Wednesday, September 27, 2017
Twitter fake page http ltwltter com timed out Beware it will steal your password phishing
Twitter fake page http ltwltter com timed out Beware it will steal your password phishing
If you get a Direct message that looks like this:
�
ROFLMAO i cant stop laughing at this pic of you ppfr.it/434
Direct message sent by YourFriend (@yourFriend) to you (@YourName)
�
The first reaction is to click on the short link ppfr.it/434 which will take you to http://t.co/tIdsrtv which will resolve to http://ltwltter.com/timed_out/ (notice the �l� before the �t� of twitter) which will present a FAKE Twitter login page that looks exactly like the Twitter web site with username and password screen:
Please beware � since this is a FAKE login screen � So do NOT enter your login details!
If you do enter your username and password � then the fake page will steal your username and password and then redirect you to another fake page:
http://ltwltter.com/status/error/ (notice the �l� before the �t� of twitter)
Once the phishers have harvested your login details then they will send DMs to all of your followers and send them the same �ROFLMAO� message and hope that they fall into the same trap and log in to the fake Twitter page.
Be careful out there and remember to ALWAYS check the URL of the page that you are logging in to.
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Sunday, September 17, 2017
TripAdvisor How fake reviews can ruin your travel diaries
TripAdvisor How fake reviews can ruin your travel diaries

The first 2 restaurants are in Belgium and as their name suggests, are owned by a same chain. The last 2 are in Portugal, and owned by an individual (see the attachment for proof, taken from TripAdvisor). There are many accounts that were created to review 2 or 3 among these or just 1 of these restaurants! Some of these reviewers have reviewed 1 or 2 of these restaurants more than once! (5-star each time).
I have attached two reviewers with this association for these 4 restaurants. There are many. Just go through each of these restaurants and click the 5-* ratings. You can see reviewers created solely to review one or a few of these 4 restaurants. All these reviewers are Nepalese or Indian.
I can do an association rule mining across all these profiles and get more associations to show how these reviewers are having a strong correlation with each of these. These 4 may be more than 4. I mean, if you find a 5th association, try to build a cluster to see whether they share the same pattern. I am just a volunteer TripAdvisor member. I gave up after finding 4.
1. It is highly unlikely that a large share of reviewers visited all 4 of these restaurants in 2 different countries, and created their accounts to review only these 4!
2. I suspect they have some incentives.
2.1. I have previously seen random employers in freelancer websites seeking freelancers to bulk review their pages in Facebook, TripAdvisor, etc..
2.2. They are probably friends of the owner. In case of Leo, it is currently #1 in Lisboa with just 136 reviews. These reviews can be from bots. Even if they are from real humans, it is not hard to find 136 "friends" for an Indian/Nepalese restaurant owner in Portugal.
3. Given that Leo is the #1 in Lisboa now, unsuspecting tourists visit there since it is a "must" now, as listed #1 by TripAdvisor. Some of them are satisfied naturally. The food is not bad - and deserve 3* - 4* anyway. So they leave a positive review. Some were a bit disappointed learning this is just yet another Indian restaurant. However, the initial bootstrap from the fake reviewers were strong enough for Leo.
As a continuous volunteer reviewer in TripAdvisor, I am disappointed to learn that TripAdvisors approval workflow is not smart yet.
1) The ranking algorithm should be changed to
1.1) ensure a meritocracy than a democracy. In the Internet, each account is not necessarily a human. So democracy in such systems is flawed. Currently, there is no difference getting 100 5* reviews from fake accounts or bots and 100, real reviewers with proven track record.
1.2) give more importance to the number of reviews. 1000 4* reviews are probably better than 4.5* rating with 137 reviews. This should of course not harm the new businesses. So needs a smart approach. Requires further research. Currently this is the loophole how Leo managed to become the first in Lisboa!
2) The approval workflow should consist of a data mining approach to ensure reviews are not creating a pattern. As of now, I was able to find a pattern very easily among these companies. With a large set of engineers and the management interface/API, this should be simple for TripAdvisor team.
3) Fix the reporting system. Currently it is a bot. First, I report, and a canned response asked me to send an email to this address. I am not even sure whether this will be considered properly.
Leo coming to the top spot reminds me the story - http://www.independent.co.uk/l
The difference is Leo actually exists as a normal Indian/Nepalese restaurant. But there are much better Nepal or Indian restaurants around, and this surely is not the #1 of Lisboa.
These first 100 reviews were given by fake reviewers to give an initial bootstrap to secure the first place, and following were social engineering. The tourists who blindly follow TripAdvisor and pay a visit here assuming this to be the best of Lisboa. Following this huge popularity, this small canteen restaurant is even unable to cope with the number of customers, making the waiting time grow large. Unsuspecting customers take all these positively. Some even fell for the mediocre Indian food, which can also be found in any other Indian/Nepal/Bengal restaurant around.
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