Blekko is the new search engine in the block. It launched in November 2010, raised about $24 million and received a fair bit of press in start-up and tech blogs.
Blekko’s promise is to provide high quality search results. They work on a smaller index of around 3 billion pages (~46 billions for Google). Blekko emphasizes the fact that they eliminate spam, malware and content farms from their results. This statement is displayed prominently on their home page.
|Blekko’s home page|
I’ve blogged a great deal about how spam SEO infects the most popular searches. This is a real problem on Google. So I was very curious to know how a search engine focused on the quality of its search results and committed to remove spam, would do.
Buying software online, currently account for the majority of SEO spam. Google search results are mostly (up to 90% or more on the first 10 results pages) a list of hijacked sites, usually university websites, redirecting to fake stores. The spam pages shown to the search engine indexer look the same and the fake stores themselves are very similar as well.
After investigating, I’m afraid that our results show Blekko doing no better than Google when it comes to filtering out spam. For example, a search for “Buy Windows 7 key” returns mostly spam:
- first page:; 7 out of the 10 links are spam redirecting to another domain, including 4 .edu hijacked sites
|Spam results on the first page|
- 2nd result page: 8 spam links, but one good link to this blog about malicious fake stores!
Still under the radar
Luckily for Blekko users, spammers are not (yet?) interested in them. The spam pages look at the Referer header, among other things, to differentiate between real users and bots (security tools, search engine indexers, etc.). Most of the spam pages redirect users to the malicious sites only if they come from a Google, Bing or Yahoo! search. Users coming from Blekko see the spam page only.
|Spam page on Universitiy website|
All the search engines are having trouble eliminating spam. Blekko appears to be focused on identifying content farms, which usually contain harmless spam, rather than hijacked sites that lead to malicious domains (fake store, fake Antivirus, etc.)
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