I have been looking around in the @parler_app and within the Parler platform. The app lacks basic security like certificate pinning. This makes it easy to take a look under the hood. Most of the accounts are marked as: "human": false". To be able to become human in the Parler, you need to get verified. Users can do this by scanning their U.S. drivers license or Passport within the app. I tried a few times with my Dutch Passport but this failed. Even Parlersupport couldn’t help. So I searched for another way.

There is this Beijing-based Artificial Intelligence company known as Pensees Technology. They build passwordless, rinky-dink, AI-based security software systems using face recognition, and crowd analysis, which can detect a specific ethnic group from photos and video streams. 🤷🏻‍♂️ Peensees products are used for security applications and use existing face recognition technologies and CCTV cameras. This is a (mockup) dashboard of their open AI R&D environment. It looks like a "SenseNets disaster 2.0" in the making as they have no clue what they are doing. 🤦‍♂️

Can anyone (from China) identify these Messaging services?

imsg <--...
qg <--...
qqmesg. <-- imqq.com
wwmsg <--...
wxmsg <--...
yymsg <--...

In China, they have a surveillance program on social networks which looks like a jerry-rigged PRISM clone of the NSA. Daily roughly 1 billion private messages get selected & routed to the closest "operator" based on geolocation. It's fascinating how quickly new monitoring solutions are deployed in the same way as the old ones were discovered & taken down. Country-based filtering for "protection"

There is this company in China named SenseNets. They make artificial intelligence-based security software systems for face recognition, crowd analysis, and personal verification. And their business IP and millions of records of people tracking data is fully accessible to anyone. This database contains over 2.565.724 records of people with personal information like ID card number (issue & expire date, sex, nation, address, birthday, passphoto, employer and which locations with trackers they have passed in the last 24 hours which is about 6.680.348 records

Responsible disclosure #4155 took 3 years, 5 months and 15 days to fix the after effect of the leaked credentials. Some breaches don't have to be big in size (as in the number of records which are exposed) to have a significant impact which can take years to fix. [1/2]

https://twitter.com/0xDUDE/status/631520323574181889

Until recently many 🇷🇺 companies were using MongoDB not securely.
Most of them are reported to the owners. The biggest issue was that @KremlinRussia_E requires remote access to businesses and used the same credentials everywhere as we found them in the thousands of open databases

Looking for 0xDEADFEED to find 0x8BADF00D that went 0xBAAAAAAD.
Maybe it needs to 0xC00010FF to escape this 0xDEAD10CC situation?
Still hunting for unicorns but I only found a pony till now. Oh I see that @Zeecka_ already found the pony :

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:-D