes things more complicated (because they don't have an e-mail address), and then there's tick…

The amount of pain still caused by things like somebody back in the sixties deciding that two characters is plenty to encode every single airline ever is still felt to this day. Witness the majesty of the "controlled duplicate": https://en.wikipedia.org/wiki/Airline_codes

Re: When you browse Instagram and find Tony Abbott's passport number

#225
post #204

Great post, thoroughly enjoyed reading it. BTW, on a side note, when you try and visit the blog's homepage[0] and scroll down to the bottom, you find a link to an actual (password protected) PDF file called Mango.pdf[1]. The author 'Alex' says the password for the PDF has been embedded in the page and it didn't take me a lot of time to figure the password out from the HTML source[2]. But when I opened the PDF, I was…

CyberChef[0] has a 'magic' decoder that tries out different encodings for you.

[0] https://gchq.github.io/CyberChef/#recipe=Magic(3,false,false...

Re: When you browse Instagram and find Tony Abbott's passport number

#227
post #26

Nice. Here's a similar personal story with a PSA that sometimes blurring is NOT sufficient. A friend of mine posted on Instagram a picture of a U.S. visa (or something similar; it was probably five years ago) to announce her trip to the U.S., and she took care to blur out sensitive information such as her passport number. But a Gaussian blur is easy to reverse and I successfully unblurred it and told her my discovery…

>a Gaussian blur is easy to reverse That's the most surprising thing I've read today. I assumed it was destructive.

It's lossy, but not destructive, and a 'sharpen' operation is technically the same as blur but in reverse. So you won't end up pixel-perfect after doing an 'unblur' but you will be able to make out more than you could before.

Re: When you browse Instagram and find Tony Abbott's passport number

#228
post #216

I would encourage anyone interested in this article to read it thoroughly to the end. This is one of the most satisfying articles I’ve read recently and I really enjoy the author’s unique sense of humor.

Try some of james mickens articles: https://mickens.seas.harvard.edu/wisdom-james-mickens

They are written in a similar style, I really love them.

Re: When you browse Instagram and find Tony Abbott's passport number

#230
post #79
post #26

Nice. Here's a similar personal story with a PSA that sometimes blurring is NOT sufficient. A friend of mine posted on Instagram a picture of a U.S. visa (or something similar; it was probably five years ago) to announce her trip to the U.S., and she took care to blur out sensitive information such as her passport number. But a Gaussian blur is easy to reverse and I successfully unblurred it and told her my discovery…

Yup. I wrote a blog post about this a long time ago in 2007, and it was republished in Gizmodo in 2014: https://gizmodo.com/why-you-should-never-use-pixelation-to-h... You can dictionary attack pixelated photos. With Gaussian kernels, besides deconvolution you can sometimes also dictionary attack them if you have the original font and if the kernel is properly normalized kernel (i.e. most gaussian blurs). Although I…

Interesting, thank you for the link. I had a hunch this should be possible but I wasn't aware that it was already proven. I used a similar trick on image recognition: turn images into a single 32 bit word by heavy pixelation and then look up a matching description. It's interesting how often that will work once you feed it with enough data. After all, that gives you 4 billion inputs mapped onto 4 billion descriptions, and plenty of those will contain the Eiffel tower with various cloudy backgrounds apparently recognized perfectly.

It's a total cheat but it is funny how close that can get you to something that might be actually useful.

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