SecMon State of the Union: Revisiting the Team of Rivals
Things change. That’s the only certainty in technology today, and certainly in security. Back when we wrote Security Analytics Team of Rivals, SIEM and Security Analytics offerings were different and did not really overlap. It was more about how can they coexist, instead of choosing one over the other. But nowadays the overlap is significant, so you need existing SIEM players basically bundling in security analytics capabilities and security analytics players positioning their products as next-generation SIEM. As per usual, customers are caught in the middle, trying to figure out what is truth and what is marketing puffery. So Securosis is again here to help you figure out which end is up. In this Security Monitoring (SecMon) State of the Union series we will offer some perspective on the use cases which make sense for SIEM, and where security analytics makes a difference. Before we get started we’d like to thank McAfee for once again licensing our security monitoring research. It’s great that they believe an educated buyer is the best kind, and appreciate our Totally Transparent Research model. Revisiting Security Analytics Security analytics remains a fairly perplexing market because almost every company providing security products and/or services claims to perform some kind of analytics. So to level-set let’s revisit how we defined Security Analytics (SA) in the Team of Rivals paper. A SA tool should offer: Data Aggregation: It’s impossible to analyze without data. Of course there is some question whether a security analytics tool needs to gather its own data, or can just integrate with an existing security data repository like your SIEM. Math: We joke a lot that math is the hottest thing in security lately, especially given how early SIEM correlation and IDS analysis were based on math too. But this new math is different, based on advanced algorithms and using modern data management to find patterns within data volumes which were unimaginable 15 years ago. The key difference is that you no longer need to know what you are looking for to find useful patterns, a critical limitation of today’s SIEM. Modern algorithms can help you spot unknown unknowns. Looking only for known and profiled attacks (signatures) is clearly a failed strategy. Alerts: These are the main output of security analytics, so you want them prioritized by importance to your business. Drill down: Once an alert fires an analyst needs to dig into the details, both for validation and to determine the most appropriate response. So analytics tools must be able to drill down and provide additional detail to facilitate response. Learn: This is the tuning process, and any offering needs a strong feedback loop between responders and the folks running it. You must refine analytics to minimize false positives and wasted time. Evolve: Finally the tool must improve because adversaries are not static. This requires a threat intelligence research team at your security analytics provider constantly looking for new categories of attacks, and providing new ways to identify them. These are attributes the requirements of a SA tool. But over the past year we have seen these capabilities not just in security analytics tools, but also appearing in more traditional SIEM products. Though to be clear, “traditional SIEM” is really a misnomer because none of the market leaders are built on 2003-era RDBMS technology or sitting still waiting to be replaced by new entrants with advanced algorithms. In this post and the rest of this series we will discuss how well each tool matches up to the emerging use cases (many of which we discussed in Evolving to Security Decision Support), and how technologies such as the cloud and IoT impact your security monitoring strategy and toolset. Wherefore art thou, Team of Rivals? The lines between SIEM and security analytics have blurred as we predicted, so what should we expect vendors to do? First understand that any collaboration and agreements between SIEM and security analytics are deals of convenience to solve the short-term problem of the SIEM vendor not having a good analytics story, and the analytics vendor not having enough market presence to maintain growth. The risk to customers is that buying a bundled SA solution with your SIEM can be problematic if the vendor acquires a different technology and eventually forces a migration to their in-house solution. This underlies the challenge of vendor selection as markets shift and collapse. We are pretty confident that the security monitoring market will play out as follows over the short term: SIEM players will offer broad and more flexible security analytics. Security analytics players will spend a bunch of time filling out SIEM reporting and visualization features sets to go after replacement deals. Customers will be confused and unsure whether they need SIEM, security analytics, or both. But that story ends with confused practitioners, and that’s not where we want to be. So let’s break the short-term reality down a couple different ways. Short-term plan: You are where you are… The solution you choose for security monitoring should suit emerging use cases you’ll need to handle and the questions you’ll need to answer about your security posture over time. Yet it’s unlikely you don’t already have security monitoring technology installed, so you are where you are. Moving forward requires clear understanding of how your current environment impacts your path forward. SIEM-centric If you are a large company or under any kind of compliance/regulatory oversight – or both – you should be familiar with SIEM products and services because you’ve been using them for over a decade. Odds are you have selected and implemented multiple SIEM solutions so you understand what SIEM does well…. And not so well. You have no choice but to compensate for its shortcomings because you aren’t in a position to shut it off or move to a different platform. So at this point your main objective is to get as much value out of the existing SIEM as you can. Your path is pretty straightforward. First refine the alerts coming out of the system to increase the signal from the SIEM and focus your team on triaging and investigating real attacks. Then
