tl;dr Planes that fly overhead are audible in any audio you post online. If the time of the recording is known, then by cross-referencing with public flight data, it is possible to find the location of the video within 100 meters.
Let this be a reminder to be very careful about posting videos and images that you personally recorded. Nothing is private on the internet
All the videos recorded during the FAA’s ground stop yesterday are unlocatable now.
I know there was that technique for using a mic to track what keyboard keys were pressed but it didn’t work very well because you had to be very close nearby and if someone was playing say heavy metal music between the mic and the keyboard it was worthless. I wonder if there’s something that be done here either with a band-filter that removes say the lower bands or playing music or generating some other sound that makes it difficult to reliably key in on these plane flyovers and determine anything from them.
At any rate it’s important to remember it’s not just audio. Geoguessers from the chans back in the day were finding people’s home addresses with just a shot of the street outside their window using google streetview. The intelligence agencies have to have automated systems to match against google streetview, apple, etc using AI these days for the same paired with some humans skilled in that. Add in services like zillow that have interior house photos and if your house or apartment was ever listed on zillow without major renovations they may be able to use that to narrow down or find the exact location using specific features. This also applies to hotels and motels.
The likely CIA asset (or poor, fool of a sap) Ashton Kutcher was pushing a project purportedly aimed at stopping sex trafficking (yeah right, when the elites are pedophiles, sure buddy) that asked people to submit pictures of hotel rooms with names and addresses and room numbers so they could match that against pictures of supposed victims to “find them”. In reality that wouldn’t be that useful for that but is super useful for intelligence agencies to locate someone trying to be off grid. Many major hotel and motel chains later voluntarily joined that effort and submitted their own photos and videos of their rooms to allow the feds/intelligence to instantly zero where you are if you’re in a hotel/motel room.
So really the only safe place to take a video is in a nondescript, painted white walls, undecorated room in a basement far from an airport with nondescript curtains drawn and the audio levels low and even then who knows. The power hum as someone else mentioned could be a problem.
Not related per se but this, tempest attacks, the whole ability to use wifi to map locations of objects/people in homes meaning the feds can get an exact picture of the layout, furniture and all of your home from outside, plus AI to help with the grunt work and sift through and categorize people based off all the illegal surveillance it’s a pretty scary situation.
It makes you think about how relatively easy the Bolsheviks had it. How their enemies had to use human spies, very crude listening devices if any even existed at all. How with easy precautions they could be safe short of human infiltration and human infiltrators couldn’t be everywhere all the time. Now we all carry wiretaps, share our thoughts, plan our lives on surveillance equipment they control and can hack and take over at will with exploits and zero days and even if we avoid that there’s things like this. It’s overwhelming and depressing and makes one question what we can hope for other than collapse and rot of the system to such a point it no longer functions as well.
even if we avoid that there’s things like this.
You might practice perfect opsec, but your friends and family almost certainly won’t. This is what opsec guides never consider. You are at most two degrees of separation from someone with 30k+ photos on Facebook.
undecorated room in a basement far from an airport with nondescript curtains drawn and the audio levels low and even then who knows.
You actually want to be somewhat close to an airport, but not too close. Basically be in a normal place.
You could also just add random plane sounds to your audio, there’s a combo in there that could id you, but if most of them are fake it would be hard to check.
Also very small, random changes in playback speed throughout the video would be difficult but not impossible to work around
Huh that’s an interesting angle. Do you know if that’s done in practice, or are you spit-balling?
I remember fourier transforms well enough to guess about how moving the signals around a bit in time could destroy the resulting frequency data.
But I didn’t learn the discrete-time version of those (what’s actually used in practice) enough to intuit much here. I’d think it would require many offsets at very granular time values to “work”, but that’s a vague guess.
And I’d imagine it would be feasible to algorithmically re-align such distorted timing, as a preprocessing step prior to performing the frequency analysis, is that what you meant about it only making the task harder?
Speculating based on the methodology shown in the video. The Doppler curve pairs are matched according to a known time-separation, so if you mess with that time-separation, the filter is less effective. Likewise, directly matching the curve shapes assumes a constant time rate. Speedup/slowdown would change the curve shape and disrupt the shape matching. A third option I thought of now is messing with the curve shape along the frequency axis — by randomly adjusting pitch, the curve can be compressed/expanded vertically.
Both of these mitigation techniques could be probably be overcome with more processing that accounts for a range of values. The video shows some of the ways to overcome measurement error, but not intentional human intervention.
I was thinking that annoying, Philip DeFranco-style cuts and even swapping clips forward/backward in time would be an effective way to negate the plane exploit. Long, uninterrupted audio seems to be the thing to avoid for both the planes and the power lines.
Interesting write-up, thank you
What if you record ambient noise in the background and add it in later before posting?
If you suspect that there are fakes mixed in with the real ones, you can just check all the combinations. Like if there’s three airplanes (a b c) detectable in the recording, and you need at least two to find a time and place, you just check {a b}, {a c} and {b c} and see if that gets you somewhere.
so what about voice calls? can someone find your location just by recording your audio over enough time?
Yes. Voice calls with exact timestamps likely only need a single airplane (inaudibly) captured in the audio recording. If you have something like a minute or two of recording so as to capture two (inaudible) airplanes, this method could likely pinpoint the time and position across many months/years and multiple continents.
I live in a city with an airport, I heard multiple airplanes through my closed window just while watching this video. I can only imagine there’s 10x more that I can’t hear but that would be detectable in the audio recording. I.e. if this comment was an audio recording you would be able to figure out my position within a couple of blocks. Voice call or recording doesn’t matter, except voice call would be even easier because you already know the time down to the second or so.
thats really scary, hopefully ways to scrub that audio live are created.
You can watch the video they discuss this a bit, but I don’t think so.
Removing the airplane doppler curves from the recording seems very difficult, you cannot just easily filter them out. *
They discuss some mitigations, namely cutting the recording and adding fake airplane sounds. But cutting wouldn’t work for a live stream anyway, plus the whole point of cutting would be to desync two planes, but if you already know the exact time (since it’s live) one single plane might be good enough to get a fix.
Adding fake airplane sounds doesn’t remove the real airplane sounds, so one could still find the real position if one ignored the fake airplanes, which could be done by assuming any possible combination of airplanes to be either fake or real and then doing the method. If the fake airplanes were random, those wouldn’t correlate with anything, so if you were wise to the fact that fake random airplanes appear in the recording, you could just focus on the pairs of planes that correspond to real flight data and dismiss the rest, though that would add some computational complexity.
If you were to not just insert random flights, but rather specific flights to make it look like you were at a different location, that would still not remove the real airplane sounds from the recording, and someone who was wise to the fact you’re trying to fool them could pick up on that. Plus that seem complex and would require your recording software to have full live flight data to simulate your fake location.
* Thinking about it some more, though I’m not knowledgeable enough tbh: While you couldn’t easily filter this out I don’t think with like a filter bank, if you did like a sliding window (which would need to be many seconds since it would need to cover the whole time the airplane is recorded), and then ran a fancy doppler curve detector on the whole window, you could maybe fully delete the doppler curve (and harmonics) in frequency space and replace it with synthetic noise without fucking up the whole recording too much.
If you were to not just insert random flights, but rather specific flights to make it look like you were at a different location, that would still not remove the real airplane sounds from the recording, and someone who was wise to the fact you’re trying to fool them could pick up on that. Plus that seem complex and would require your recording software to have full live flight data to simulate your fake location.
Record the audio being played at a different location with another device (ie recording the original audio playing from the PC with your phone). I’m guessing it would be pretty easy to tell that it would be a recording of a recording, but I wonder how that would affect the Doppler curves. If the recording’s Doppler curves are indistinguishable from the rerecording’s Doppler curves, then it would take a lot more data crunching. Or how about record a video, record a second video a week later with the same exact script, and splice the two videos together. Maybe throw in a few fake Doppler curves to further confuse things.
If you are someone state actors want to liquidate asap, then it’s only a matter of patient number crunching. If you spliced together 3 different recordings with 7 Doppler curves and threw in 4 fake Doppler curves for a total of 11 curves, then they would number crunch by going:
Assuming 1 recording, 0 fakes.
Assuming 1 recording, 1 fake. Check all combinations.
…
Assuming 1 recording, 10 fakes. Check all combinations.
Assuming 2 recordings, 0 fakes. Check all combinations.
Assuming 2 recordings, 1 fake. Check all combinations.
…
Assuming 2 recordings, 9 fakes. Check all combinations.
Assuming 3 recordings, 0 fakes. Check all combinations.
…
Assuming 11 recordings, 0 fakes.could you remove the infrasound entirely?
They go over it in the video, you can’t just filter the frequencies without either affecting normal voice frequencies and/or leaving it in there but even more silent but still detectable. Though I did update my previous post and maybe something fancy could be done with Fourier transforms but I honestly don’t know enough about signal processing to be certain.
sanest solution is deepfake btw
I just do text, airplane vibrations aren’t going to click my keyboard switches.
There’s something kinda similar with powerlines. The hum from wires varies enough that you can pull the frequency that makes it into videos, and compare it against grid data. More for timestamping rather than geo-locating.
So what you’re saying is that if you combine these two you can get the timestamp needed for method used in the OP?
They can also use wifi signal analysis to track you throw walls, identify specific people based on their skeleton, and measure breathing and heart rate
it always pisses me off to see the empire being proudly strengthened by marginalized people like her
Technology was a mistake
That’s wild, ty for sharing
tl;dr Planes that fly overhead are audible in any audio you post online. If the time of the recording is known, then by cross-referencing with public flight data, it is possible to find the location of the video within 100 meters.
Oh that’s way less cool than what the title led me to believe tf
Did you watch it? I was way more impressed after watching it.
The time of the recording does not need to be known. If there are two planes captured in the recording (honestly sounds like any 1-minute recording from any place with regular air traffic would work, probably even indoor recordings because the planes need not be audible), this can correlate both planes and pinpoint an exact location even within a timeframe of a month. Honestly it would probably work even for timeframe of a year or multiple years across multiple continents. Even if you got more than one possible candidate time/date, some common sense can probably exclude the false ones.
These are good points. In the post I said the planes are audible, but that means present in the audio data. And knowing the time is only useful for reducing the volume of data to process; I’m sure 3 letter agencies could just chuck it in a 10-year search on a supercomputer. Plus they might deduce the recording device based on known characteristics; a recent iPhone likely has an obvious “fingerprint” in its recorded audio
Also this is something a person hacked on their own as a side project. We just have to assume what any org with real resources has will be way more powerful than anything civilians can do.
I do GIS stuff for a living and this is a fantastic example of a workflow that could be automated.
A few spatial queries, some SQL filtering, then keep filtering until the O(n^2) point matching function has an n that is reasonable.
Especially since basically all of that can be done in Python.
