Colin Cochrane

Colin Cochrane is a Software Developer based in Victoria, BC specializing in C#, PowerShell, Web Development and DevOps.

Catching Unwanted Spiders And Content Scraping Bots In ASP.NET


If you have a blog that is even moderately popular then you have likely fallen victim to some form of content scraping.  Ever since it became possible to earn money through ads on a website there have been people trying to find ways to cheat the system.  The most widespread example of this comes in the form of splogs and similar spam-based websites, which consist only of ads from Google AdSense and duplicated content that is scraped from other sites.  In this post I will share a method you can use to identify "evil" spiders and content scraping bots that are wasting your website's resources.

I'll start off by defining what is considered an "evil" spider/bot.  For our purposes here, we'll be looking at spiders and bots that ignore robots.txt and nofollow when crawling a site.  These are spiders and bots that offer no value to you in allowing them to crawl your site, as the major search engines use spiders and bots that respect these rules (with the unique exception of MSN who employs a certain bot that presents itself as a regular user in order to identify sites that present different content to search engine spiders than users).  

Of these valueless spiders, some are almost certainly going to be some form of content scraping bot, which is sent to literally copy the content of your site for use elsewhere.  It is in your best interest to limit how much of your content gets scraped because you want visitors coming to your site, not some spam-filled facsimile.

This method to identify unwanted spiders involves the creation of a trap,  which can be created as follows:

1) Create a Hidden Page

To identify these undesired visitors you need to isolate them.  Create a page on your site, but do not link to it from anywhere just yet.  For the purposes of my examples, I'll call our example page "trap.aspx".


Now you want to disallow this page in your robots.txt.


With this trap page disallowed in the robots.txt, it will prevent good spiders from crawling it.  What is needed now is a link to the trap page with the rel="nofollow" attribute, which should be placed on your home page for maximum effect.  The link must be invisible to users otherwise you might mistake a unwitting visitor for a bad spider.

<a rel="nofollow" href="/trap.aspx" style="display:none;" />

This creates a situation in which the only requests for "/trap.aspx" will be from a spider or bot that ignores both robots.txt and nofollow, which is exactly the kind of bots we want to identify.

2) Create a Log File

Create an XML document and name it "trap.xml" (or whatever you want) and place it in the App_Data folder of your application (or wherever you want, as long as the application has write-access to the directory).  Open the new XML document and create an empty root-element "<trapRequests>" and ensure it has a complete closing tag.

<?xml version="1.0" encoding="utf-8"?>
You can use whatever method is best for you to log the requests, you do not need to use an XML document.  I am using XML for the purposes of this example.

3) Log What Gets Caught In The Trap

With the trap in place, you now want to keep track of the requests being made for "trap.aspx".  This can be accomplished quite easily using LINQ, as illustrated in the following example:

Imports System.Xml.Linq
Partial Class trap_aspx Inherits System.Web.UI.Page
Protected Sub Page_Load(ByVal sender As Object, ByVal e As System.EventArgs) _ Handles Me.Load
  LogRequest(Request.UserHostAddress, Request.UserAgent)
End Sub

Private Sub LogRequest(ByVal ipAddress As String, ByVal userAgent As String)
Dim logFile As XDocument


    logFile = XDocument.Load(Server.MapPath("~/App_Data/trap.xml"))
<date><%= Now.ToString %> </date>
<ip><%= ipAddress %> </ip>
<userAgent><%= Now.ToString %> </userAgent>
Catch ex As Exception
End Try
End Sub
End Class

This code sets it up so every request for this page is logged with:

  1. The Date and Time of the request.
  2. The IP address of the requesting agent.
  3. The User Agent of the requesting agent.

You can, of course, customize what information is logged to your preference.  The code will need to be adjusted if you are using a different storage method.  Once done, you will end up with an XML log file (or your custom store) with every request to "trap.aspx" that will look like:

<?xml version="1.0" encoding="utf-8"?>
<date>12/30/2007 12:54:20 PM</date>
<date>12/30/2007 2:31:51 PM</date>
Now you've set your trap and any unwanted bots and spiders that find it will be logged.  You are then free to use the logged data to deny access to offending IPs, User Agents, or by whatever criteria you decide is appropriate for your site.

Is There Added Value In XHTML To Search Engine Spiders?

The use of XHTML in the context of SEO is a matter of debate.  The consensus tends to be that using XHTML falls into the category of optimization efforts that provide certain benefits for the site as a whole (extensibility, ability to use XSL transforms) but offers little or no added value in the eyes of the search engines.  That being said, as the number of pages that search engine spiders have to crawl continues to increase every day, the limits to how much the spiders can crawl are being tested.  This has been recognized by SEOs and is reflected in efforts to trim page sizes down to make a site more appealing to the spiders.  Now it is time to start considering the significant benefits that a well-formed XHTML document can potentially offer to search engine spiders.

Parsing XML is faster than parsing HTML for one simple reason: XML documents are expected to be well-formed.  This saves the parser from having to spend the extra overhead involved in "filling in the blanks" with a non-valid document.  Dealing with XML also opens the door to the use of speedy languages like XPath that provide fast and straightforward access to any given part of an XML document.  For instance, consider the following XHTML document:

<?xml version="1.0" encoding="utf-8" ?>
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "">
<html xmlns="" xml:lang="en">
    <title>My XHTML Document</title>
    <meta name="description" content="This is my XHTML document."/>
      <h1>This is my XHTML document!</h1>
      <p>Here is some content.</p>

Now let's say we wanted to grab the contents of the title element from this document.  If we were to parse it as straight HTML we'd probably use a regular expression such as "<title>([^<]*)</title>" (As a quick aside, I want to clarify that HTML parsers are quite advanced and don't simply use regular expressions to read a document).  In Visual Basic the code to accomplish this would look like:

Imports System.Text.RegularExpressions

Class MyParser

  Function GetTitle(ByRef html As String) As String 
    Return RegEx.Match(html,"<title>([^<]*)</title>").Groups(1).Value 
  End Function 

End Class 

If we were to use XPath, on the other hand, we would get something like this:

Imports System.Xml 

Class MyParser 

  Function GetTitle(ByRef reader As XmlReader) As String 
    Dim doc As New XPath.XPathDocument(reader) 
    Dim navigator As XPath.XPathNavigator = doc.CreateNavigator
    Return navigator.SelectSingleNode(&quot;/head/title&quot;).Value 
  End Function 

End Class

Don't let the amount of code fool you.  While the first example uses 1 line of code to accomplish what takes the second example 3 lines, the real value comes when dealing with a non-trivial document.  The first method would need enumerate the elements in the document, which would involve either very complex regular expressions with added logic (because regular expressions are not best suited for parsing HTML), or the added overhead necessary for an existing HTML parser to accurately determine how the document "intended" to be structured.  Using XPath is a simple matter of using a different XPath expression for the "navigator.SelectSingleNode" method.

With that in mind, I constructed a very basic test to see what kind of speed differences we'd be looking at between HTML parsing and XML (using XPath) parsing.  The test was simple: I created a well-formed XHTML document consisting of a title element, meta description and keywords elements, 150 paragraphs of Lorum Ipsum, 1 <h1> element, 5 <h2> elements, 10 <h3> elements and 10 anchor elements scattered throughout the document.

The test consisted of two methods, one using XPath, and one using Regular Expressions.  The task of each method was to simply iterate through every element in the document once, and repeat this task 10000 times while being timed.  Once completed it would spit out the elapsed time in milliseconds that it took to complete.  The test was kept deliberately simple because the results are only meant to very roughly illustrate the performance differences between the two methods.  It was by no means an exhaustive performance analysis and should not be considered as such.

That being said, I ran the test 10 times and averaged the results for each method, resulting in the following:

XML Parsing (Using XPATH) - 13ms

HTML Parsing (Using RegEx) - 1852ms

As I said, these results are very rough, and meant to illustrate the difference between the two methods rather than the exact times. 

These results should, however, give you something to consider in respect to the potential benefits of XHTML to a search engine spider.  We don't know how search engine spiders are parsing web documents, and that will likely never change.  We do know that search engines are constantly refining their internal processes, including spider logic, and with the substantial performance beneifts of XML parsing, it doesn't seem too far-fetched to think that the search engines might have their spiders capitilizing on well-formed XHTML documents with faster XML parsing, or are at least taking a very serious look at implementing that functionality in the near future.  If you consider even a performance improvement of only 10ms, when you multiply that against the tens of thousands of pages being spidered every day, those milliseconds add up very quickly.