Continuous Security Monitoring: Migrating to CSM
We spent a bulk of this series defining the major use cases for Continuous Security Monitoring, taking a journey through Attacks, Change Control, and Compliance. We know that many of you tend to be people of action, who want to just get going. But without a proper plan and definition for what you are trying to achieve with your security monitoring initiative, you will just end up with a lot of shiny expensive shelfware. Now you need to decide on the technology platform you will use to aggregate your data sources and perform the CSM analysis. You have a bunch of candidates, and probably a few already operational in your environment – though likely underutilized. We will cover the general requirements you need to cover, and then consider whether an existing platform can satisfy them. Not to spoiler the ending, but shockingly enough it will depend on your use case. Then we will discuss deployment models and the process involved to broaden our use cases. Selecting the CSM Platform Many folks feel their eyes glaze over when someone uses the word ‘platform’. Security folks have a long and tattered history with all sorts of ‘platforms’, none of which have really done what they were supposed (promised) to do. Now we have the opportunity to reset expectations, which is why looking at the CSM platform in terms of use cases is critical. Let’s start with the general platform requirements and what you need: Secure and scalable: Depending on your primary use case and the data sources you choose to aggregate, you may have significant scalability requirements. But for lighter use cases such as compliance, data storage demands are less intense. But we like planning for the future, which means picking a solution that can provide increased scale – even if you don’t need it yet. That comes back to architecture and deployment models, as described in our Security Management 2.0 paper. Keep in mind that the CSM environment includes sensitive data. So you will want to make sure your platform provides adequate security (strong authentication, data protection at rest, data integrity, etc.) to protect your information. Analytics: Monitoring is all about being able to find patterns in disparate data sources, which requires the ability to analyze lots of data. Does that mean you need “big data” analytics? Again it depends on the use case, but make sure you can both look for patterns you already know about (standard attack scenarios) and also unknown situations that are clearly not normal. Agentry: For the attack and change control use cases you will need to get information directly from monitored endpoints, which requires some kind of agent running on the devices. Does it need to be a persistent agent? Not necessarily. You can get much of the data you need via credentialed scans or dissolving agents. But for truly continuous monitoring you will need something on the device looking for indicators of malicious activity. Flexible alerting: Collecting data is good, but alerts make that data useful. You will want to ensure each alert provides enough information for you to actually do something about it. Whether that’s a poor man’s capability to manage an incident, or integration with a broad investigative platform, you will need some way to operationally use the information from the platform. With the increasing availability of third-party threat intelligence, you should also look for the ability to pull in external research feeds to search for specific indicators in the monitored environment. Visualization: A good dashboard environment offers user-selectable elements, and defaults for both technical and non-technical users. The dashboard should focus on the highest-level information (which devices are at risk, aggregate reports, system health, etc.), and provide the ability to drill down as appropriate. Given the current state of technology, a web-based interface with significant customization is now table stakes. Reporting: If compliance is your primary use case, then your requirements are all about reporting. You need to produce artifacts to document how the security monitoring environment substantiates the effectiveness of controls on devices in scope. Even if another use cases is your driver, you will need some measure of ongoing reporting to satisfy compliance requirements. Now that we know what the CSM platform is, let’s take a minute to mention what it doesn’t need to be – at least today: Real time: One of the biggest confusions in security monitoring is ‘real-time’. You are aggregating data from an event that already happened, so it cannot actually be in real time. That said, the sooner you get the data, analyze it, and are able to determine whether you have an issue, the better. Compliance doesn’t require any kind of real-time response. Change control requires more timeliness, for critical devices, and the attack use case can urgently require fast reaction, so the shorter the window between event and alert, the better. But keep in mind that ‘real-time’ alerts aren’t useful if you cannot respond in immediately. If you have a limited triage/investigations staff (and who doesn’t?), that minimizes the relevance of ‘real-time’ response. Big data centric: Big data is all the rage in all sorts of security discussions. But for compliance and change control big data is generally overkill. And depending on the capabilities of your adversaries, advanced analytics may not add value to your efforts. Eventually you may need a true security analytics platform with pseudo-real-time data collection to drive your CSM process. If you are facing truly advanced attackers you might need much more robust searching and forensics capabilities (perhaps including big data analytics). But if you are starting with compliance or change control advanced analytics are likely to be overkill. Doesn’t the SIEM Do This? You could certainly make a case that the SIEM/Log Management product you probably already have in place is in a good position to become the platform for CSM. SIEM does a good job with most of the requirements above. And SIEM already consumes most of the data sources needed for our use cases, with the exception of endpoint forensics and network packet capture… and a number of SIEMs are gaining the ability
