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Message Sniffer (SNF) is an intelligent anti-spam scanner that uses advanced pattern recognition and collaborative learning technologies to accurately identify spam, scams, viruses, and other email borne malware at your email server or gateway (before it gets to your inbox).
Your trial request will be sent to ARM Research Labs, Inc. for consideration. If your trial request has been accepted, within 24 hours (usually much sooner) you will receive an e-mail from ARM with a link to download the Message Sniffer software, a license and authentication key to setup the software on your server, and an account will be setup on ARM’s system.
Please note that the email address you provide must be on the server that will be testing Message Sniffer. Please use an address that is hosted on a system that you personally manage. Message Sniffer is designed to be installed on an email server or filtering appliance. We will NOT fill orders with email addresses from hotmail, gmail, yahoo, etc.
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Message Sniffer (SNF), from ARM Research Labs, is a high performance message scanning engine that uses advanced pattern recognition and collaborative machine learning technologies to accurately identify spam and email borne security threats (viruses, malware) at your email server or gateway (before it gets to your inbox). The engine is designed for high-speed, high-availability applications on many platforms including Windows, Linux and BSD based systems. A professionally managed rulebase is provided via subscription and is updated frequently throughout the day (24×7) by analysts and intelligent monitoring systems.
Message Sniffer is about raw power, reliability, and effectiveness. The Message Sniffer engine requires no “training period” and does not rely on DNS based spam blocking lists (DNSBLs) or external database lookups which can be slow to respond and can introduce heavy loads to critical network infrastructures.
Message Sniffer’s adaptive, comprehensive scanning engine examines an entire message and its structure searching for combinations of spam, virus, and malware characteristics including unusual headers, structural artifacts, message source behaviors, obfuscation techniques, email and url targets, binary and image signatures, unusual code fragments, and even coding styles.
While training is not required, the Message Sniffer engine does become more accurate and more efficient over time by learning new patterns from your system and sharing pattern rule and IP reputation data with other SNF nodes. Each SNF instance is a small part of a much larger “brain” that constantly learns about new spam, viruses, and malware.
