Through the history of computers, there were always programs trying to mimic human actions/behavior. From ELIZA in the sixties to these days the task raises in different fields of computers science: artificial intelligence, natural language processing, image processing, etc. Particular type of programs are designed to mimic or automate human-computer interactions. They produce inputs for other programs as if they came from a person. In this post I’m going to introduce those programs, how they work, why is it important to detect (and stop) them, how is it done today and some new ideas I have on the subject.
The power of automation can be harnessed, like all powers, for good and evil. On one hand it can save you a lot of time performing tedious repetitive tasks such as news checking, file downloading, event handling, etc. On the other hand it can be used by advertisers, spammers and soliciters to perform mass-mailing, mass-registering, mass-spamming, etc. As you can guess, some organizations would like to use such an automation while others would like to block it.
Sometimes it is unclear which side is which, for example if I want to download a file from service like “rapidshare”, it would present me with a waiting screen. The sole purpose of this screen, as well as other restrictions they impose on non-paying members is to motivate people to pay. Using automation, my computer could do the waiting and download the files while I’m away, so it’s pretty good from a selfish point of view but pretty bad from their business point of view.
The automation programs can generate data at different levels. To better understand this, let’s first examine typical web interaction: talk-backs. When you talk-back or post comment you use your browser, keyboard and probably mouse too to select (focus on) the text area designed for this purpose, type whatever you have to say and click on “submit” or whatever. What happens under the hood is that your browser sends data to the website, or to be more exact, makes HTTP request to the web server running at the other end, sending data including your talk-back. The web server processes this data and responds according to predefined business logic such as responding with “thank you” and placing your talk-back in queue for approval.
The talk-back is sent along cookies and other data as defined in RFC2616. Since the interaction is well-defined per site (the protocols, parameter names and everything else used as part of the interaction) it’s fairly easy to make a tool that automatically sends data as if it was a web browser operated by a person. From web server point of view it would look exactly the same. Once the interaction is analyzed and understood (can be easily done using proxy or tools like Firebug) a dedicated tool can be built to automate it for example using java.net package, or even as a shell script using curl. Please note that these are no hackers utilities. They’re pretty standard “building blocks” for any web related application/script.
So how can we determine whether it’s really a person using a browser or an automated tool messing with us? The most common solution today is using CAPTCHAs. I’m sure you’ve all seen them before. CAPTCHA is a mean of challenge-response in which the web server generates a picture, usually containing twisted text, and expects the text to be sent back as data. For a human, it’s supposedly easy to understand the picture and type the text in the required field, and for a computer program it’s supposedly difficult to analyze the picture and “understand” the text.
The original idea behind CAPTCHA is nice, but it is becoming increasingly ineffective. Firstly, it is very possible to use Computer Vision techniques alone or together with Artificial Intelligent techniques to recognize the text. Secondly, with publicly available CAPTCHA solving libraries such as PWNtcha or online services such as DeCaptcher, it’s really a matter of how much time/money one is willing to spend rather than a technological challenge. There are also “indirect” ways to overcome CAPTCHA such as analyzing audio CAPTCHA (sometimes available for accessibility purposes) or passing the CAPTCHA images to a different (preferably large traffic) web site to be solved by real humans.
As CAPTCHA breakers are closing the gap, it’s time to present them with new challenges. Don’t get me wrong, I’m not picking a side. I’ve been on both sides, and my interest is pure intellectual, so whoever is upper-handed at the moment is irrelevant. I got some ideas for new challenges. Feel free to implement/use/further develop them. However, I take no responsibility, and I can assure you they are breakable, but they should take the game to the next level.
Let’s first examine Achilles’ heel of current methods:
- They are deterministic: client-server interaction is always the same and can be easily revealed.
- Automation tools are challenged by means of something they need to figure out, usually independently of what those means try to protect.
- CAPTCHAs are presented as images in a format suitable for copying and processing.
The script should present a challenge in a manner it’s response is context dependent for example for talk-backs or comments you can ask about article’s content. Beware that it should be smartly implemented. If you ask multiple choice question, automation tool will try all choices. If response is a single word from the article automation tool may try them all. Anyhow, if it’s inapplicable or you feel it’s more harmful then helpful (by narrowing down response space) you can always revert to letters/numbers combination.
The challenge should not consist of image only. It should be partially an image, maybe as background, and dynamically rendered pixels/lines/polygons/curves or placement of smaller image portions using browser’s rendering engine. Together they should all visually form the “question” (or letters/numbers combination) mentioned in the previous paragraph. This step will make it more difficult for automation tool to process/copy/understand the challenge.
Finally, you can add your own spice just to make things more complex, for example the running script can record time differences between key presses on response field and send them along the response. You can use statistical analysis to determine if it came from human (generally, if auto-filled by robot, even if there is random wait between each key press, standard deviation should be relatively low). This is only one example. You can also invent new things, add random business logics, use self modifying code… possibilities are endless.
I hope you liked my ideas. Let me know what you think.