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Junk Mail Filtering

Feature details

Xeams uses a sophisticated score based mechanism to decide if an email should be considered junk. Every incoming and out-going email is assigned a score. Based on this score, Xeams assigns one of three categories to the email:

1. Junk
2. Possible Junk
3. Good

Besides Junk and Good, Xeams utilizes a third category called Possible Junk. Occasionally, if an email to too close to being good or junk, it is assigned this category, providing the users to manually decide if they want to mark them as junk or good. By default if an email gets a score less than 60, it is considered good. A score of 100 or higher is considered junk. Score between 60 and 100 is considered Possible Junk.

Scoring criteria

Scoring is done based on several built-in rules. Every rule in the system can take the score either in the positive or negative direction. The final score decides the category of the email. Rules in Xeams can be further divided into two categories:

1. User defined rules
   
2. Self-learning rules

Several user-defined rules are bundled with Xeams at the time of installation. All of these rules has a default score and are fully user configurable.

Self-learning rules adapt to the environment of your users. For example, it learns from the past history of emails to assign a score to future emails. One such rule is called Bayesian Analysis. Another example of self-learning rule is when a local user sends a message to someone outside the network. Xeams remembers who the recipient is and gives credit to that user if he/she sends a reply back.

Score reasoning

Many spam filtering solutions block messages without giving an adequate reason of why it was selected as junk. Xeams, on the other hand, gives a detail description of why a particular email is considered junk. This description is very useful for administrators who want to fine tune the filtering rules.

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Types of rules in Xeams for email filtering

Custom filters
Custom Filters	Custom filters are the most powerful and effective filters used in Xeams to detect junk messages. Often spammers use several tricks to avoid being filtered. These custom filters are specially designed to detect such tricks. We believe that these custom filters are so effective that leaving just these filters on you can eliminate 90% of all junk messages.
IP/Domain Based Rules
RBL	The word "RBL" stands for Real-Time Blackhole List. It refers to several services on the Internet that keep a database of IP addresses belonging to known spammers, virus sources and other exploits. Xeams queries these servers to check if the IP address exists in such a list.
SPF Check	The word "SPF" stands for Sender Policy Framework. SPF records are used to prevent email forgery on the Internet. Many companies publish their SPF data through their DNS server, which includes a list of IP addresses where an email can originate. Xeams tries to match the SPF record for incoming messages and assigns a score if a mismatch is found.
DKIM Check	Sender's domain name is checked for forgery using the DomainKeys Identified Mail (DKIM).
DMARC	Incoming emails are checked for DMARC alignment, which is based on sender's domain rather than the IP address.
Black/White listing	Administrators can either black list or white list IP addresses in Xeams. A black listed IP address is assigned a positive score, whereas a white list IP address is assigned a negative score.
Content Filters
Finger print analysis	Xeams uses a proprietary method of creating a finger print of every email. This finger print is then compared with future messages to determine if it is part of a bulk-mail campaign.
Image analysis	Embedded images in emails are analyzed for patterns.
Body and Header	Xeams utilizes a two-pass approach to analyze the body of every message. It then compares it with a known list of keywords containing a score. Rules can be specified for the following sections: Subject Body Attachments Header
Anti-Virus	There are three types of virus detection in Xeams Built-in detector, which checks for obvious signs of an attachment containing a virus Integration with CLAMAV - an open source virus protection Integration with any other virus detector that works from command line. More info...
Adaptive Filters	Adaptive filters are self-learning filters that gets smarter by analyzing the patterns of previously sent and received emails. These filters include: Bayesian analysis Manually marking messages junk or good Sender history tracking
Challenge Response	Challenge response is a mechanism where the system sends a challenge email to the sender to verify if it is a valid message. This type of filter is disabled by default but can be enabled if the users want to use it.