The Case for Wire Data: Save the SIEM

I recently attended Black Hat and one of the key narratives that I overheard while meeting with INFOSEC practitioners was the need to have better/smarter data. Attendees voiced some frustration with current traditional tools that are delivering too much data and the time it takes to respond to an incident leaves attackers enough time to do their dirty work. Over the last year we have heard several criticisms of SIEM based solutions and some of the limitations that they have in dealing with today’s more agile threat landscape. My induction into security was based in SIEM and I even ran a blog dedicated to Syslogs at where I detailed work I had done around my “Skunk” project. It stemmed from my desperate, but unheeded, pleas to my former manager to purchase Splunk saying “Can I have $20,000?” and being told “No” then seeing Kiwi Syslog support SQL Server connections and I then made a second plea, “Can I have $300 dollars?” which was accepted. SKUNK stood for SQL, KIWI to make it like Splunk. We used SQL, SSRS and KIWI’s ODBC connector with some parsing engines. As SIEM products go, Splunk was ABSOLUTELY my first love! I still know a few brilliant engineers that work there and I have a great deal of respect for what that company has done to revolutionize security.

Over the last 5 years I had another epiphany, I was introduced by an SE named Matt Cauthorn to the concept of Wire Data Analytics. So why am talking about a SIEM on a wire data analytics blog? Well, first, I feel like a lot of the criticism of SIEM’s aren’t necessarily 100% fair. My experience with the SIEM is that it is only as good as the data you put into it. Even more importantly, the investment you make in back-end processes in terms of how you parse, interpret and report with back end processes so that you can “set context”. By “set context” I mean find actionable data which is the subject of some intense criticisms of SIEM products today.

In an article from Dark Reading citing a Ponemon institute study:

Today, those same products “barely work at all,” says Exabeam CMO Rick Caccia. Older systems aren’t built to capture credential or identity-based threats, hackers impersonating people on corporate networks, or rogue employees trying to steal data. A recent report by the Ponemon Institute, commissioned by Cyphort, discovered 76% of SIEM users across 559 businesses view SIEM as a strategically important security tool. However, only 48% were satisfied with the actionable intelligence their SIEMs generate.


With that I’d like to start writing about how Wire Data Analytics with ExtraHop can set context in flight, reduce the cost of your SIEM investment and bring to bear an entirely new set of metrics and provide security teams with better data instead of more data.

Setting Context in Flight:
ExtraHop’s wire data analytics capabilities enable you to set context in flight by interrogating the wire for specific events then applying logic to them in milliseconds so that your logs have considerably more value and a much higher intelligence yield.

Example: Auditing your PCI Environment.
You have a PCI environment that you want to set up network based auditing for. The rules are as follows:

  • Alert on ANY external non-RFC1918 access and report it as an Egress Violation
  • Alert on any client or server based traffic that has not been pre-defined.

Using the SIEM only approach you must perform the following:

– Audit/Log every single build-up and tear-down action which could result in thousands and potentially millions of logs via Syslog or Netflow
– Index, parsed these logs
– Build/run back end batch processes to root out the few suspect transactions from the, potentially, millions of logs that you already have.

Now let’s consider what that would look like using an ExtraHop appliance.
– Create a rule that sets the appropriate communications
– Acceptable client/server traffic (Fill out the pre-defined application inspection trigger with the appropriate protocols)
– Tell the ExtraHop appliance to alert on any non-RFC1918 connection.
– Send ONLY actionable intelligence to the SIEM relieving both the CSIRT team and the back-end SIEM of the burden of indexing/parsing and sorting millions of logs.


Click Image:trigger

After setting the criteria, aka “casting the web” we need only lie in wait for something to run across it. In the video below you will see examples of how we have integrated with Splunk Cloud to “set context in flight” by sending ONLY logs that have violated the criteria cast in the application inspection trigger above.

Now instead of leaving the Threat hunter to sort through thousands or millions of logs on the back end we are sending data that is actionable because we set the rules prior to sending the Syslog message. As you can see below in the Splunk Cloud instance, every transaction sent to the SIEM is actionable vs. the madness of sending thousands and thousands of logs every second to your SIEM. This will make the bill for indexing much cheaper both from a licensing standpoint as well as a hardware scaling standpoint. (Please Watch the Video on Youtube)

New Concept: Intelligence Yield
In my time as the Event Correlation guru for my security team one of the more frustrating things I would run into is the fact that I consistently needed about 30% of what was in a log file but I would pay to store and/or index 100% of the data. When you use ExtraHop as a forwarder you have the ability to actually pick and choose what parts of a log/payload you want to forward and you can even customize the delimiter if you like. This means that there is no leftover ASCII that needs to be stored/indexed. While this may not seem like a lot, at scale it can actually get expensive! Another way we provide better intelligence yield is, as you noted in the example above, we set the conditions under which we would like to send Syslog data and ignore transactions that you may already be logging via whatever daemon you are running (apache for HTTP, etc). Why log HTTP network connections when you are already doing it in /var/log/apache/.


Possible Licensing Cost Savings:
We actually had a scenario with a customer where they wanted to find out if there were excessive logins from a single client. The traffic was sending thousands of messages per minute to their SIEM. We looked what was happening and we did the following:

  • Kept a running ticker of the number of logins per client IP
  • Sent actionable data to the SIEM by sending just those client IPs that had more than 5 logins in a ten minute period reducing the message count from thousands per minute to between 5-7.

In the fictitious scenario below, we are using Splunk’s list price to show the difference in savings when you use ExtraHop as a forwarder and give the SIEM a break on processing messages. Keep in mind, while this is an overly simple example, there may be parts of your logging regimen that ExtraHop can provide in-flight context as well as a reduction in the amount of work, licensing costs and an increase in the quality of the data you are receiving in your SIEM.

Scenario: Reducing your licensing costs as well as your Mean Time To “WTF!?” (MTTWTF)
A customer has 500 clients with each Client node sending around 2500 logs per minute (this is HARDLY out of the ordinary for a large enterprise).  So if you have say 500 clients sending 2500 events per minute you are looking at 1.25 million events being indexed every minute.  

Let’s say we use the SESSION_EXPIRE event, we are sending ONE event that has the Client:Server and a count of 500,  In terms of “Intelligence  Yield” it has the same value but it has an overall impact of .04 percent (not four percent, “point zero four” percent).  I would argue that the intelligence yield is actually higher because you have delivered a level of context (the count) in the syslog messages vs. leaving it to some algorithm or batch process on the back end to deliver context.  Five events….”meh”……500, 5000 events….”WTF!”.

Our “MTTWTF” (Mean Time To “WHAT THE F***….”) is potentially MUCH faster.  

So if I take the overly simplistic view of a 50GB Splunk license (it will NOT be this easy for you but I think most customers will get the value prop here)

From Splunk’s Website:

A 50GB Splunk license is $38K Annual or $95K perpetual WITH $19K in support.  If we can proportionally reduce the impact of their SIEM product you get the improved “MTTWTF” with a 2GB license which would cost $1500 Annually and $4500 perpetual w/$1500 in maintenance.

As I said earlier, the view here is simplistic but there is WITHOUT QUESTION logging regimens within customers that we can look to make more efficient using ExtraHop’s Wire Data Analytics and the Session table to replace logging every transaction. Also, please credit Splunk for publishing their sticker price.

This is not a knock on Splunk!

In this model you get the following:

  • On perpetual a 2100% decrease in initial costs
  • On Annual a 2500% decrease in initial costs
  • Better Intelligence Yield
  • No forwarders or debugging levels to enable on the clients themselves.

Keep in mind, the larger the license the smaller the savings will be as Splunk rewards customers for the larger GB license but the point here is, there is significant savings to be made in addition to having all around better logs.

What’s on YOUR wire!!?
When you leverage ExtraHop as a log forwarder you actually get access to the best source of data on your network. Not only do you get access to it, but you get application inspection triggers that will allow you to actively interact with it. When you are using ExtraHop, unlike logging based solutions, you are not dependent on someone to “opt-in” to logging. You will NEVER have to go to another team and ask them to install forwarders, agents or send data to a remote system. If you have an IP address, you have already opted-in and if you have an IP address, there is NO opting out. If a system is rooted and /var/log is deleted…we will still log. If logging is shut off on a system, we, like a closed caption TV, will continue surveillance and logging.

No agents, no logs….NO PROBLEM!
As previously stated, ExtraHop works from a mirror of the Network so if you have IoT devices that cannot log, we can log it for them. If you have a systems that are “certified” by a vendor and cannot be patched or have forwarders installed on them, not a problem, we can log for them. If you have a malicious raspberry pi plugged into the MDF and have ACL’d yourself off so you cannot be discovered….not a problem, we’ll log everything you do!! (We also send a New Device alert when your mac shows up). What the ExtraHop Discover appliance does is allow you to “log the un-logable” if that makes sense. Adopting a passive, surveillance strategy is a perfect complement to any SIEM regimen.

As I stated near the beginning of the post, INFOSEC teams do NOT need more data, they need better data. I am not saying you no longer need a SIEM but I am absolutely saying that we need to send better data to our SIEM. Using ExtraHop can greatly enhance the agility and certainty of any CSIRT team or SOC. Evaluating transactions BEFORE you send them to the SIEM provides the level of certainty needed to take that next step toward orchestration and automation. As Threat Hunting continues to evolve as a discipline, no one will provide you a more intelligent and scalable web to cast as we move from playing whack-a-mole to a role more consistent with a trap-door spider. Several INFOSEC workflows are currently tied to the SIEM and let’s not throw the baby out with the bathwater. The SIEM can still serve us well, we just need to take steps to send it better data, there is no better source of data than the network and there is no solution more capable of letting you mine data directly off the network than ExtraHop.

Thanks for reading


John M. Smith
Security Systems Engineer
ExtraHop Networks.


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