The Image-Based CAPTCHA: Part 2

• Download demo project #1 - 55.2 KB
• Download demo project #2 - 58.2 KB

Background

The article continues the topic of image-based CAPTCHAs that was started in my previous article, The Image-Based CAPTCHA. Please look through it in order to get some idea about this article's subject.

Image-Based Bot Detector

I made a control - I named it ImageBasedBotDetector - that implemented the idea stated in the previous article. Its code differs from the example posted before, basically because of the separation of the code that renders the control and the code that renders the CAPTCHA image (it is replaced with an HttpHandler). For use, it needs to set TemplateImageFolder to a path where template images are located, and add the registration of the HttpHandler in the web.config.

<httpHandlers>
  <add verb="GET" path="ImageBasedBotDetector.ashx" 
       type="Marss.Web.UI.Controls.ImageBasedBotDetector, Marss.Web"/>
</httpHandlers>

ImageBasedBotDetector can be used as either a finished control, or as a base control if you want to add your own functionality - the GetTemplateImage and DrawCustom methods are virtual and can be overridden. An example of use can be found in demo project #1.

A Few Answers on Your Comments

After the publication of the previous article, I got many comments concerning the reliability of this type of CAPTCHAs. I'll try to systematize and answer them.

Quite possible, no doubt. If it is possible to distinguish between a real person and a fake one on a photo, then it can be done for specific distortions on a picture. Most of the text-based CAPTCHAs are also crackable in 90-99% of the cases, but it does not prevent their general use. The fact is that there is no system that can crack everything; a specific implementation is required in every concrete case. Specific implementations mean resources and money. So, don't worry if your site is not as popular as Yahoo! or Google.

Sure, this is applicable for about 4% of visitors. But, it is hard to imagine a present-day web application that offers site-to-visitor interaction and does not use JavaScript. Besides, if you use ASP.NET controls, then most probably you already have these visitors excluded.

The control now offers three types of distortion: Stretched, Random, and Volute (see picture).

Also, you can implement your own distortion if you set DistortionType to Custom and override the DrawCustom method.

To avoid pixel-to-pixel comparison, an original image is slightly distorted too. As for more complicated comparisons, read paragraph #1.

Besides, a reconstruction of template images set can be avoided if you don't use any images set. It sounds strange, but actually it is rather simple. The basic principle is that though images of specific themes are required, there is no need to sort them manually. So you can use a search engine, for example Google Images search. Select a theme, for example, "Landscape", and choose the appropriate search keywords. Then, override the GetTemplateImage method.

public class AdvancedImageBasedBotDetector : 
             Marss.Web.UI.Controls.ImageBasedBotDetector
{
  //search request pattern

  private const string requestPattern = 
    "http://images.google.com/images?hl=en&q=" + 
    "{0}&gbv=2&svnum=10&start={1}&sa=N&ndsp=20";

  protected override System.Drawing.Image GetTemplateImage()
  {
    //search keywords 
    string[] keywords = new string[] { "forest", "mountains", "waterfall", 
                                       "falls", "hills", "lake"};
    
    Random r = new Random();
    
    //build request url based on keyword that was selected in a random way
    string url = string.Format(requestPattern, 
                        keywords[r.Next(0, keywords.Length)], r.Next(0, 50));
    HttpWebRequest req = (HttpWebRequest)WebRequest.Create(url);
    using (HttpWebResponse resp = (HttpWebResponse)req.GetResponse())
    {
        if (resp.StatusCode == HttpStatusCode.OK)
        {
            string html;
            using (StreamReader sr = new StreamReader(resp.GetResponseStream()))
            {
                //get content of the search results page
                html = sr.ReadToEnd();

                resp.Close();
                sr.Close();
            }

            Regex re = new Regex(@"dyn\.Img[(](?:""([^""]*)""[,)])*", 
                                 RegexOptions.Multiline);
            MatchCollection matches = re.Matches(html);
            if (matches.Count > 0)
            {
                //select one of the image urls found on the search results page
                Match match = matches[r.Next(0, matches.Count)];
                string imageUrl = string.Format("{0}?q=tbn:{1}{2}",
                                        match.Groups[1].Captures[14],
                                        match.Groups[1].Captures[2],
                                        match.Groups[1].Captures[3]);

                //get image
                HttpWebRequest req2 = (HttpWebRequest)WebRequest.Create(imageUrl);
                using (HttpWebResponse resp2 = (HttpWebResponse)req2.GetResponse())
                {
                    if (resp2.StatusCode == HttpStatusCode.OK)
                    {
                        System.Drawing.Image im = 
                            System.Drawing.Image.FromStream(resp2.GetResponseStream());
                        resp2.Close();
                        return im;
                    }
                }
            }
        }
    }
    //use default implementation if getting template image failed for any reason
    return base.GetTemplateImage();
  }
}

If the answer "pleasant variety" does not suit you, then - I guess - it may be ok to say that these type of CAPTCHAs are more user friendly (one mouse click vs. typing 5-6 letters).

1. It is possible to make a system that can recognize images and find the distorted part.
2. A solution that relies on JavaScript is not firm because the script can be disabled.
3. Insufficient accessibility.
4. Possibility to download template images and compare them to an image that is generated by the CAPTCHA.
5. What is this necessary for?

That is all. Start to criticize :).

History

• 1^st July, 2007: Initial version

Other Links

• Articles related to Image-Based Bot Detector at my site