Image-based spam defeating filters

By on
Image-based spam defeating filters

Overall spam levels have soared by more than 67 per cent, and image-based spam by more than 500 per cent, since August, according to new figures from security vendor Barracuda Networks.

The company said that it has seen a marked increase in simple-text messages, particularly 'penny stock' scams, because these forms of spam are particularly well suited for text-only email.

As the call is simply to transact a stock, these emails need not reveal their intent through embedded URLs or HTML tags.

"The observed increase in the volume of trading in penny stocks hyped in spam emails provides significant financial motivation for speculators to send this type of spam," said Stephen Pao, vice president of product management at Barracuda.

The volume of other forms of spam messages has also increased dramatically, including messages pitching diet pills and other drugs.

"Across the board, we are observing more spam and more sophistication in sending the spam," said Pao.

Obfuscating text spam usually involves misspelling key words or randomly inserting unrelated phrases to throw off spam filters.

Sophisticated spammers generally design and test their messages against the current spam definitions of popular spam filters.

Blocking messages engineered to pass through filters therefore requires early detection of an outbreak and rapid deployment of mitigation strategies.

Barracuda also reported a considerable climb in the volume of image-based spam, a trend that began more than six months ago.

Because developing stock spam that can pass through filters often requires the spammer to degrade the readability of the messages, stock spam also makes up a significant percentage of image spam.

Optical character recognition techniques and fingerprint methods are some of the weapons used by anti-spam companies.

"Image-based spam has created problems for many solutions that do not have the comprehensive feature set needed to protect against it," said Pao.
Copyright ©

Most Read Articles

Log In

|  Forgot your password?