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What is Spam Filtering?

Spam filtering is the use of a dedicated security program to detect unsolicited, unwanted, or suspicious emails and filter them out of the user's email inbox. Spam filters will assess incoming emails using a set of different criteria.

If the email seems safe enough depending on the criteria it is judged upon, it will pass through the filter. However, if the email does not score well on the set criterion, it will be moved to your email's spam folder instead.

Not all spam filters work the same way or use the same criterion to assess incoming emails. Therefore it becomes difficult to avoid "false positives" from aggressive spam filters. As a result, even compliant senders may be flagged as spam. If you're sending out marketing emails to your prospects, for instance, there is a high chance they may be sent to the spam folder instead of the user's inbox.

This is also why if you're expecting an email from someone but can't see it in your inbox, you should check your spam folder in case it was flagged down.

Spam filters have evolved, they incorporate AI and machine learning to better filter through incoming emails. Spam filters are also being personalized - they study what a user considers spam, even if another user may consider it important. In this way, the correct emails are allowed through.

Spam filtering programs are compiled of multiple features to protect you from excessive spam emails and their accompanying threats. For instance, they will scan both inbound and outbound emails to protect you and your users from spam, malware, and phishing attacks. They will also be able to detect viruses, malicious attachments, denial of service attacks, and some types of phishing attacks.

The proper spam filtering solution should work with several platforms, should provide you with detailed logs and reports, should be easy to operate, and should be able to detect spam in other languages as well.

If you understand how spam filters work you can minimize the chances of your complaint emails being rendered as spam. Here we'll be going over spam filters and the types of spam filters you'll commonly find. We'll also discuss how you can use and alternatively, avoid spam filters,

Why is Spam Filtering Important?

Nearly 320 billion spam emails were sent every day in 2021, and a significant part of these spam emails are malicious including trojans, spyware, and ransomware. While spam filters may not always be accurate, they are still crucial for your security.

Many malware attacks use emails to trick a user into downloading malicious attachments onto their computers. One spam email that gets through can easily take down an entire organization. Spam filtering will never allow these messages from getting into your inbox in the first place, protecting you and your organization.

In short, a business without spam filtering is incredibly vulnerable. Spam emails can clog up your inboxes and overload your servers with non-essential emails. What's more, if your servers are overloaded they may be converted into spam servers themselves. This is why you must invest in a quality spam filtering program.

How Does a Spam Filter Work?

A spam filter will scrutinize incoming emails using a set of filters and protocols to determine which incoming messages are spam and which are safe. The most basic approaches to filtering spam are mostly similar across all spam filtering solutions.

The spam filtering software will inspect the header information of your email and look for any signs of malicious content. The header information examined will include the IP address of the server that sent the email, the date and time the email was sent, the message ID, DKIM signature, etc. Spam filters will look for any attempts at forging this information or look for discrepancies that may indicate that the email is spam.

They will then determine the sender of the email and compare it with blacklists of spammers. ISPs and email service providers will collect lists of known scammers, and publish them on credible platforms. This is also why it's recommended that you mark any spam emails you receive, you might be saving the next person from having a similar experience.

Most importantly, spam filters will analyze the content of the email for patterns that might indicate it is spam mail. Although this method may lead to false positives it is the best way to filter out spam messages. Essentially the filter will check for suspicious content in the body of the email; certain words or images are consistently used by spammers. The content filter can also be configured to use custom words and phrases during filter processing.

When all these work together, you'll have multiple layers of security separating inbound spam messages from your inbox. This makes it incredibly difficult for suspicious emails to get through.

What are the Types of Spam Filters?

There are many types of spam filters available for use. If we talk about spam filters based on deployment, there are three main identifiable types i.e. those hosted on "cloud", those hosted on-premise appliances, and those that are software-based (installed on PCs).

However, if we differentiate spam filters based on their functions and protocols, there are various other types. We'll be discussing some of the most frequently used types below:

1. Heuristic Filter

Heuristic filters are a type of rule-based spam filtering technique. The term "heuristics" essentially means to use rules, estimates, or educated guesses to find a satisfactory solution to an issue. Such an approach can be successful where timely action is required. Heuristic solutions in email spam filtering are used to analyze text or content using various algorithms and resources.

Here the spam filter will use existing rules and high-level algorithms for the heuristic analysis of content i.e relying on experience or specific intuitive criterion. If any of the detected text or content matches specific patterns detected in spam emails it will add to the score of a message. The higher the score the more likely it is to be filtered as spam, otherwise, it is counted as a valid email.

The rules used to rank emails are constantly updated over time as spammers continue to introduce new spam messages that can pass through email filters undetected.

2. Word Filter

This is probably one of the simplest and most used email spam filters. As the name suggests, this filter will scan through the content of incoming emails and look for words that are commonly used in scam emails. This will help them identify spam i.e. it will block emails if they contain any of the predefined words. However, with these, there is always a concern of false positives,

What's useful is that you can also choose the terms you hope to block out from your inbox. However be careful when doing so, some words may end up blocking both legitimate messages and spam messages. Good use of word filters would be to filter out emails that use inappropriate language or contain explicit content. This is suitable for emails that are used in business communications or professional settings.

When using word-based filters, always make sure that the word list used by spam filters is updated regularly. This will protect your inbox from new emerging word patterns in spam emails.

3. Rule-based Filter

Rule-based spam filters are a type of content-based filter that uses a set of customized rules, typically designed by an organization to filter out emails from certain blacklisted senders or emails containing spam words in their subject line or email body.

These will allow users to establish rules for filtering and apply them to all incoming emails. Whenever the content of an incoming email matches that of one of the pre-defined rules, it will be forwarded to the spam folder. Similarly, you can set the filter to look for particular words or phrases in the header of the email. This can be useful if you want to filter out emails from certain memberships or marketing campaigns that you don't want to be a part of.

Initially, when an email is received, it is at a 0 score level. Then the spam filter will analyze the content, and header of the email against existing rules, and every time they detect any spam words it will add to the score of the email. In the end, the final score is assessed. If it crosses a certain threshold value (an average) then it will be marked as spam.

There are, however, certain drawbacks to such filters. For instance, the word SALE could be written as S*A*L*E to bypass the filters. Moreover, such filters lack self-learning capabilities so they are not entirely flexible.

4. Content Filter

Content-based filters are used to filter spam emails from incoming emails by examining the content of emails. We've already discussed heuristic and word-based filters; these are both types of content filters. Content filters will also incorporate such heuristic filter-based ruling and machine learning algorithms to weed out spam emails.

Content filters will take the text enclosed within an email and decide if it is to be marked as spam or not. Most spam filters are predictable enough, they contain enticing and inviting content and usually offer some sort of feals, or promote explicit content. Content filters are created so they can filter through these emails effectively.

For instance, most spammers tend to use words such as "discount" or "special offer" multiple times throughout the email, this can trigger the spam filtering software.

5. Bayesian Filter

Bayesian filters are another content-based filter but these are far more intelligent than our previously discussed filters. These filters analyze user actions; if a user constantly marks emails from a certain sender as spam the filter will look for emails from that sender and send them to spam automatically. In other words, it is trained by the user

These filters use machine learning and advanced algorithms to distinguish unwanted or dangerous messages from legitimate messages. The filter will take words and phrases from legitimate emails and add them to a list, it will do the same to words found in spam emails. These lists will help calculate the probability that the email is spam or secure.

The longer the Bayesian filter is in use, the more efficient it will be in its functionality. The user can also go back and review the software's decision, in this way any false positives can be uncovered. The software will adapt to this form of training and will therefore become more and more efficient over time.

6. Blacklist Filter

Blacklist filters, as the name suggests, make use of names added to a "blacklist". In this case, the blacklist comprises senders that are known to send out spam emails. These blacklists are generally created by internet service providers and email platforms; a company can also use its spam blacklist to filter through emails.

These blacklists are updated regularly because spammers can always change their email addresses if they believe they've been added to a blacklist. This is why blacklists need to be constantly updated.

Note that such blacklists tend to contain both email addresses used in spam emails and IP addresses used as well.

7. Whitelist Filter

Whitelist filters are the exact opposite of blacklist filters. These filters work by using a list of senders and IP addresses that are legitimate or trustworthy. These emails are acceptable for inboxes. These lists contain both sender emails, domain names, and URLs that can be used to identify legitimate emails.

So instead of indicating which emails to send to a spam folder, these filters will indicate which emails are to be sent to the inbox. The only drawback to such lists is that if the sender you have marked as trustworthy has been compromised, for instance, through viruses or trojans then you may also receive spam messages containing the same virus. But since you've marked the sender as trustworthy, they will send it to your inbox instead of the spam folder.

8. Greylist Filter

Greylist filters work by temporarily blocking any incoming emails from a new unknown sender. As a result, the sending server will receive a temporary 451 Error. Legitimate email servers will try to resend the email after a few minutes. The temporary error will be read by the sending server as a "delayed delivery notification", so it will resend the message after a few minutes. On the other hand, a spammer will ignore such error messages.

If the email is received again after a short period, the sender details are added to a database. From then on, any new emails received from that sender will not be greylisted. The filter may also alternatively receive the email and proceed with anti-spam scanning before they are deemed trustworthy.

Since spammers and bulk mailers won't go back to resend emails after they received an error, such sender details are added to a spam list.

How to Use Spam Filter?

Spam filters all work on the same basic objective, to make sure spam emails are left out of user inboxes. We've discussed the various types of spam filters, each using different filtering methods to weed out spam emails.

To start working with a spam filter, you must first search for the right email spam filter service. The ideal spam filter service will provide you with a wide range of functions, and should be able to effectively flag down spam emails and email-borne threats without slowing down your normal operations. It should also be able to filter outgoing mail, not just inbound emails.

Why is this important? Because if your IP or domain is being used to send our spam emails then your domain may end up on IP blacklists. This will damage your credibility and limit the number of customers receiving your emails.

Once you have your spam filter service you can tailor filters to meet your needs and those of your customers. For instance, you can set rules to send certain trustworthy emails to certain subfolders. However, emails that aren't identified may be scrutinized. The emails that are marked as spam will allow for the creation of a database containing common characteristics of spam emails. This way, future spam emails are effectively filtered out.

How to Avoid Spam Filters?

Spam filters use AI and machine learning to detect unsolicited and unwanted emails, however, these filters are not always accurate and may deliver a false positive. As a result, even legitimate emails, such as yours, may end up in the spam folder at the recipient's end. However, there are ways you can reduce the chances of getting marked as spam.

For instance, you should start by creating a unique subject line, perhaps something unique to the recipient instead of using misleading subject lines. Avoid trigger words that may seem too "sales-y", keep your format simple and clean, and limit the number of URLs you have added (Most spammers tend to add plenty of URLs throughout the email in the hopes that a user may unknowingly click on one).

Make sure that your email contains quality content. The more engagement your email gets from users the less likely you'll end up in the junk or spam folder. Also try to not add attachments to your email, instead lead your users to a new landing page through a CTA. Attachments tend to take much longer to load and may lead your email to spam.

You can also ask your subscribers to add you to their approved contact list. This way you'll rarely end up in the spam folder.

Does Firewall Do Spam Filtering?

A firewall is a type of network security system that monitors your internet traffic flow to and from your network using a defined set of security rules; it will filter out suspicious content or users from gaining access to your network.

A simple look at its definition may tell you that firewalls are quite similar to spam filters when it comes to the function they perform. Dedicated email firewalls can also be set up around complex networks to filter incoming and outgoing email server traffic. These also function using a set of pre-defined rules and in this way can protect your inbox from spam emails. Email firewalls will analyze any incoming messages to determine if they are to be flagged as spam or not.

Zenarmor, for instance, is a popular next-generation firewall deployed as software, virtually anywhere. It can be used without the need for a dedicated appliance, by small and large medium businesses alike. As a part of their cloud threat intelligence services, they allow for spam site blockage i..e blocking sites that distribute spam.

Zenarmor: Essential Security Control Settings

Figure 1: Zenarmor: Essential Security Control Settings blocks Spam sites

What is the Difference Between Spam Filter and Firewall?

The basic difference between a spam filter and a firewall is the number of services each solution offers. While a spam filter can essentially keep you safe from incoming unsolicited emails, however most spam filters are email specific. On the other hand, a firewall can not only filter emails but will also help filter other threats from incoming network traffic. They offer protection from a much wider range of cyber attacks, which are far more sophisticated.

Moreover, many believe that a firewall acts as the first line of defense for your network, email spam filters come secondary. Firewalls are therefore given priority when it comes to deployment and email spam filters are added later on.

What are the Best Spam Filters in the Market?

There are plenty of spam filters out there and so choosing the right one can seem difficult. Some of the most popular spam filters we've seen in the market so far include:

  1. SpamTitan
  2. ZEROSPAM
  3. Trustifi Inbound Shield
  4. MailChannels
  5. Mailwasher
  6. N-able Mail Assure