Episode 4: Security Investigation Series – Tackling SPAM Attacks


One of the age-old attacks seen in the Internet is a SPAM attack. Many organizations have been blacklisted for having been a SPAM relay or a SPAM Source. Even though technologies have improved vastly over the decade, SPAM is still real and users are still being enticed by SPAM. The result is Machine Compromise and potential data breach. As of 2011, more than 7 Trillion SPAM Messages have originated. Many organizations combat SPAM in many different ways. In this Security Investigation Series Episode, I am going to layout a workflow for SPAM detection, Cleanup and Prevention.

Understanding SPAM: Firstly, let us understand SPAM. SPAM is nothing but a mass of unsolicited messages being sent anonymously or using fake identities. This often is a pre-cursor of an attack and hence is one of the Attack Vectors.  Two major sources of SPAM in an enterprise are

  • Email based SPAM and
  • Instant Messaging SPAM

Let us break this down even further. Email based SPAM uses SMTP protocol as its transport whereas the Instant Messaging using a gamut of protocols from HTTP, SIP, IMPP to XMPP. Several tools and technologies for SPAM detection and filtering work at this protocol level and identify SPAM and filter them as needed. Still intelligent spammers, can circumvent the detection and make their way to the user mailbox. In such cases, a clear incident detection and response process is needed.

Let us take one sample scenario so that I can layout the process flow for similar scenarios.

A Real Life Scenario: A mail is received at the user’s inbox containing a Password Stealer link. This is suspected as SPAM by the Security Devices in your enterprise. The security devices can be anyone or combination of Intrusion Detection Systems, Gateway Filters, SPAM filters etc. These alerts are logged to a SIEM solution. SIEM Solutions then correlate the various messages received and trigger an Incident. If there are no Security devices that do this, SIEM can help you identify SPAM through Network Traffic monitoring.

Logic for good SPAM detection: In signature based detection, it is good enough to just pick on the Triggers from the individual product vendors and then correlate among them. But if there is a SPAM message that is fresh and does not have a signature pattern, then only behavior based detection will be effective. Several tools today do some behavior based detection. Enterprises who don’t have behavior based systems can look at making use of SIEM to be that system. SIEM is a powerful tool and can do trending, correlation and pattern matching. A simple rule can be written for network log correlation for protocols like SMTP/IMP etc. Typically a value of 25 SPAM messages going to different destinations within a minute is a good indication of SPAM. This value combinations can be throttled (Throttling is a great SIEM topic and one of the classic rule writing as well as throttling ArcSight example can be found here at wymanstocks.com) to get a more accurate SPAM detection rate. This detection is crucial for the response to be triggered.

Responding to SPAM Attacks: Once the SPAM detection is done through signature or behavior based logs, it is important to take a series of responsive actions.

  • Before responding obviously validation needs to be done to ensure we don’t falsely respond to a legitimate email. This is typically done at the SIEM level itself and is the job of a Level 1 Analyst.
  • Then, We need to ensure that the SPAM domain is blocked at the gateway level. This is to ensure that the SPAM does not spread from Internal to External. Some SPAM mails have carefully constructed callback to the domain itself and hence it is important to block it at the gateway.
  • Secondly, we need to ensure that the SPAM spreading is controlled in the Internal Mail Infrastructure. This can be done by putting filtering rules in Exchange to move SPAM messages to the deleted items folder. Similarly for IM also, such rules can be put in the messaging server.
  • Finally, the SPAM has to be cleaned from the individual machines. This is where it gets interesting.
  • There are three major types of users:
    1. Many users are aware of the SPAM and hence they would not have clicked on any of the links available in the mail or the message. These user machines can be remediated by just deleting the SPAM messages.
    2. Some users who are curious would have clicked on the link and then closed it after seeing its suspicious face. Majority of these cases are nothing and get remediated by just deleting the SPAM message. Some targeted SPAM attacks work to just make the user click on the SPAM link and then get re-directed to a Malware Dropper site. In these cases, even though the SPAM mail has been deleted the users are at risk. Hence these user machine have to be validated as well for possible compromise.
    3. Time and again we also see users clicking on the link, keying in all their data to the site and then feeling that nothing wrong has happened to them. These user machines are no longer clean and have to be re-imaged straight away.
  • Once the remediation is done, the appropriate documentation need to be carried out. Again as I said, documentation is vital in a Security Investigation process. Without documentation, it will not be repeatable, it will not be efficient.

Preventing SPAM Attacks: Preventing SPAM is the ultimate goal for every enterprise. Day in and Day out, Enterprise Defenses are being improved to combat SPAM. However, SPAM is mostly an initialization vector and hence it is at the hands of the End-User to be aware of the risks involved with SPAM. So more than the tools and technologies I would say “User Training” is the best way to prevent SPAM. What do you think?

How do you combat SPAM in your enterprise? Sound off in the comments below

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