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Why Sguil Is the Best Option for Network Security Monitoring Data

There are many ways to correlate and integrate data from multiple sources in UNIX, but this chapter explains why Sguil is the best option for Network Security Monitoring data, and how to implement this system.
This chapter is from the book

The bulk of this book offers advice on the tools and techniques used to attack and defend networks. Although many defensive applications have been discussed so far, none of them individually presented more than one or two forms of NSM data. We used Tcpdump to collect traffic in libpcap format and used Ethereal to get a close look at packet headers. To see application data exchanged between parties, we reconstructed full content data with Tcpflow. We used Argus and NetFlow to obtain session data. Dozens more tools showed promise, each with a niche specialty.

The UNIX philosophy is built around the idea of cooperating tools. As quoted by Eric Raymond, Doug McIlroy makes this claim: "This is the UNIX philosophy: Write programs that do one thing and do it well. Write programs to work together. Write programs to handle text streams, because that is a universal interface." [1]

Expanding on the idea of cooperating tools brings us to Sguil, an open source suite for performing NSM. Sguil is a cross-platform application designed "by analysts, for analysts," to integrate alert, session, and full content data streams in a single graphical interface. Access to each sort of data is immediate and interconnected, allowing fast retrieval of pertinent information.

Chapter 9 presented Bro and Prelude as two NIDSs that generate alert data. Sguil currently uses Snort as its alert engine. Because Snort is so well covered in other books, here I concentrate on the mechanics of Sguil. It is important to realize that Sguil is not another interface for Snort alerts, like ACID or other products. Sguil brings Snort's alert data, plus session and full content data, into a single suite. This chapter shows how Sguil provides analysts with incident indicators and a large amount of background data. Sguil relies on alert data from Snort for the initial investigative tip-off but expands the investigative options by providing session and full content information.

Why Sguil?

Other projects correlate and integrate data from multiple sources. The Automated Incident Reporting project (http://aircert.sourceforge.net/) has ties to the popular Snort interface ACID. The Open Source Security Information Management project (http://www.ossim.net/) offers alert correlation, risk assessment, and identification of anomalous activity. The Crusoe Correlated Intrusion Detection System (http://crusoecids.dyndns.org/) collects alerts from honeypots, network IDSs, and firewalls. The Monitoring, Intrusion Detection, [and] Administration System (http://midas-nms.sourceforge.net/) is another option. With so many other tools available, why implement Sguil?

These are projects worthy of attention, but they all converge on a common implementation and worldview. NSM practitioners believe these tools do not present the right information in the best format. First, let's discuss the programmatic means by which nearly all present IDS data. Most modern IDS products display alerts in Web-based interfaces. These include open source tools like ACID as well as commercial tools like Cisco Secure IDS and Sourcefire.

The browser is a powerful interface for many applications, but it is not the best way to present and manipulate information needed to perform dynamic security investigations. Web browsers do not easily display rapidly changing information without using screen refreshes or Java plug-ins. This limitation forces Web-based tools to converge on backward-looking information. [2] Rather than being an investigative tool, the IDS interface becomes an alert management tool.

Consider ACID, the most mature and popular Web-based interface for Snort data. It tends to present numeric information, such as snapshots showing alert counts over the last 24 or 72 hours. Typically the most numerous alerts are given top billing. The fact that an alert appears high in the rankings may have no relationship whatsoever to the severity of the event. An alert that appears a single time but might be more significant could be buried at the bottom of ACID's alert pile simply because it occurred only once. This backward-looking, count-based method of displaying IDS alert data is partially driven by the programmatic limitations of Web-based interfaces.

Now that we've discussed some of the problems with using Web browsers to investigate security events, let's discuss the sort of information typically offered by those tools. Upon selecting an alert of interest in ACID, usually only the payload of the packet that triggered the IDS rule is available. The unlucky analyst must judge the severity and impact of the event based solely on the meager evidence presented by the alert. The analyst may be able to query for other events involving the source or destination IP addresses, but she is restricted to alert-based information. The intruder may have taken dozens or hundreds of other actions that triggered zero IDS rules. Why is this so?

Most IDS products and interfaces aim for "the perfect detection." They put their effort toward collecting and correlating information in the hopes of presenting their best guess that an intrusion has occurred. This is a noble goal, but NSM analysts recognize that perfect detection can never be achieved. Instead, NSM analysts look for indications and warnings, which they then investigate by analyzing alert, full content, session, and statistical data. The source of the initial tip-off, that first hint that "something bad has happened," almost does not matter. Once NSM analysts have that initial clue, they swing the full weight of their analysis tools to bear. For NSM, the alert is only the beginning of the quest, not the end.

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