Birth of a conspiracy!

[thewop]

Prediction: when Trump loses this will be part of the next "Q" movement...

No idea how true/not true it is or what the reasonable explanation is (I'm sure there is one), but I scrolled past this one and thought HBOT would enjoy it:

 

[thewop]

Oh crap I'm going to have to erase my history because then I saw this... Both Trump would-be assassins were featured in Black Rock commercials?!?

 

[noStemsnoSTICKS]

When it comes to conspiracy theories, this brand of maga republicans are champs.

 

[hawkeyetraveler]

People will fall for anything. GPS and cellphone data are not available to the public. There is no way anyone could gather that data and aggregate it. It would mean every cellphone provider violated their privacy terms then sent it off to some dude on Twitter who in a matter of a couple days created these summary statistics. That just doesn’t happen.

Be better OP. You usually aren’t as dumb as this.

 

[noStemsnoSTICKS]

People will fall for anything. GPS and cellphone data are not available to the public. There is no way anyone could gather that data and aggregate it. It would mean every cellphone provider violated their privacy terms then sent it off to some dude on Twitter who in a matter of a couple days created these summary statistics. That just doesn’t happen.

Be better OP. You usually aren’t as dumb as this.

Sure, facts, logic and rational thought can explain why its wrong. But try using facts, logic and rational thought on 71 million trumpers.

 

[Obviously Oblivious]

People will fall for anything. GPS and cellphone data are not available to the public. There is no way anyone could gather that data and aggregate it. It would mean every cellphone provider violated their privacy terms then sent it off to some dude on Twitter who in a matter of a couple days created these summary statistics. That just doesn’t happen.

Be better OP. You usually aren’t as dumb as this.

I thought the same thing because I enjoy a functioning brain. How do people fall for this endless river of bullshit? It’s embarrassing.

 

[ItsinourDNA]

I thought the same thing because I enjoy a functioning brain. How do people fall for this endless river of bullshit? It’s embarrassing.

Good ol confirmation bias methinks

but yes people are dumb.

 

[seminole97]

People will fall for anything. GPS and cellphone data are not available to the public. There is no way anyone could gather that data and aggregate it. It would mean every cellphone provider violated their privacy terms then sent it off to some dude on Twitter who in a matter of a couple days created these summary statistics. That just doesn’t happen.

Be better OP. You usually aren’t as dumb as this.

You don’t understand how this works.

That doesn’t mean you’re dumb, just ignorant.

The cure for ignorance is knowledge:

https://www.eff.org/deeplinks/2022/06/how-federal-government-buys-our-cell-phone-location-data

Where does the data come from?​

Weather apps, navigation apps, coupon apps, and “family safety” apps often request location access in order to enable key features. But once an app has location access, it typically has free rein to share that access with just about anyone.

That’s where the location data broker industry comes in. Data brokers entice app developers with cash-for-data deals, often paying per user for direct access to their device. Developers can add bits of code called “software development kits,” or SDKs, from location brokers into their apps. Once installed, a broker’s SDK is able to gather data whenever the app itself has access to it: sometimes, that means access to location data whenever the app is open. In other cases, it means “background” access to data whenever the phone is on, even if the app is closed.

One app developer received the following marketing email from data broker Safegraph:

SafeGraph can monetize between $1-$4 per user per year on exhaust data (across location, matches, segments, and other strategies) for US mobile users who have strong data records. We already partner with several GPS apps with great success, so I would definitely like to explore if a data partnership indeed makes sense.

But brokers are not limited to data from apps they partner with directly. The ad tech ecosystem provides ample opportunities for interested parties to skim from the torrents of personal information that are broadcast during advertising auctions. In a nutshell, advertising monetization companies (like Google) partner with apps to serve ads. As part of the process, they collect data about users—including location, if available—and share that data with hundreds of different companies representing digital advertisers. Each of these companies uses that data to decide what ad space to bid on, which is a nasty enough practice on its own. But since these “bidstream” data flows are largely unregulated, the companies are also free to collect the data as it rushes past and store it for later use.

The data brokers covered in this post add another layer of misdirection to the mix. Some of them may gather data from apps or advertising exchanges directly, but others acquire data exclusively from other data brokers. For example, Babel Street reportedly purchases all of its data from Venntel. Venntel, in turn, acquires much of its data from its parent company, the marketing-oriented data broker Gravy Analytics. And Gravy Analytics has purchased access to data from the brokers Complementics, Predicio, and Mobilewalla. We have little information about where those companies get their data—but some of it may be coming from any of the dozens of other companies in the business of buying and selling location data.

If your next question is “which apps are sharing data?”, the answer is: “It’s almost impossible to know.” Reporting, technical analysis, and right-to-know requests through laws like GDPR have revealed relationships between a handful of apps and location data brokers. For example, we know that the apps Muslim Pro and Muslim Mingle sold data to X-Mode, and that navigation app developer Sygic sent data to Predicio (which sold it to Gravy Analytics and Venntel). But that is just the tip of the iceberg. Each of the location brokers discussed in this post obtains data from hundreds or thousands of different sources. Venntel alone has claimed to gather data from “over 80,000” different apps…

 

[hawkeyetraveler]

You don’t understand how this works.

That doesn’t mean you’re dumb, just ignorant.

The cure for ignorance is knowledge:

https://www.eff.org/deeplinks/2022/06/how-federal-government-buys-our-cell-phone-location-data

Where does the data come from?​

Weather apps, navigation apps, coupon apps, and “family safety” apps often request location access in order to enable key features. But once an app has location access, it typically has free rein to share that access with just about anyone.

That’s where the location data broker industry comes in. Data brokers entice app developers with cash-for-data deals, often paying per user for direct access to their device. Developers can add bits of code called “software development kits,” or SDKs, from location brokers into their apps. Once installed, a broker’s SDK is able to gather data whenever the app itself has access to it: sometimes, that means access to location data whenever the app is open. In other cases, it means “background” access to data whenever the phone is on, even if the app is closed.

One app developer received the following marketing email from data broker Safegraph:

SafeGraph can monetize between $1-$4 per user per year on exhaust data (across location, matches, segments, and other strategies) for US mobile users who have strong data records. We already partner with several GPS apps with great success, so I would definitely like to explore if a data partnership indeed makes sense.

But brokers are not limited to data from apps they partner with directly. The ad tech ecosystem provides ample opportunities for interested parties to skim from the torrents of personal information that are broadcast during advertising auctions. In a nutshell, advertising monetization companies (like Google) partner with apps to serve ads. As part of the process, they collect data about users—including location, if available—and share that data with hundreds of different companies representing digital advertisers. Each of these companies uses that data to decide what ad space to bid on, which is a nasty enough practice on its own. But since these “bidstream” data flows are largely unregulated, the companies are also free to collect the data as it rushes past and store it for later use.

The data brokers covered in this post add another layer of misdirection to the mix. Some of them may gather data from apps or advertising exchanges directly, but others acquire data exclusively from other data brokers. For example, Babel Street reportedly purchases all of its data from Venntel. Venntel, in turn, acquires much of its data from its parent company, the marketing-oriented data broker Gravy Analytics. And Gravy Analytics has purchased access to data from the brokers Complementics, Predicio, and Mobilewalla. We have little information about where those companies get their data—but some of it may be coming from any of the dozens of other companies in the business of buying and selling location data.

If your next question is “which apps are sharing data?”, the answer is: “It’s almost impossible to know.” Reporting, technical analysis, and right-to-know requests through laws like GDPR have revealed relationships between a handful of apps and location data brokers. For example, we know that the apps Muslim Pro and Muslim Mingle sold data to X-Mode, and that navigation app developer Sygic sent data to Predicio (which sold it to Gravy Analytics and Venntel). But that is just the tip of the iceberg. Each of the location brokers discussed in this post obtains data from hundreds or thousands of different sources. Venntel alone has claimed to gather data from “over 80,000” different apps…

Actually I do know how this works having worked directly in this field. What you think is possible here is not possible. The data available wouldn’t support being able to triangulate thousands of users, you would be lacking key data you would need (as I said before) and the processing time would be such that you could not get this analysis done so quickly. And even if you had access to the right data it is not pre-structured in the appropriate geofences, nor would it be filtered to specific users who entered those geofences. You would need to do a shit ton of post processing, you would need to correct for triangulation errors inside a venue, and more. It just doesn’t work that way and it sure as hell doesn’t work that fast.

And even if it did, it would not be some random dude on Twitter and Tik Tok that figured it all out.

 

[seminole97]

Actually I do know how this works having worked directly in this field. What you think is possible here is not possible. The data available wouldn’t support being able to triangulate thousands of users, you would be lacking key data you would need (as I said before) and the processing time would be such that you could not get this analysis done so quickly. And even if you had access to the right data it is not pre-structured in the appropriate geofences, nor would it be filtered to specific users who entered those geofences. You would need to do a shit ton of post processing, you would need to correct for triangulation errors inside a venue, and more. It just doesn’t work that way and it sure as hell doesn’t work that fast.

And even if it did, it would not be some random dude on Twitter and Tik Tok that figured it all out.

Genuinely asking, what has changed since this was written?

I Gave a Bounty Hunter $300. Then He Located Our Phone​

Nervously, I gave a bounty hunter a phone number. He had offered to geolocate a phone for me, using a shady, overlooked service intended not for the cops, but for private individuals and businesses. Armed with just the number and a few hundred dollars, he said he could find the current location of most phones in the United States.

The bounty hunter sent the number to his own contact, who would track the phone. The contact responded with a screenshot of Google Maps, containing a blue circle indicating the phone’s current location, approximate to a few hundred metres.

Queens, New York. More specifically, the screenshot showed a location in a particular neighborhood—just a couple of blocks from where the target was. The hunter had found the phone (the target gave their consent to Motherboard to be tracked via their T-Mobile phone.)

The bounty hunter did this all without deploying a hacking tool or having any previous knowledge of the phone’s whereabouts. Instead, the tracking tool relies on real-time location data sold to bounty hunters that ultimately originated from the telcos themselves, including T-Mobile, AT&T, and Sprint, a Motherboard investigation has found. These surveillance capabilities are sometimes sold through word-of-mouth networks.

Whereas it’s common knowledge that law enforcement agencies can track phones with a warrant to service providers, IMSI catchers, or until recently via other companies that sell location data such as one called Securus, at least one company, called Microbilt, is selling phone geolocation services with little oversight to a spread of different private industries, ranging from car salesmen and property managers to bail bondsmen and bounty hunters, according to sources familiar with the company’s products and company documents obtained by Motherboard. Compounding that already highly questionable business practice, this spying capability is also being resold to others on the black market who are not licensed by the company to use it, including me, seemingly without Microbilt’s knowledge.

Motherboard’s investigation shows just how exposed mobile networks and the data they generate are, leaving them open to surveillance by ordinary citizens, stalkers, and criminals, and comes as media and policy makers are paying more attention than ever to how location and other sensitive data is collected and sold. The investigation also shows that a wide variety of companies can access cell phone location data, and that the information trickles down from cell phone providers to a wide array of smaller players, who don’t necessarily have the correct safeguards in place to protect that data.