PDF Spam Jumps 500% in Two Weeks

CUPERTINO, Calif. -- Proofpoint, Inc., the leading provider of unified email security and data loss prevention solutions, today announced the availability of a new version of its machine learning-based anti-spam technology that offers enhanced protection against PDF spam (unsolicited email messages where the message “payload” is hidden inside of an Adobe Acrobat PDF file attached to the message) and other forms of attachment-based spam, such as Excel-based spam. Through a combination of analysis techniques, including the ability to open, extract and analyze the contents of message attachments, the Proofpoint Spam Detection™ module—powered by Proofpoint MLX™ machine learning technology—offers higher than 99% effectiveness against PDF-based spam.

During the past two weeks, PDF-based spam surged approximately 500%, from less than 5% of all spam, to nearly 25% of all spam observed by the Proofpoint Attack Response Center. In comparison, image-based spam using GIF or JPEG has represented less than 4% of all spam during the same period.

“Spammers have realized that most anti-spam solutions do not analyze PDF attachments, so they simply started putting their same old spam content, whether text or images, inside of PDF files,” said Andres Kohn, vice president of product management for Proofpoint, Inc. “We started seeing small amounts of PDF spam months ago, but the volumes surpassed even image-based spam at the beginning of August, and have now quintupled in the past two weeks.”

Proofpoint Inc.