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|It has been suggested that Anti-spam techniques (users) be merged into this article. (Discuss) Proposed since October 2012.|
To prevent email spam (a.k.a. unsolicited bulk email), both end users and administrators of email systems use various anti-spam techniques. Some of these techniques may be embedded in products, services and software to ease the burden on users and administrators. No technique is a complete solution to the spam problem, and each has trade-offs between incorrectly rejecting legitimate email vs. not rejecting all spam, and the associated costs in time and effort.
Anti-spam techniques can be broken into four broad categories: those that require actions by individuals, those that can be automated by email administrators, those that can be automated by email senders and those employed by researchers and law enforcement officials.
People tend to be much less bothered by spam slipping through filters into their mail box (false negatives), than having desired email ("ham") blocked (false positives). Trying to balance false negatives (missed spams) vs false positives (rejecting good email) is critical for a successful anti-spam system. Some systems let individual users have some control over this balance by setting "spam score" limits, etc. Most techniques have both kinds of serious errors, to varying degrees. So, for example, anti-spam systems may use techniques that have a high false negative rate (miss a lot of spam), in order to reduce the number of false positives (rejecting good email).
Detecting spam based on the content of the email, either by detecting keywords such as "viagra" or by statistical means (content or non-content based), is very popular. Content based statistical means or detecting keywords can be very accurate when they are correctly tuned to the types of legitimate email that an individual gets, but they can also make mistakes such as detecting the keyword "cialis" in the word "specialist" (see also Internet censorship: Over- and under-blocking). Spam originators frequently seek to defeat such measures by employing typographical techniques such as replacing letters with accented variants or alternative characters which appear identical to the intended characters but are internally distinct (e.g., replacing a Roman 'A' with a Cyrillic 'A'), or inserting other characters such as whitespace, nonprinting characters, or bullets into a term to block pattern matching. This introduces an arms race which demands increasingly complex keyword-detection methods.
The content also doesn't determine whether the email was either unsolicited or bulk, the two key features of spam. So, if a friend sends you a joke that mentions "viagra", content filters can easily mark it as being spam even though it is neither unsolicited nor sent in bulk. Non-content base statistical means can help lower false positives because it looks at statistical means vs. blocking based on content/keywords. Therefore, you will be able to receive a joke that mentions "viagra" from a friend.
The most popular DNSBLs (DNS Blacklists) are lists of domain names of known spammers, known open relays, known proxy servers, compromised “zombie” spammers, as well as hosts on the internet that shouldn’t be sending external emails, such as the end-user address space of a consumer ISP. These are known as “Dial Up Lists”, from the time when end users whose computers were "zombieing" spam were connected to the internet with a modem and a phone line.
Spamtraps are often email addresses that were never valid or have been invalid for a long time that are used to collect spam. An effective spamtrap is not announced and is only found by dictionary attacks or by pulling addresses off hidden webpages. For a spamtrap to remain effective the address must never be given to anyone. Some black lists, such as spamcop, use spamtraps to catch spammers and blacklist them.
Enforcing technical requirements of the Simple Mail Transfer Protocol (SMTP) can be used to block mail coming from systems that are not compliant with the RFC standards. A lot of spammers use poorly written software or are unable to comply with the standards because they do not have legitimate control of the computer sending spam (zombie computer). So by setting restrictions on the mail transfer agent (MTA) a mail administrator can reduce spam significantly, such as by enforcing the correct fall back of Mail eXchange (MX) records in the Domain Name System, or the correct handling of delays (Teergrube).
There are a number of techniques that individuals can use to restrict the availability of their email addresses, reducing or preventing their attractiveness to spam.
Sharing an email address only among a limited group of correspondents is one way to limit spam. This method relies on the discretion of all members of the group, as disclosing email addresses outside the group circumvents the trust relationship of the group. For this reason, forwarding messages to recipients who don't know one another should be avoided. When it is absolutely necessary to forward messages to recipients who don't know one another, it is good practice to list the recipient names all after "bcc:" instead of after "to:". This practice avoids the scenario where unscrupulous recipients might compile a list of email addresses for spamming purposes. This practice also reduces the risk of the address being distributed by computers affected with email address harvesting malware. However, once the privacy of the email address is lost by divulgence, it cannot be regained.
Posting anonymously, or with a fake name and address, is one way to avoid email address harvesting, but users should ensure that the fake address is not valid. Users who want to receive legitimate email regarding their posts or Web sites can alter their addresses so humans can figure out but spammers cannot. For instance, firstname.lastname@example.org might post as joeNOS@PAM.invalid.example.com. Address munging, however, can cause legitimate replies to be lost. If it's not the user's valid address, it has to be truly invalid, otherwise someone or some server will still get the spam for it. Other ways use transparent address munging to avoid this by allowing users to see the actual address but obfuscate it from automated email harvesters with methods such as displaying all or part of the email address on a web page as an image, a text logo shrunken to normal size using in-line CSS, or as jumbled text with the order of characters restored using CSS.
Spammers often regard responses to their messages—even responses like "Don't spam me"—as confirmation that an email address is valid. Likewise, many spam messages contain Web links or addresses which the user is directed to follow to be removed from the spammer's mailing list. In several cases, spam-fighters have tested these links, confirming they do not lead to the recipient address's removal—if anything, they lead to more spam. This removal request of filing a complaint may get the address list washed. To lower complaints so the spammer can stay active before having to acquire new accounts and/or internet provider.
Sender addresses are often forged in spam messages, including using the recipient's own address as the forged sender address, so that responding to spam may result in failed deliveries or may reach innocent email users whose addresses have been abused.
In Usenet, it is widely considered even more important to avoid responding to spam. Many ISPs have software that seek and destroy duplicate messages. Someone may see a spam and respond to it before it is cancelled by their server, which can have the effect of reposting the spam for them; since it is not a duplicate, the reposted copy will last longer. Replying may also cause the poster to be falsely linked to as part of the spam message.
Contact forms allow users to send email by filling out forms in a web browser. The web server takes the form data, forwarding it to an email address. Users never see the email address. Such forms, however, are sometimes inconvenient to users, as they are not able to use their preferred email client, risk entering a faulty reply address, and are typically not notified about delivery problems. Further, contact forms have the drawback that they require a website that supports server side scripts. Finally, if the software used to run the contact forms is badly designed, it can become a spam tool in its own right. Additionally, some spammers have begun to send spam using the contact form.
Mail clients which do not automatically download and display HTML, images or attachments, have fewer risks, as do clients who have been configured to not display these by default.
An email user may sometimes need to give an address to a site without complete assurance that the site owner will not use it for sending spam. One way to mitigate the risk is to provide a disposable email address—a temporary address which the user can disable or abandon which forwards email to a real account. A number of services provide disposable address forwarding. Addresses can be manually disabled, can expire after a given time interval, or can expire after a certain number of messages have been forwarded. Disposable email addresses can be used by users to track whether a site owner has disclosed an address. This capability has resulted in legal jeopardy for sites that disclose confidential addresses without permission.
Systems that use ham passwords ask unrecognised senders to include in their email a password that demonstrates that the email message is a "ham" (not spam) message. Typically the email address and ham password would be described on a web page, and the ham password would be included in the "subject" line of an email message. Ham passwords are often combined with filtering systems, to counter the risk that a filtering system will accidentally identify a ham message as a spam message.
The "plus addressing" technique appends a password to the "username" part of the email address.
|This section does not cite any references or sources. (October 2012)|
Tracking down a spammer's ISP and reporting the offense can lead to the spammer's service being terminated. Unfortunately, it can be difficult to track down the spammer—and while there are some online tools to assist, they are not always accurate. Occasionally, spammers employ their own netblocks. In this case, the abuse contact for the netblock can be the spammer itself and can confirm your address.
Examples of these online tools are SpamCop and Network Abuse Clearinghouse. They provide automated or semi-automated means to report spam to ISPs. Some spam-fighters regard them as inaccurate compared to what an expert in the email system can do; however, most email users are not experts.
A free tool called Complainterator may be used in the reporting of spam. The Complainterator will send an automatically generated complaint to the registrar of the spamming domain and the registrar of its name servers.
Historically, reporting spam in this way has not seriously abated spam, since the spammers simply move their operation to another URL, ISP or network of IP addresses.
Consumers may also forward "unwanted or deceptive spam" to an email address (email@example.com) maintained by the FTC. The database collected is used to prosecute perpetrators of scam or deceptive advertising.
An alternative to contacting ISPs is to contact the registrar of a domain name that has been used in spam email. Registrars, as ICANN-accredited administrative organizations, are obliged to uphold certain rules and regulations, and have the resources necessary for dealing with abuse complaints.
|This section's tone or style may not reflect the encyclopedic tone used on Wikipedia. (March 2009)|
Some advocate responding aggressively to spam—in other words, "spamming the spammer".
The basic idea is to make spamming less attractive to the spammer, by increasing the spammer's overhead. There are several ways to reach a spammer, but besides the caveats mentioned above, it may lead to retaliations by the spammer.
There are a number of appliances, services, and software systems that email administrators can use to reduce the load of spam on their systems and mailboxes. Some of these depend upon rejecting email from Internet sites known or likely to send spam. Other more advanced techniques analyze message patterns in real time to detect spam like behavior and then compare it to global databases of spam. Those methods are capable of detecting spam in real time even when there is no content (common to image based spam) and in any language. Another method relies on automatically analyzing the content of email messages and weeding out those which resemble spam. These three approaches are sometimes termed blocking, pattern detection, and filtering.
There is an increasing trend of integration of anti-spam techniques into MTAs whereby the mail systems themselves also perform various measures that are generally referred to as filtering, ultimately resulting in spam messages being rejected before delivery (or blocked).
Many filtering systems take advantage of machine learning techniques, which improve their accuracy over manual methods. However, some people find filtering intrusive to privacy, and many email administrators prefer blocking to deny access to their systems from sites tolerant of spammers.
A number of systems have been proposed to allow acceptance of email from servers which have authenticated in some fashion as senders of only legitimate email. Many of these systems use the DNS, as do DNSBLs; but rather than being used to list nonconformant sites, the DNS is used to list sites authorized to send email, and (sometimes) to determine the reputation of those sites. Other methods of identifying ham (non-spam email) and spam are still used.
Authentication systems cannot detect whether a message is spam. Rather, they allow a site to express trust that an authenticated site will not send spam. Thus, a recipient site may choose to skip expensive spam-filtering methods for messages from authenticated sites.
Another method which may be used by internet service providers, by specialized services or enterprises to combat spam is to require unknown senders to pass various tests before their messages are delivered. These strategies are termed challenge/response systems or C/R. Some view their use as being as bad as spam since they place the burden of spam fighting on legitimate email senders—who it should be noted will often indeed give up at the slightest hindrance. A new implementation of this is done in Channel email.
Checksum-based filter exploits the fact that the messages are sent in bulk, that is that they will be identical with small variations. Checksum-based filters strip out everything that might vary between messages, reduce what remains to a checksum, and look that checksum up in a database which collects the checksums of messages that email recipients consider to be spam (some people have a button on their email client which they can click to nominate a message as being spam); if the checksum is in the database, the message is likely to be spam.
The advantage of this type of filtering is that it lets ordinary users help identify spam, and not just administrators, thus vastly increasing the pool of spam fighters. The disadvantage is that spammers can insert unique invisible gibberish—known as hashbusters—into the middle of each of their messages, thus making each message unique and having a different checksum. This leads to an arms race between the developers of the checksum software and the developers of the spam-generating software.
Checksum based filtering methods include:
Some email servers expect to never communicate with particular countries from which they receive a great deal of spam. Therefore, they use country-based filtering - a technique that blocks email from certain countries. This technique is based on country of origin determined by the sender's IP address rather than any trait of the sender.
DNS-based Blacklists, or DNSBLs, are used for heuristic filtering and blocking. A site publishes lists (typically of IP addresses) via the DNS, in such a way that mail servers can easily be set to reject mail from those sources. There are literally scores of DNSBLs, each of which reflects different policies: some list sites known to emit spam; others list open mail relays or proxies; others list ISPs known to support spam.
Other DNS-based anti-spam systems list known good ("white") or bad ("black") IPs domains or URLs, including RHSBLs and URIBLs.
Analysis of an email's conformation to RFC standards for the Simple Mail Transfer Protocol (SMTP) can be used to judge the likelihood of the message being spam. A lot of spammers use poorly written software or are unable to comply with the standards because they do not have legitimate control of the computer they are using to send spam (zombie computer). By setting limits on the deviation from RFC standards that the MTA will accept, a mail administrator can reduce spam significantly.
A greeting delay is a deliberate pause introduced by an SMTP server before it sends the SMTP greeting banner to the client. The client is required to wait until it has received this banner before it sends any data to the server. (per RFC 5321 3.2). Many spam-sending applications do not wait to receive this banner, and instead start sending data as soon as the TCP connection is established. The server can detect this, and drop the connection.
There are some legitimate sites[clarification needed] that play "fast and loose" with the SMTP specifications, and may be caught by this mechanism. It also has a tendency to interact badly with sites that perform callback verification, as common callback verification systems have timeouts that are much shorter than those mandated by RFC 5321 22.214.171.124.
The SMTP protocol allows for temporary rejection of incoming messages. Greylisting is the technique to temporarily reject messages from unknown sender mail servers. A temporary rejection is designated with a 4xx error code that is recognized by all normal MTAs, which then proceed to retry delivery later.
Greylisting is based on the premise that spammers and spambots will not retry their messages but instead will move on to the next message and next address in their list. Since a retry attempt means the message and state of the process must be stored, it inherently increases the cost incurred by the spammer. The assumption is that, for the spammer, it's a better use of resources to try a new address than waste time re-sending to an address that's already exhibited a problem. For a legitimate message this delay is not an issue since retrying is a standard component of any legitimate sender's server.
The downside of greylisting is that all legitimate messages from first-time senders will experience a delay in delivery, with the delay period before a new message is accepted from an unknown sender usually being configurable in the software. There also exists the possibility that some legitimate messages won't be delivered, which can happen if a poorly configured (but legitimate) mail server interprets the temporary rejection as a permanent rejection and sends a bounce message to the original sender, instead of trying to resend the message later, as it should.
For example, some spamware can be detected by a number of simple checks confirming compliance with standard addressing and MTA operation. RFC 5321 section 4.1.4 says that "An SMTP server MAY verify that the domain name argument in the EHLO command actually corresponds to the IP address of the client. However, if the verification fails, the server MUST NOT refuse to accept a message on that basis.", so to be in compliance with the RFCs, rejecting connections must be based on additional information/policies.
Invalid HELO localhost Invalid HELO 127.0.0.1 Valid HELO domain.tld Valid HELO [127.0.0.1]
Fraudulent HELO friend Fraudulent HELO -232975332
The SMTP protocol can allow several SMTP commands to be placed in one network packet and "pipelined". For example, if an email is sent with a CC: header, several SMTP "RCPT TO" commands might be placed in a single packet instead of one packet per "RCPT TO" command. The SMTP protocol, however, requires that errors be checked and everything is synchronized at certain points. Many spammers will send everything in a single packet since they do not care about errors and it is more efficient. Some MTAs will detect this invalid pipelining and reject email sent this way.
The SMTP protocol requires that email servers for any given domain be provided in a prioritized list (namely, MX records), and further specifies mandatory error-handling behavior when servers in that list cannot be contacted. Nolisting is a technique of purposely creating unreachable MX records, so that only senders who have implemented this error-handling behavior can successfully deliver mail.
The SMTP protocol requires connections to be closed with a QUIT command. (RFC 5321 section 4.1.4) Many spammers skip this step because their spam has already been sent and taking the time to properly close the connection takes time and bandwidth. Some MTAs like Exim are capable of detecting whether or not the connection is closed with the quit command and can track patterns of use for the purpose of building DNSBLs.
Another approach is simply an imitation MTA which gives the appearance of being an open mail relay, or an imitation TCP/IP proxy server which gives the appearance of being an open proxy. Spammers who probe systems for open relays/proxies will find such a host and attempt to send mail through it, wasting their time and resources and potentially revealing information about themselves and the origin of the spam they're sending to the entity that operates the honeypot. Such a system may simply discard the spam attempts, submit them to DNSBLs, or store them for analysis.
Hybrid filtering, such as is implemented in the open source programs SpamAssassin and Policyd-weight uses some or all of the various tests for spam, and assigns a numerical score to each test. Each message is scanned for these patterns, and the applicable scores tallied up. If the total is above a fixed value, the message is rejected or flagged as spam. By ensuring that no single spam test by itself can flag a message as spam, the false positive rate can be greatly reduced.
Several appliances such as the Barracuda Networks Spam firewall, and services like Postini and Cudamail employ spam scoring and bayesian filtering to arrive at thresholds which determine filtering action. An example of defaults might be:
3 - Tag the email (add a "tagged" or "suspected spam" type of string to the email subject line to assist end users in checking their inbox.
4.5 - Quarantine the email (hold it, and email the end user to let them know that it quite possibly is spam and as a result they must log in and see it. Typically this type of action is taken due to more "spammy" features in the email such as hyperlinks, more image content than text, or certain words.
6 - Block the email (do not allow it through. Typically this action is taken due to presence in the email of words like viagra, or links to malware sites, or to urls that are known to be used by spammers, or to have been blacklisted by a variety of online blacklist services like Barracuda Central or SpamHaus.
Outbound spam protection involves scanning email traffic as it exits a network, identifying spam messages and then taking an action such as blocking the message or shutting off the source of the traffic. Outbound spam protection can be implemented on a network-wide level (using policy-based routing or similar techniques to route SMTP messages to a filtering service). Or, it can be implemented within a standard SMTP gateway. While the primary economic impact of spam is on spam recipients, sending networks also experience financial costs, such as wasted bandwidth, and the risk of having IP addresses blocked by receiving networks.
The advantage of outbound spam protection is that it stops spam before it leaves the sending network, protecting receiving networks globally from the damage and costs that would otherwise be caused by the spam. Further it lets system administrators track down spam sources on the network and remediate them – for example, providing free anti-virus tools to customers whose machines have become infected with a virus or are participating in a botnet. Given an appropriately designed spam filtering algorithm, outbound spam filtering can be implemented with a near zero false positive rate, which keeps customer related issues with blocked legitimate email down to a minimum.
When dealing with outbound spam, it's important to not only analyze the content of individual messages, but also to keep track of the behaviour of email senders over time. Senders exhibiting suspicious behaviour should be rate limited to reduce the likelihood that they will send spam, which may get past even a good filter.
There are several commercial software vendors who offer specialized outbound spam protection products, including MailChannels and Commtouch. Open source options such as SpamAssassin may also be effective.
Pattern detection, is an approach to stop spam in real time before it gets to the end user. This technology monitors a large database of messages worldwide to detect spam patterns. Many spam messages have no content or may contain attachments which this method of detection can catch. Pioneered by Commtouch, a developer of anti-spam software, their Recurrent Pattern Detection (RPD) software can be integrated into other appliances and applications. This method is more automated than most because the service provider maintains the comparative spam database instead of the system administrator.
The PTR DNS records in the reverse DNS can be used for a number of things, including:
Content filtering techniques rely on the specification of lists of words or regular expressions disallowed in mail messages. Thus, if a site receives spam advertising "herbal Viagra", the administrator might place this phrase in the filter configuration. The mail server would then reject any message containing the phrase.
Header filtering is the means of inspecting the header of the email, the part of the message that contains information about the origin, destination and content of the message. Spammers will often spoof fields in the header in order to hide their identity, or to try to make the email look more legitimate than it is; many of these spoofing methods can be detected. Also, a violation of the RFC 5322 standard on how the header is to be formed can serve as a basis for rejecting the message.
Disadvantages of filtering are threefold: First, filtering can be time-consuming to maintain. Second, it is prone to false positives. Third, these false positives are not equally distributed: since content filtering is prone to reject legitimate messages on topics related to products frequently advertised in spam. A system administrator who attempts to reject spam messages which advertise mortgage refinancing, credit or debt may inadvertently block legitimate email on the same subject.
Spammers frequently change the phrases and spellings they use. This can mean more work for the administrator. However, it also has some advantages for the spam fighter. If the spammer starts spelling "Viagra" as "V1agra" (see leet) or "Via_gra", it makes it harder for the spammer's intended audience to read their messages. If they try to trip up the phrase detector, by, for example, inserting an invisible-to-the-user HTML comment in the middle of a word ("Via<!---->gra"), this sleight of hand is itself easily detectable, and is a good indication that the message is spam. And if they send spam that consists entirely of images, so that anti-spam software can't analyze the words and phrases in the message, the fact that there is no readable text in the body can be detected, making that message a higher risk of being spam.
Content filtering can also be implemented to examine the URLs present (i.e. spamvertising) in an email message. This form of content filtering is much harder to disguise as the URLs must resolve to a valid domain name. Extracting a list of such links and comparing them to published sources of spamvertised domains is a simple and reliable way to eliminate a large percentage of spam via content analysis.
Recently a spam campaign has started using a table layout consisting of three horizontal cells. Text is inserted into each cell, so that when viewed in the email, words like Viagra, Cialis etc. are visible, but the whole words don't actually exist in the html. Like this (imagine a properly built html table with invisible lines):
AL | IS |
AG | RA |
Several spam filtering services and appliances are working on this new campaign, as spammers continue to evolve their methods of bypassing filters.
There are a few organizations which offer IP whitelisting and/or licensed tags that can be placed in email (for a fee) to assure recipients' systems that the messages thus tagged are not spam. This system relies on legal enforcement of the tag. The intent is for email administrators to whitelist messages bearing the licensed tag.
A potential difficulty with such systems is that the licensing organization makes its money by licensing more senders to use the tag—not by strictly enforcing the rules upon licensees. A concern exists that senders whose messages are more likely to be considered spam would accrue a greater benefit by using such a tag. The concern is that these factors form a perverse incentive for licensing organizations to be lenient with licensees who have offended. However, the value of a license would drop if it was not strictly enforced, and financial gains due to enforcement of a license itself can provide an additional incentive for strict enforcement.
Since a large percentage of spam has forged and invalid sender ("from") addresses, some spam can be detected by checking that this "from" address is valid. A mail server can try to verify the sender address by making an SMTP connection back to the mail exchanger for the address, as if it was creating a bounce, but stopping just before any email is sent.
Callback verification can be compliant with SMTP RFCs, but it has various drawbacks. Since nearly all spam has forged return addresses, nearly all callbacks are to innocent third party mail servers that are unrelated to the spam. At the same time, there will be numerous false negatives due to spammers abusing real addresses and some false positives. One of the ways of reducing the load on innocent servers is to use other spam detection methods first and save callback verification for last.
SMTP proxies allow combating spam in real time, combining sender's behavior controls, providing legitimate users immediate feedback, eliminating a need for quarantine.
Spamtrapping is the seeding of an email address so that spammers can find it, but normal users can not. If the email address is used then the sender must be a spammer and they are black listed.
As an example, consider the email address "firstname.lastname@example.org". If this email address were placed in the source HTML of our web site in a way that it isn't displayed on the web page, normal humans would not see it. Spammers, on the other hand, use web page scrapers and bots to harvest email addresses from HTML source code so they would find this address.
When the spammer sends mail with the destination address of "email@example.com" the SpamTrap knows this is highly likely to be a spammer and can take appropriate action.
Statistical (or Bayesian) filtering once set up, requires no administrative maintenance per se: instead, users mark messages as spam or nonspam and the filtering software learns from these judgements. Thus, a statistical filter does not reflect the software author's or administrator's biases as to content, but rather the user's biases. For example, a biochemist who is researching Viagra won't have messages containing the word "Viagra" automatically flagged as spam, because "Viagra" will show up often in his or her legitimate messages. Still, spam emails containing the word "Viagra" do get filtered because the content of the rest of the spam messages differs significantly from the content of legitimate messages. A statistical filter can also respond quickly to changes in spam content, without administrative intervention, as long as users consistently designate false negative messages as spam when received in their email. Statistical filters can also look at message headers, thereby considering not just the content but also peculiarities of the transport mechanism of the email.
Typical statistical filtering uses single words in the calculations to decide if a message should be classified as spam or not. A more powerful calculation can be made using groups of two or more words taken together. Then random "noise" words can not be used as successfully to fool the filter.
Software programs that implement statistical filtering include Bogofilter, DSPAM, SpamBayes, ASSP, the email programs Mozilla and Mozilla Thunderbird, Mailwasher, and later revisions of SpamAssassin. Another interesting project is CRM114 which hashes phrases and does bayesian classification on the phrases.
There is also the free mail filter POPFile, which sorts mail in as many categories as the user wants (family, friends, co-worker, spam, whatever) with Bayesian filtering.
A tarpit is any server software which intentionally responds extremely slowly to client commands. By running a tarpit which treats acceptable mail normally and known spam slowly or which appears to be an open mail relay, a site can slow down the rate at which spammers can inject messages into the mail facility. Many systems will simply disconnect if the server doesn't respond quickly, which will eliminate the spam. However, a few legitimate email systems will also not deal correctly with these delays.
There are a variety of techniques that email senders use to try to make sure that they do not send spam. Failure to control the amount of spam sent, as judged by email receivers, can often cause even legitimate email to be blocked and for the sender to be put on DNSBLs.
Since spammer's accounts are frequently disabled due to violations of abuse policies, they are constantly trying to create new accounts. Due to the damage done to an ISP's reputation when it is the source of spam, many ISPs and web email providers use CAPTCHAs on new accounts to verify that it is a real human registering the account, and not an automated spamming system. They can also verify that credit cards are not stolen before accepting new customers, check the Spamhaus Project ROKSO list, and do other background checks.
One difficulty in implementing opt-in mailing lists is that many means of gathering user email addresses remain susceptible to forgery. For instance, if a company puts up a Web form to allow users to subscribe to a mailing list about its products, a malicious person can enter other people's email addresses — to harass them, or to make the company appear to be spamming. (To most anti-spammers, if the company sends email to these forgery victims, it is spamming, albeit inadvertently.)
To prevent this abuse, MAPS and other anti-spam organizations encourage that all mailing lists use confirmed opt-in (also known as verified opt-in or double opt-in). That is, whenever an email address is presented for subscription to the list, the list software should send a confirmation message to that address. The confirmation message contains no advertising content, so it is not construed to be spam itself — and the address is not added to the live mail list unless the recipient responds to the confirmation message. See also the Spamhaus Mailing Lists vs. Spam Lists page.
Email senders can do the same type of anti-spam checks on email coming from their users and customers as can be done for email coming from the rest of the Internet.
Problems with sending challenges to forged email addresses can be greatly reduced by not creating a new message that contains the challenge. Instead, the challenge can be placed in the Bounce message when the receiving mail system gives a rejection-code during the SMTP session. When the receiving mail system rejects an email this way, it is the sending system that actually creates the bounce message. As a result, the bounce message will almost always be sent to the real sender, and it will be in a format and language that the sender will usually recognize.
Firewalls and routers can be programmed to not allow SMTP traffic (TCP port 25) from machines on the network that are not supposed to run Mail Transfer Agents or send email. This practice is somewhat controversial when ISPs block home users, especially if the ISPs do not allow the blocking to be turned off upon request. Email can still be sent from these computers to designated smart hosts via port 25 and to other smart hosts via the email submission port 587.
Network address translation can be used to intercept all port 25 (SMTP) traffic and direct it to a mail server that enforces rate limiting and egress spam filtering. This is commonly done in hotels, but it can cause email privacy problems, as well making it impossible to use STARTTLS and SMTP-AUTH if the port 587 submission port isn't used.
Machines that suddenly start sending lots of email may well have become zombie computers. By limiting the rate that email can be sent around what is typical for the computer in question, legitimate email can still be sent, but large spam runs can be slowed down until manual investigation can be done.
By monitoring spam reports from places such as spamcop, AOL's feedback loop, and Network Abuse Clearinghouse, the domain's abuse@ mailbox, etc., ISPs can often learn of problems before they seriously damage the ISP's reputation and have their mail servers blacklisted.
Both malicious software and human spam senders often use forged FROM addresses when sending spam messages. Control may be enforced on SMTP servers to ensure senders can only use their correct email address in the FROM field of outgoing messages. In an email users database each user has a record with an email address. The SMTP server must check if the email address in the FROM field of an outgoing message is the same address that belongs to the user's credentials, supplied for SMTP authentication. If the FROM field is forged, an SMTP error will be returned to the email client (e.g. "You do not own the email address you are trying to send from").
Most ISPs and webmail providers have either an Acceptable Use Policy (AUP) or a Terms of Service (TOS) agreement that discourages spammers from using their system and allows the spammer to be terminated quickly for violations.
Increasingly, anti-spam efforts have led to co-ordination between law enforcement, researchers, major consumer financial service companies and Internet service providers in monitoring and tracking email spam, identity theft and phishing activities and gathering evidence for criminal cases.
The penalty provisions of the Australian Spam Act 2003 dropped Australia's ranking in the list of spam-relaying countries for email spam from tenth to twenty-eighth.
Legislation that provides mandates that bulk emailers must follow makes compliant spam easier to identify and filter out.
Analysis of sites being spamvertised by a given piece of spam often leads to questionable registrations of Internet domain names. Since registrars are required to maintain trustworthy WHOIS databases, digging into the registration details and complaining at the proper locations often results in site shutdowns. Uncoordinated activity may not be effective, given today's volume of spam and the rate at which criminal organizations register new domains. However, a coordinated effort, implemented with adequate infrastructure, can obtain good results.
Several approaches have been proposed to improve the email system.
Since spamming is facilitated by the fact that large volumes of email are very inexpensive to send, one proposed set of solutions would require that senders pay some cost in order to send email, making it prohibitively expensive for spammers. Anti-spam activist Daniel Balsam attempts to make spamming less profitable by bringing lawsuits against spammers.
There are a number of proposals for sideband protocols that will assist SMTP operation. The Anti-Spam Research Group (ASRG) of the Internet Research Task Force (IRTF) is working on a number of email authentication and other proposals for providing simple source authentication that is flexible, lightweight, and scalable. Recent Internet Engineering Task Force (IETF) activities include MARID (2004) leading to two approved IETF experiments in 2005, and DomainKeys Identified Mail in 2006.
DMARC, which stands for "Domain-based Message Authentication, Reporting & Conformance" standardizes how email receivers perform email authentication using the well-known Sender Policy Framework (SPF) and DKIM mechanisms.
Channel email is a new proposal for sending email that attempts to distribute anti-spam activities by forcing verification (probably using bounce messages so back-scatter doesn't occur) when the first email is sent for new contacts.
Spam is the subject of several research conferences, including: