In China, they have a surveillance program on social networks which looks like a jerry-rigged PRISM clone of the NSA.imqq.com
So this social media surveillance program is retrieving (private) messages per province from 6 social platforms and extracts named, ID numbers, ID photos, GPS locations, network information, and all the conversations and file transfers get imported into a large online database.
Around 364 million online profiles and their chats & file transfers get processed daily. Then these accounts get linked to a real ID/person. The data is then distributed over police stations per city/province to separate operators databases with the same surveillance network name
With these "operator databases" the local law enforcement investigate 2600 to 2900 messages and profiles. The name new table per day to keep track of the progress. So they manually review the social media communication (public/private messages).
And the most remarkable part is that this network syncs all this data to open MongoDBs in 18 locations.
The most dialogs which are being monitored are typical teenager conversations. Which conversations need to be reviewed by a human based on "trigger words" is at this moment still not entirely clear.
One of the multiple intelligence feeds showing the distribution of triggered events routed to the police stations identified by numbers. It's a very effective way of spreading the workload from a single source to multiple operators. It will require tremendous work ethics as well
How many gamers live in China and who many of them are using an internet cafe (or internet bars / netbars) as they are being called there?
It is most likely that this system is only for tracking gamers as most of the sample dialogs appears to be about this subject.
”Most of the internet cafes use management softwares called "网吧管理软件", there are only a few companies develop such software, this is a gray area, the management softwares contains advertising, push notifications, even with ability to push executables to a client.”
The internet cafe management software named "网吧管理软件"
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"
From 240 million messages to over 1 billion private messages per day.
The biggest issue is that this not only for ordering pizza. It is completely hardwired into our lives. Doing "monitoring in a safe way" still appears to be a challenge.
What we have learned from 1.081.231.257 "captured" WeChat dialogues ( 3,784,309,399 messages) made on the 18 March 2019 is that were automatically selected for "reviewing" based on a "keyword" trigger.
Not all the dialogues were in Chinese or only had GPS coordinates in China.
From 3.784.309.399 messages, 3.698.798.784 were written in Chinese.
59.378.236 in English and 26.132.379 in another language. 98% of the Chinese messages had a GPS location in China. 68% of the English messages were sent in China. More than 19 million were sent from outside 🇨🇳
We were able to detect a patron of a little bit more than 800 Chinese keywords (combinations) which would be the selection criteria for having the entire WeChat dialogue being stored in this database for further "analysis" by most likely a law enforcement.
We could build a "dictionary" of 829 keywords (combinations) based on the intercepted WeChat messages which were written in English. I was a bit surprised to see my full name "Victor Gevers" in this generated English list. 维克多 葛弗斯 was not in the Chinese keyword list.
Using these keywords will not get your account locked. But I you try to send your contact a few messages contains a few hundred of these words then you need to “unblock” your account after a few minutes.
Based on the 3,784,309,399 WeChat messages we tried to build a "keyword trigger list" with NLP tools which possibly triggered the automatic selection criteria for having the entire conversation being stored for review.
From 3.784.309.399 intercepted messages. 59.378.236 were in English.
19 million were sent from outside Mainland China: South Korea, Taiwan, US, Australia, Canada, Colombia, Venezuela, Belgium, France, UK, Germany, Netherlands, Turkey, Italy, Switzerland, New Zealand & Ireland.
I am listening to the @riskybusiness show [], and I hear this at 21:50:
"We've got politicians in Australia who are using WeChat."
Wait!? What? So they can have been one of the 937202 "flagged" conversations recorded in Australia? 🤷♂️
512.2 million WeChat accounts (unique wxids) sent 3,784,309,399 messages on 18-03-2019. 1 billion captured WeChat conversations contained keywords which marked for "review". 59.378.236 were written in English.
19 million were sent from 🇰🇷🇹🇼🇺🇸🇦🇺🇨🇦🇨🇴🇻🇪🇧🇪🇫🇷🇬🇧🇩🇪🇳🇱🇹🇷🇮🇹🇨🇭🇳🇿🇮🇪
I wonder why the Australia politicians are willing to take a "calculated" risk when they expose the participants (the Mandarin-speaking community and themselves) to Chinese surveillance by using WeChat for "a novel political experiment."
In the "phrase matching" process the Chinese data scientist student used these Chinese keywords from this wordlist
So we can safely assume that the keyword trigger list is far from complete. So we decided to do this research all over again from scratch... github.com/citizenlab/cha…
A quick status update. The data scientist who created the current keyword list is still MIA. []. We did not make so much progress. Yet new breadcrumbs are slowing surfacing thanks to termination of third party translation services.
New sources keep contributing to the research into WeChat and other multi-purpose messaging, social media and mobile payment monitoring. Every day new development systems are randomly popping up in China and are sharing data that is all publicly available (in open databases).
Globally, hundreds of millions are consuming information directly produced by Chinese state media—sometimes without knowing it, says @freedomhouse
’s @Sarah_G_Cook.
Social media and multi-purpose messaging apps are being monitored, and controlled.
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.
So Parler advertises to be an unbiased social media focused on real user experiences and engagement
I appreciate projects which enable free speech. On Parler, it seems that many celebrities are not 'human'. Most accounts are not verified. But even the verified ones are not human?
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. 🤦♂️
The issue with these experimental R&D AI/FRT projects is that they use real production systems and data. Realtime security footage from governmental buildings and actual police data sets used in open systems grating access to active third party mass surveillance systems in China.
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
The database is now "protected" with a firewall rule. Although the suspicion is that all traffic from outside China is blocked for this service. At least the data is not to access the data anymore for outlanders.
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]
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
One of these open databases w these Kremlin credentials was a MongoDB server holding ERDR information by @MVS_UA (RD#5019) which shows that changing a password in a system (where they had remote access) in a country with who how they are in a war with was too much effort for 🇷🇺
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.
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:-D
"optional, backdoor for tweaking UART config" and "Dup Tag Debug Backdoor Ram Access for CP0/CA0". At least Apple named it what it is in the #iBoot source code :-)