Today we’re excited to announce that over 3 million people have tried GlassWire! We’d like to thank all the GlassWire users who told their friends and shared GlassWire online so other people could learn about us. Without your sharing, help, support, feedback, and bug reports we wouldn’t be here. We hope you’ll continue using GlassWire, sharing it with others, and sending in reports so we can continue to improve and grow.
We’re also happy to announce our GlassWire 1.2.64b update that was released this morning. This software update has a lot of improvements and fixes due to feedback from GlassWire users in the forum, and some reports made on HackerOne.
As usual please report feedback along with any problems to our helpdesk, or in the forum. Thanks again for all your help and support!
Some of our users have been confused about how GlassWire’s graph scaling works so we wanted to post an explanation to help avoid confusion.
Please see the GlassWire graph example above. This example shows that over the past 5 minutes you have downloaded 20 KB worth of data. When you downloaded the most data you’ll see there is a spike on the graph. Now I’d like to explain what the graph spike shown above means, and how much data was actually downloaded at that point.
Please check the upper left of the graph where it shows that the upper limit of the graph is 20 KB. This means that this spike is less than 20 KB. So you can estimate that this spike is about 15 KB of data.
So now you’ve estimated that this spike is about 15 KB. Now you can confirm your suspicions by setting the vertical line on this spike, then clicking the graph to see that your estimation is correct.
Please also note that when you click the graph you can see below what apps/hosts used the most data at that point in time on the graph. For example in the image below you could click the “Dropbox” icon or the “client-cf” American Flag icon to see what hosts/apps caused this spike and what hosts they were communicating with.
Now you are able to associate the scale of the spike with the top left label.
There is also a bandwidth label at the bottom left of the window. Bandwidth means the number of bytes divided to the time of transfer. So if the 15 KB file was downloaded during 10 seconds, the bandwidth will be 15 KB per second.
With regards to our graph this will mean that we have to summarize all the transferred bytes during 3 hours and divide it into 3 hours. We can implement it easily, but the problem is that the user is unable to see the sum of all the transferred data on the graph tab. So he will have to go to the Graph\Apps, see the “All apps” value and divide it into 3 hours and he will get the bandwidth, than go back to graph and continue working.
You can see that the total amount of data during 3 hours is 154.8MB, this means that the average bandwidth will be 154.8MB/3hours = 51.6 MB per hour = 14,6 KB/s.
Some users have also asked how our scaling works when you drag the GlassWire graph larger/smaller.
When a GlassWire user changes the window size, the graph scale also changes. We can see some spikes if the window is small, but if the size is increased those spikes may be divided into several lower spikes. And vice-versa, for example, GlassWire is running in full screen mode and we can see several spikes and then when we decrease the size of the window, those spikes will be combined into one big spike.
The amount of traffic will be also recalculated so the top left value will change.
For example, we have two spikes in 10MB and 20MB and the top right value is 30MB. Then we’ve decreased the window size so those two spikes are combined into a single spike.
Since two spikes were 10 and 20 MB, that single spike will be about 30MB. So the top right value will be recalculated too, and this is required to fit the graph in the graph area and the new top right value may be 50-60MB.
Now the window size decreased and spikes are combined.
We hope this Blog post helps explain how our graph works, and makes it easier to estimate data usage on the fly. If you have any further questions feel free to comment, or make a post in our forum.
Your PC may be safe from tracking, but is your face?
Up until recently you could go out in public in a city you’ve never visited before with the expectation that nobody would know who you are. Unfortunately, due to facial recognition technology, your ability to be anonymous in crowds may soon be a thing of the past.
Russian photographer Yegor Tsvetkov recently presented a project online he calls “YOUR FACE IS BIG DATA” that showed how he was able to easily find out the name and details of random people sitting across from him on the subway. Below is one example photo from his project.
On the left is a random person Yegor photographed on the subway and on the right was the social media account photo Yegor found from a facial recognition database.
Yegor used facial recognition technology from a Russian search company called N-Tech.Lab to find intimate details about people sitting near him on the subway just by taking a photo of their face with his mobile phone. The N-Tech.Lab search could match the faces of most people Yegor photographed by using their public social media account details.
Unfortunately GlassWire can’t do much to protect your face from being put in a massive facial recognition database, but there are some things you can do on your own to help protect your privacy.
Also, always think twice before posting photos/names of friends, family, and children online. They may not want their photo associated with their name so it’s permanently part of a future massive facial recognition database.
Download GlassWire
Instantly see your current & past network activity. Detect malware, & block badly behaving apps.
