I’ve been seeing a lot of very clever spam getting through Askimet’s net lately. At first they completely threw me and I let them go. It’s only been recently that I’ve delved deeper and realised that everything isn’t as it seems. These are comments I’ve received …

is there a FREE program that i can add alpha channels to png imagesIMPORTANT: please include a tutorial on how …

and this equally baffling one …

Interesting. Not that bad as you are saying. Keep trying. Thanks

These comments were not completely out of context to the posts they were commenting on but were contextless enough to seem … well, odd.

Digging deeper (but not too deep) revealed that the authors were an assortment of retailers and services that could only have been spam clientele. You have to hand it to the spammers though, this is very clever spamming. They seem to be able to generate the comments based on other comments on the same subjects or are able to structure generic comments that fit the tone of the post.

Pearl has a similar problem and a great church sign image here.

Thom James has an interesting post on a similar and much less perceptible comment spamming technique here.

Anyway, I’ve installed reCaptcha to try and stop this. ReCapthcha has a novel way of using the data that users input …

reCAPTCHA improves the process of digitizing books by sending words that cannot be read by computers to the Web in the form of CAPTCHAs for humans to decipher. More specifically, each word that cannot be read correctly by OCR is placed on an image and used as a CAPTCHA. This is possible because most OCR programs alert you when a word cannot be read correctly.

But if a computer can’t read such a CAPTCHA, how does the system know the correct answer to the puzzle? Here’s how: Each new word that cannot be read correctly by OCR is given to a user in conjunction with another word for which the answer is already known. The user is then asked to read both words. If they solve the one for which the answer is known, the system assumes their answer is correct for the new one. The system then gives the new image to a number of other people to determine, with higher confidence, whether the original answer was correct.