Welcome to The Administrator Shortcut Guide to Blocking Spam with Sender Validation!
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Spam—everyone hates it, and it has reached epidemic proportions over the past year. Some estimates list the spam rate as high as 70 percent of all Internet mail traffic. Spam clogs up Internet WAN lines and consumes a significant amount of a user's day. If you have reached the point at which spam is annoying enough to do something about, this guide will help you do so by focusing on the following topics:
Installing spam filtering software on a single workstation is a fairly simple task; however, implementing an enterprise-wide spam filtering solution requires careful evaluation and planning. You can expect difficulties—particularly false positives—when implementing any spam solution. In addition to being prepared for these considerations, you need to be aware of and plan for ongoing maintenance, which can be a hidden cost when implementing a spam solution.
There are many methods to block spam:
However, only sender validation holds the promise of blocking 100 percent of spam. Sender validation has been around for quite some time and has had success in the Post Office Protocol (POP3) market. The concept of sender validation is very simple. If a user that is on your "approved senders" list sends you a message, you get the message. If the user is not on the list, the message is quarantined. Most sender validation spam solutions deal with individual POP3 mailboxes. Although these individual solutions work well, such has not been the case for past network enterprise deployments of sender validation. Sender validation has been criticized as an undesirable solution for fighting spam in enterprise environments. To avoid any problems and benefit from the 100 percent blocking power of sender validation in an enterprise environment, simply select a vendor that has a mature sender validation solution. In this guide, we'll examine how to avoid the pitfalls of sender validation and implement this solution to cut spam to zero.
Fortunately, implementing an anti-spam solution is one of the easiest IT projects to cost justify. Imagine the productivity savings each user will experience if their spam is cut to zero! Typically even a small company can recoup their investment of an anti-spam solution in as little as 2 months. For larger companies, the cost recovery is even faster. Thus, sender validation is a solution that sells itself. Before we jump into how to begin saving money through sender validation, let's briefly establish a foundation of spam history and terminology.
Everyone knows what spam is; we've all received it. It's the automated mass email of advertisements and other annoying email messages. Just as important as defining what spam is, is to define what spam is not: a virus, identity theft, or instant messaging.
Spam exists because it works. When compared with snail mail junk mail campaigns, spam has significantly lower costs. Consider the example that Table 1.1 shows.
Traditional Mail Campaign
Spam Email Campaign
Cost per piece $1.37
Cost per piece $0.001
Mail 10,000 pieces
Total cost is $13,700
Total cost is $1000
Hit rate is 2 percent
Hit rate is .02 percent
Total hits of 200 at $68.50 each
Total hits of 200 at $5 each
Table 1.1: Traditional mail vs. a spam email campaign.
From this very simple example, you can see that spam campaigns typically cost much less per hit than a traditional direct mail piece. But because the hit rate is much lower (in this example 100 times lower) than a direct mail piece, spammers must send out significantly more pieces to achieve the desired number of hits. This the reason that spammers use the "shotgun" approach in their mail campaigns—the cost per piece is almost zero, so spammers can afford to send their message to any email address on which they can get their hands. They don't bother trying to target their lists for specific groups that might be interested in the product. Spam is all about volume; the more messages sent, the better chance of receiving a hit.
Although spammers closely guard their hit ratios, they are making money. However, they must annoy a significant amount of the population to get the desired number of hits—before I implemented a spam solution, I typically received 200 to 300 messages per day. Spam has grown to a point at which both end users and organizations are willing to invest in a solution to stop the spam and recoup valuable lost productivity.
Spammers use email harvesting to continually get new email addresses. They use harvesting spiders/programs such as Atomic Harvester III, Email Marketing, and Text Bomber that monitor the Internet looking for new email addresses to gather. These programs are capable of gathering email addresses on specific Web sites, can target users in specific geographic areas, can target users in specific newsgroups and chat rooms, and can spoof IP addresses of bulk email servers.
For more information about the capabilities of spam harvesting programs, check out http://www.emailemailemail.com/.
One of the more covert harvesting programs uses EMAIL_ID, which will capture your address when you simply visit a site by tricking your browser into giving your name and email address. If the security level on Microsoft Internet Explorer (IE) is set to the default level, you should receive a warning message before this information is submitted.
Spammers might also attempt to guess your email address by using a dictionary/directory attack. This type of attack simply runs down a list of names and tries each one until it gets a hit. When a hit is determined, the spammer exploits the entire domain name by following the naming convention (for example, <first_initial><last_name>@<domain_name>) for email addresses in the domain. Dictionary attacks are common on hotmail.com, msn.com, and other widely used email domains because of their mail volume and number of users. Spammers hit these sites continuously 24 hours a day, 7 days a week with dictionary attacks. When a hit is identified, the email address is recorded, and this list is sold to other spammers. These sites are continuously under attack, so you are almost guaranteed to receive spam if you set up a mail account here.
If your Internet connection slows suddenly you might be under a dictionary or Denial of Service (DoS) attack. Examine the log in your firewall to attempt to identify the source of the attack. If possible, use your firewall to block the IP address(es) from which the attack originates, and contact your ISP and ask them to block the IP address at the backbone to prevent further problems.
In a recent Federal Trade Commission (FTC) study, 86 percent of email addresses that were posted on Web pages, chat rooms, and message boards received spam. One email address received spam 9 minutes after a message was posted in a chat room!
For more information, refer to http://www.ftc.gov/bcp/conline/pubs/alerts/spamalrt.htm.
Thus, never have a direct link from your Web page to a real person's email address. Use a generic email address such as info@<domain_name>. Spammers tend to leave these generic addresses alone, and if they do receive spam, the address can be easily changed. Alternatively, your company can create a Web form (rather than use a generic email address).
I've had mixed success submitting an opt-out request to spam mail. If the spam appears to come
from a legitimate source, I've had better luck with the opt-out request. Be aware, however, that replying to a spam mail verifies to spammers that they've reached a real person. Use the opt-out feature at your own risk.
As a result of the spam problem, 30 states within the United States have passed laws that make it illegal to send spam, but enforcing the laws inter-state and even within the same state (not to mention internationally) is difficult if not impossible. In June 2003, the Burns-Wyden bill passed. This bill legislates that spammers can face up to 1 year in prison and a maximum fine of 1 million dollars. Although anti-spam legislation will help, it probably will not solve the problem. Law enforcement has higher priorities within the IT industry such as catching virus creators and cyber terrorists. Thus, rather than wait for a legal remedy to this problem, the only effective solution is to use a spam blocking tool.
There are quite a few anti-spam software packages on the market, most of which use a combination of spam blocking methods to reduce the amount of spam in a user's mailbox. However, spammers are constantly developing new methods of bypassing spam filters. Thus, except for sender validation solutions (which don't necessitate ongoing updates), spam filtering solution vendors must develop additional methods of blocking spam to keep up with the spammers. Let's examine these methods and their advantages and disadvantages.
For keyword searching, the anti-spam software looks for specific words or phrases in an email. In you're in the market for this type of solution, look for a package that supports keyword phrases, keyword conditions, and keyword searching in either the subject or body of the email message. Keyword searching can reduce the amount of spam by performing a search for words that are likely to be included in the spam message (for example, Viagra, refinance, and mortgage). Phrase searching with conditions will give you more flexibility to search for items such as "need cash" and "refinance." This functionality provides a finer degree of control when searching for keywords and should help reduce false positives. Some spam filter vendors allow you to update your keyword searches based on the most current spam messages on the Internet.
If the message you receive has a consistent word or phrase, keyword searching is an effective method of blocking spam. It is very useful for blocking other unwanted messages that contain viruses, such as the Sobig.F worm, that use the several phrases as the following email message shows:
Re: Approved Re: Re: My details Re: Thank you! Re: That movie Re: Wicked screensaver Re: Your application Thank you! Your details
Although anti-spam software can block unwanted messages that contain viruses, do not rely antispam software as your only virus email scanner. Purchase a virus scan option with the anti-spam package or install a dedicated email virus scanner on your email server.
Unfortunately, this method requires that you receive at least one email with a consistent keyword before you can block future messages with a keyword search. You must manually maintain the keyword list as new spam messages are received, unless the spam filtering vendor supplies updates for you. In addition, this method has the potential to consume considerable resources on the server—for example, if you perform searches on the message body versus the subject line or add keywords to the search list, more resources will be consumed on the server. On a heavily loaded server, some messages can get through the keyword search. Smart spammers randomize the words in the subject and message body in an attempt to bypass the keyword filter. Finally, keyword searches have the potential to cause many false positives depending on the type of mail your company receives.
A mail server configured as an open relay allows spammers to bounce messages off the mail server to send the spammers' messages. Some packages can perform an ORDB check to determine whether a message was received from a mail server that is identified as an open relay (see Figure 1.1).
Figure 1.1: A DNS Blacklists screenshot from GFI Mail Essentials.
Many of these sites can test whether your server is an open relay. When you bring up a new mail server, it is a good idea to test it to verify that the server is not open. If your server is marked as an open relay, you must first close it, then submit it for retesting. If you are running an earlier mail package (for example, Microsoft Exchange 5.0, Novell GroupWise 5.2) that cannot be shut down as an open relay, take a look at the anti-spam features of your firewall. Some firewalls have anti-spam features built-in to their Simple Mail Transfer Protocol (SMTP) daemons that can help close the open relay. Another option is to upgrade your email software to a version that does not allow open mail relaying. An irony of the ORDB is that it provides a convenient list for spammers to relay their messages—the opposite of what the ORDB is trying to prevent. After the server has been retested and is no longer an open relay, it should be removed from the database. If the server is marked as an open relay, it might be listed in multiple databases. If such is the case, you must submit a removal request from each database on which the server is listed. The response time for a removal request varies depending on the database list.
Sometimes after the server is removed from an ORDB, the server might still have difficulty sending mail messages to one or more domains. If all else fails, you can change the external IP address and MX record of the server to bypass this problem. Typically, the ORDBs only list specific IP addresses rather than ranges of IP addresses. Thus, changing your mail server address is a simple workaround if your mail server is identified as an open relay (even though it is not open anymore).
A quick way to test this workaround is to change the outside address of your firewall, then try to send mail to the problem domain(s). If you are successful, issue an MX record change to the ISP that hosts your domain. If this workaround does not work, don't bother with the MX record change—the sending problem lies somewhere else, possibly with DNS, the mail server, or the message is infected with a virus. Be aware that you will temporarily take down your incoming mail while you run this test until you either update your MX record and it propagates throughout the Internet or change the firewall back to its original address. For this reason, it is a good idea to have extra IP addresses when ordering your DSL, T1, or broadband connection from your ISP even if you plan to use Network Address Translation (NAT) on the firewall. If you decide to use this approach, make absolutely sure that your relay is closed before changing the IP address; otherwise, you will end up on the ORDB again.
Checking whether an email message came from a server marked as an open relay can block as much as 50 percent of your spam. Another benefit is that once this method has been configured, there is no on-going maintenance.
Checking an ORDB consumes bandwidth because a lookup must be performed for each received message. If you use this method, rely on one of the larger ORDBs such as ordb.org. Open relay checking can potentially generate false positives because the relay might already be closed. Unfortunately spammers are getting smarter in their relaying methods. In the past they would find an open relay and exploit it until it was marked as an open relay. Now they hop from server to server and relay a smaller number of messages. This process makes it very difficult to identify the mail server as an open relay. Going forward, this anti-spam method will become less effective.
Some mail filtering services maintain their own "real-time" open relay list that is continually updated. When a mail server appears to deliver spam, the relay is tested periodically to verify that it is still sending spam. Once the server stops sending spam, it is automatically taken off the open relay list. This approach was developed to catch the technically savvy spammer that hops from open relay to open relay to avoid detection.
If a message is received from an email address or domain on a whitelist, the message is delivered to the user. If you're shopping for this functionality, look for a package that can support entire domains with one whitelist entry such as *@<whitelist_domain.com> (instead of separately listing individual users in the whitelist). This feature is very useful for users who correspond with multiple users in another company regularly. Of course, you don't want to open an entire domain—such as *@aol.com, *@yahoo.com, and *@hotmail.com—from which users will receive spam on a regular basis, but for other domains, this feature can save a lot of administrative time.
Typically, a whitelist entry overrides conflicting configurations. For example, if a message is received from a user that is on the whitelist, but the message originated from a server marked as an open relay, the message is allowed through. Some software packages can automatically add users to a whitelist when an internal user sends mail to that person. However, this feature can be undesirable, especially if a user decides to opt-out of a mailing list. By replying to the mailing list message, the opt-out address is automatically added to the whitelist. If you decide to turn on the auto-add whitelist feature, make sure your users do not reply to such opt-out email messages. Alternatively, IT staff can simply remove an unwanted address from the whitelist. Many solutions offer the choice of per-person or company-wide whitelists, which enable administrators to decide whether users' auto-add feature will affect other users.
Preloading a whitelist of approved senders will reduce the number of false positives when implementing anti-spam software. For this reason, preloading this list is an integral part of any whitelist implementation. At least, give the whitelist system time to "learn" who your users send mail to before turning on the spam-blocking feature. If the whitelist overrides other filter values, you can use the whitelist and blacklist in combination to filter out spam. (I'll discuss blacklists in the following section.) For example, you can block an entire domain, such as *@hotmail.com, in the blacklist, then selectively list email addresses in the hotmail.com domain for messages from senders you want to pass through the spam-filtering software.
If you do not implement the auto-add whitelist feature, this list must be maintained manually. Even if you preload a whitelist, expect to receive several false positives when implementing antispam software. If you're running Microsoft Outlook, you can export all the email addresses in the contacts list for each user, consolidate the list, format it based on the spam-filtering software requirements, then import the list into the whitelist. The number of manually added whitelist entries should taper off after the package is up and running for a few weeks—especially if you enable an auto-add feature. Both the whitelists and blacklists are responsible for the majority of the ongoing maintenance for anti-spam packages that use these methods of blocking spam.
Blacklists work just the opposite of whitelists—if a message is received from an email address or domain on a blacklist, the message is rejected by the server. Blacklists have the same drawbacks as keyword searching, because you usually have to receive a spam message before you can block it (unless, of course, you already blocked the entire domain).
If spam is consistently sent from a single email address, blacklists are an effective spam-fighting tool. However, more than 75 percent of spam if from a one-time use address, blacklists alone will help to protect against only a quarter of the spam. As I previously mentioned, you can use the blacklist and whitelist combination to block an entire domain, then only let selected messages through the spam filter. If you implement a server-based spam-filtering solution, you need to enter the blacklisted address only once on the server; after the address is blacklisted, all mail received from this address is automatically blocked at the server level.
The biggest disadvantage of blacklists is ongoing maintenance. As new messages appear, the administrator must add the sender's name to the blacklist. Most spammers use "throwaway" email address such as email@example.com. Once the email service recognizes the sender as a spammer, the account is deactivated. However, because many spammers don't even bother acquiring an email account in the first place—a recent study showed that more than 76 percent of spam is from nonexistent accounts—deactivation of a spammer's account is of little consequence. Maintaining a list of all these one-time use accounts causes exhaustive and excessive blacklist checking by the server—particularly considering that most spammer addresses are only used once. Thus, with blacklists, you're always one step behind the spammer, so a subscription to a blacklisting company is required to make this method an effective spamfighting tool.
MX record or a reverse DNS record lookup performs a DNS query on the sender's domain. If the sender's domain matches the MX record IP address of the server, the mail is accepted. If the IP address does not match, the message is rejected.
This approach can work well if a sender's domain name has been spoofed by a spammer. In such a case, the server would know that the message is not coming from the legitimate contact.
This approach has the potential to create many false positives. The following scenarios can cause a false positive:
For these reasons, I suggest using other methods for spam blocking.
Heuristics and Bayesian filtering is one of the more recent methods developed to block spam. The software gathers statistics about the type of message received, then makes a judgment call about whether the message is spam. To make this determination, some software packages use a point scoring system and others use custom algorithms. This method can be a very effective weapon against spam.
Heuristics and Bayesian filtering works like a blackjack player who is counting cards. A card counter knows that the deck is in his or her favor when a series of low cards appears because this means that the deck is "ten rich," increasing the probability that the dealer will bust if the dealer must draw a card. Heuristics and Bayesian filtering similarly looks at words in email messages that are already marked as spam, then compares how often key words appear in an incoming email to estimate the probability that the message is spam. Generally, more recent data is more heavily weighted and email keywords are continually updated with new and current information. This system gives heuristics and Bayesian filtering the advantage of becoming somewhat selfmaintaining.
If you're considering an heuristics and Bayesian filtering solution, consider a filter that looks at outgoing email to reduce the amount of false positives. For example, if you work for a refinance company and the word mortgage appears quite frequently in your outgoing emails, you want to ensure that messages that contain mortgage aren't blocked. In this particular case, the word mortgage will not have such a heavy weight for incoming mail because it occurs quite frequently in the company's outgoing mail. This analysis of outgoing email will reduce the amount of false positives.
Because heuristics and Bayesian filtering typically takes the whole message into account, it can usually catch misspelled words such as s*e*x or v-i-a-g-r-a. In fact, these misspelled words almost guarantee that the message is spam because a legitimate email will most likely never spell words in this manner.
The biggest selling point for heuristics and Bayesian filtering is that this solution is very low maintenance. Heuristics and Bayesian filtering constantly gathers information about incoming mail and updates statistics on an ongoing basis. Because it typically only looks at mail sent and received by the company, the statistics are custom-tailored for the company's email. Usually these statistics are more heavily weighted on the most recent data. Some companies claim they can block out as much as 99 percent of spam with a very low percentage of false positives by using heuristics and Bayesian filtering.
Heuristics and Bayesian filtering is only as good as the engine/algorithm making the spam judgment call. Typically, the entire message is evaluated, which results in an additional load on the email server assuming the heuristics and Bayesian filtering engine is installed on the same machine as the mail server. On a heavily loaded server, this spam-blocking method can cause performance issues.
In addition, after the heuristics and Bayesian filtering analysis, each message is typically assigned a probability ranging from 0 to 100 percent that the message is spam. This probability must be fine-tuned over time. Set the threshold too high, and too much spam gets through. Set the threshold too low, and you generate many false positives. Refer to the software documentation for a recommended initial setting, then fine-tune this setting based on your company's requirements. Because every company's email is different, you must use trial and error to determine the best setting for your company. Also, because heuristics and Bayesian filtering has the potential for generating false positives, look for a package that also supports a whitelist or some other method of receiving a legitimate message that was incorrectly marked as spam.
At a basic level, sender validation works by letting mail through if the sender is on an approved list and rejecting the mail if the sender is not on the list. Think of sender validation as an "intelligent whitelist." Once a sender is placed on the approved list, the mail server will accept mail from this address. The concept is simple, but it is the management of the approved list and a smooth validation process that are keys to a successful sender validation anti-spam solution.
Most corporate sender validation packages work like the flowchart that Figure 1.2 shows.
Figure 1.2: A flowchart that illustrates the sender validation process.
If you're considering a sender validation solution, look for the following features to ensure a successful implementation:
Load balancing/fault tolerance—Very large companies and those for which email is a mission-critical application should look for a package that supports load balancing and/or fault tolerance/failover between multiple servers. Even without this feature, make sure that it is easy to bypass the sender validation filtering server (typically an IP address change on the firewall) in case of a complete hardware failure on the server.
Fault tolerance is a concern with any anti-spam solution. Using a secondary MX record to the ISP's backup-relay server is an excellent solution for fault tolerance.
Vendors such as SpamLion and MailFrontier provide sender validation packages that offer all these necessary features.
Historically, desktop/POP3 versions of sender validation have had the most success in the spam world. They are the easiest to implement and evaluate for the individual user; however, they are generally impractical within a business environment. The advantage of such solutions is that, compared with an internal enterprise solution, the software development cycle for a desktop sender validation solution is relatively short. It is fairly easy to evaluate and install because the sender validation server and software are usually located off-site.
However, some sender validation POP3 solutions are not online all the time, which can cause mail delivery problems. Depending on the solution, the validation process can be cumbersome and take a long time (days) to complete. It is possible to encounter a deadlock situation when both the sender and receiver have a sender validation spam protection for their mail. Sometimes the sender validation solution will not send an NDR to a legitimate sender, so the sender assumes their mail was delivered, but it wasn't. Make sure you can manually add senders to the approved list to avoid a deadlock situation. Some of the earlier attempts at sender validation were built by amateurs and lack the stability and features of a proper corporate sender validation solution.
Early sender validation enterprise solutions (circa 1995) lacked the stability and functionality that corporate users required. The advantage of such solutions is that the sender validation server is internal, so it is always online. However, many of the early attempts at sender validation were immature products, which resulted in a bad reputation for sender validation. These immature products were costly to evaluate because they typically required a dedicated internal server and complete implementation of the package just to evaluate it (a significant investment in both hardware and time for IT staff to purchase, install, configure, and sometimes develop the software for the sender validation server). With some early sender validation solutions, it was possible to encounter a deadlock situation between companies. Like the POP3 solution, you sometimes had the problem of lost NDRs, so a legitimate sender assumed you received their message when you actually had not. Some of the earlier sender validation solutions were developed in-house by internal IT departments or individuals, which had mixed success rates. Some of these sender validation systems have matured and evolved into today's systems.
There are quite a few advantages of sender validation, especially when compared with other spam-filtering methods:
To truly benefit from sender validation, you need to be aware of the disadvantages of this spamblocking method:
The spam problem becomes more of an issue everyday—spam exists because spammers make money doing it. The cost per piece of spam is dramatically lower than a traditional direct mail campaign. However, as we explored in this chapter, there are many spam-blocking methods available and being developed to combat this growing problem.
Each of these spam-fighting strategies has advantages and disadvantages. Often a combination of these strategies can provide a satisfactory solution for blocking spam. Among all of these methods, only one can potentially eliminate 100 percent of spam—sender validation. Although sender validation got a bad rap in the 1990s as a result of homegrown systems that lacked features and functionality and had poorly designed user interfaces, the current crop of sender validation solutions are ready for the corporate environment and have been fully tested and refined.
Spam robs a tremendous amount of time and resources from end users, IT staff, mail servers, WAN links, and storage requirements. The good news is that almost any solution will save your company money. Obviously, you want the best solution, and sender validation is a good fit for most companies. Once you've decided that sender validation is the right technology for your company, you must evaluate the advantages and disadvantages of each sender validation package. In the next chapter, we'll take a look at finding the right sender validation package for your company as well as how to evaluate the package you choose to ensure that it is the best solution for your environment.