Maillier provides flexible anti spam filtering of inbound / outbound messages to protect user mailboxes from unsolicited or malicious email. Mail is scanned at the gateway level, before the messages are delivered to user accounts. A complete Web-interface is included for users to maintain and configure Anti-Spam settings via Maillier.

Filtering features:

• Anti Spam Protection
  The SpamAssassin backend provides blacklist and whitelist functionality, text and header analysis, Bayesian (learning) filters, and DNSBL support. User mailboxes are kept clean of unwanted Spam messages that clutter the filesystem and waste user productivity.
  
  
• Group and User Filtering
  Email filters can be defined for specific email accounts, groups, and domain names.
  
  
• User Level antispam Settings
  Using the Maillier WebMail interface users can define custom antispam settings for their account. Users can choose the level of antispam-filtering, where to route Spam messages, define user-level white/blacklists, and enable Bayesian filtering.
  
  
• Whitelist & Blacklist support
  The individual users can define Blacklists -- lists of domain names & email addresses from which undesired mail is known to originate, and should be ignored. Adding a domain name or email address to a Blacklist automatically qualifies messages from those locations as Spam. The Whitelist feature allows the admin to enter trusted domain names & email addresses so that messages from those senders will be bypassed by the anti spam filter. Adding a domain name or email address to a Whitelist ensures that messages from those locations will not be handled as Spam.
  
  
• Bayesian filtering
  The Bayesian filters identify Spam by searching incoming messages for tokens (words or short character sequences that are commonly found in Spam). As the filter rules qualify messages as Spam, characteristic strings are logged which can be used to identify future instances of undesired content. The filters will be trained automatically as email is delivered to Maillier. Optionally, users can train the Bayesian filter by moving selected messages to the anti spam folder via the Webadmin interface.
  
  
• DNS Blacklist (DNSBL) support
  DNSBL is a network of services that provide blacklists of known Spammers. Incoming messages can be checked on the fly against the DNSBL network to determine if the originating address is known to be a source of Spam.
  
  
• Pattern matching engine
  Messages are parsed through various tests to determine if the message is Spam. Keywords and regular expressions are pattern-matched with incoming emails to identify unwanted messages. The pattern-matching engine is optimized for maximum performance and does not slow down email delivery.
  
  
• Message redirection
  Email marked as Spam can be diverted in several ways: Messages can be deleted from the system, moved to the anti spam folder for the local recipient's account, or delivered to the user's Inbox with the Email subject modified to indicate that the message is Spam. The latter ensures that no legitimate messages are accidentally lost or deleted from the system.