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Now that we have covered the base features it’s time to consider how these tie in with policies, workflow, and reporting. We’ll focus on the features needed to support these processes rather than defining the processes themselves. Policy Creation File Activity Monitoring products support two major categories of policies: Entitlement (Permissions/Access Control) policies. These define which users can access which repositories and types of data. They define rules for things like orphaned user accounts, separation of duties, role/group conflicts, and other situations that don’t require real-time file activity. Activity-based polices. These alert and block based on real-time user activity. When evaluating products, look for a few key features to help with policy creation and management: Policy templates that serve as examples and baselines for building your own policies. A clean user interface that allows you to understand business context. For example, it should allow you to group categories, pool users and groups to speed up policy application (e.g., combine all the different accounting related groups into “Accounting”), and group and label repositories. This is especially important given the volume of entries to manage when you integrate with large user directories and multi-terabyte repositories. New policy wizards to speed up policy creation. Hierarchical management for multiple FAMs in the same organization. Role-based administration, including roles for super administrators and assigning policies to sub-administrators. Policy backup and restore. Workflow As with policy creation, we see workflow requirements focusing on the two major functions of FAM: entitlement management and activity monitoring. Entitlement Management This workflow should support a closed-loop process for collection of privileges, analysis, and application of policy-based changes. Your tool should do more than merely collect access rights – it should help you build a process to ensure that access controls match your policies. This is typically a combination of different workflows for different goals – including identification of orphan accounts with access to sensitive data, excessive privileges, conflict of interest/separation of duties based on user groups, and restricting access to sensitive repositories. Each product and policy will be different, but they typically share a common pattern: Collect existing entitlements. Analyze based on policies. Apply corrective actions (either building an alerting/blocking policy or changing privileges). Generate a report of identified and remediated issues. The workflow should also link into data owner identification because this must often be understood before changing rights. Activity Monitoring and Protection The activity monitoring workflow is very different than entitlement management. Here the focus is on handling alerts and incidents in real time. The key interface is the incident handling queue that’s common to most security tools. The queue lists incidents and supports various sorting and filtering options. The workflow tends to follow the following structure: Incident occurs and alert appears in the queue. It is displayed with the user, policy violated, and repository or file involved. The incident handler can investigate further by filtering for other activity involving that user, that repository, or that policy over a given time period (or various combinations). The handler can assign or escalate the incident to someone else, close the incident, or take corrective actions such as adjusting the file permissions manually. The key to keeping this efficient is not requiring the incident handler to jump around the user interface in a manual process. For example, clicking on an incident should show its details and then links to see other related incidents by user, policy, and repository. Incidents should also be grouped logically – an attempt to copy an entire directory should appear as one incident, not one incident for each of 1,000 files in the repository. Any FAM product may also include additional workflows, such as one for identifying file owners. Reporting One of the most important functions for any File Activity Monitoring product is robust reporting – this is particularly important for meeting compliance requirements. Aside from a repository of pre-defined reports for common requirements such as PCI and HIPAA, the tool should allow you to generate arbitrary reports. (We hate to list that as a requirement, but we still occasionally see security tools that don’t support creation of arbitrary reports). Share:

Introduction Our entire profession is called “information security”, but surprisingly few of our technologies focus on actually protecting the data itself, as opposed to the infrastructure surrounding it. Data Loss Prevention emerged nearly 10 years ago to address exactly this problem. By peering inside files, network traffic, and other sources – and understanding both content and context – DLP provides new capabilities comparable to when we first started looking inside network packets. The Data Loss Prevention market is split into two broad categories of tools – full suites dedicated to DLP, and what we call “DLP Light”. There is lots of confusion about the differences between these approaches… and even their definitions. In this series we will focus on DLP Light – what it is, how it works, and how to rapidly take advantage of it. (For more information on full-suite Data Loss Prevention, see our white paper Understanding and Selecting a Data Loss Prevention Solution. Defining DLP Light We are talking about a subset of Data Loss Prevention, so we need to start with our definition of DLP: Products that, based on central policies, identify, monitor, and protect data at rest, in motion, and in use, through deep content analysis. A full DLP suite includes network, storage, and endpoint capabilities; as well as a range of deep content analysis techniques such as document fingerprinting. DLP Light tools include a subset of those capabilities; they are generally features of, or integrated with, other security products – such as endpoint protection platforms, email security gateways, and next-generation firewalls. DLP Light tools tend to have some or all the following characteristics: Focused on a subset of ‘channels’. A DLP Light tool might focus on portable storage, email, web traffic, other channels, or a combination. Fewer/simpler content analysis techniques. Rather than providing a wide range of deep content analysis techniques, many of which are resource-intensive, DLP Light products tend to include a smaller set of techniques, or even a single method. The most common is pattern matching, which is the most commonly used technique in both full and Light DLP deployments. Less dedicated workflow. DLP Light tools are often integrated with, or features of, other security tools. As such, they lack the full self-contained workflow found in full DLP suites. You might ask, “So how is this still DLP?” The key defining characteristic of both full DLP and DLP Light is content analysis. If a tool can peer into network traffic or a file and sniff out something like a credit card number, it’s DLP. If all it does is rely on tagging/labeling, metadata, or contextual information… it isn’t DLP. The Role of DLP Light DLP Light plays an important role in a few different use cases: Organizations that already use the product the DLP Light tool integrates with – such as email security gateways – often want to start protecting sensitive data while constraining costs. Organizations that don’t require dedicated DLP tools. This is often due to less stringent or more circumscribed data security requirements. Organizations that want to scope out their DLP problem before investing in a dedicated tool. DLP Light can play a valuable role in helping assess data security risk. Organizations that want to start small and grow into full DLP. There is a bit of overlap between these cases, but they reflect the most common reasons we see people using DLP Light. Dedicated Data Loss Prevention is extremely powerful, but not appropriate for everyone. Next we will cover the technology side of DLP Light, and then we will finish with the Quick Wins process for rapidly deriving value from your implementation. Share:

At Securosis we tend to be passionate about security. We have the luxury of time (and lack of wingnuts yelling at us all day) to think about how security should work, and make suggestions for how to get there. We also have our own pet projects – areas of research that get us excited. We usually focus on ‘hot’ topics, because they pay the bills. We rarely get to step back and think outside the box about a security process that really needs to change. That’s why I’m very excited to be starting a new research project called Security Benchmarking, Going Beyond Metrics – interestingly enough, on security metrics and benchmarking. This topic is near and dear to my heart. I have been writing about metrics for years, and I broached the subject of benchmarking in my security methodology book (The Pragmatic CSO) back in 2007. To be candid, talking about security metrics – and more specifically security benchmarking – was way ahead of the market. Four years later, we still struggle to decide what we should count. Forget about comparing our numbers to other organizations to understand relative performance – which is how we would define a benchmark. It has been like trying to teach a toddler quantum physics. But we believe this idea’s time has come. In this series and the resulting white paper, I will revisit many of the ideas in The Pragmatic CSO, including updates based on industry progress since 2007. Ultimately, at Securosis we focus on practical (even pragmatic) application of research, so there won’t be any fluff or pie-in-the-sky handwaving. Just things you can start thinking about right now, with some actionable information to both rejuvenate your security metrics program and start comparing yourself against your peers. Before we jump in, thanks to our friends at nCircle for sponsoring this research. The rest of this series will appear on the complete (‘heavy’) side of our site and our heavy RSS feed. Introduction: Security Metrics As long as we have been doing security, we have been trying to count different aspects of our work. The industry has had vert limited success so far (yes – we are being very kind), so we need a better way to answer the question: “How effective are you at security?” The fundamental problem is that security is a nebulous topic, and at the end of the day the only important question is whether you are compromised or not – that is the ultimate measure of your effectiveness. But that doesn’t help communicate value to senior management or increase operational efficiency. The problem is further complicated by the literally infinite number of things to count. You can count emails and track which ones are bad – that’s one metric. So is the number of network flows, compared to how many of them are ‘bad’. If you can count it, it’s a metric. It may not be a good metric, but it is a metric. You can spend as much time as you like modeling, and counting, and correlating, and trying to figure out your “coverage” percentage, comparing the controls (always finite) to every conceivable attack (always infinite). But ultimately we have found that most security professionals do best keeping two sets of books. No, not like Worldcom did in the good old days, but two distinct sets of metrics: Important to senior management: Folks like the CIO, CFO, and CEO want to know whether you are ‘secure’ and how effective the security team is. They want to hear about the number of ‘incidents’, how much money you spend, and whether you hit the service levels you committed to. They tend to focus on those for ‘overhead’ functions – and whether you like it or not, security is overhead. Important to running your business: Distinct from business-centric numbers, you also need to measure the efficiency of your security processes. These are the numbers that make senior management eyes glaze over. Things like AV updates, time to re-image a machine or deploy a patch, number of firewall rule changes, and a host of other metrics that track what your folks are doing every day. The point of these numbers isn’t to gauge security quality overall, but to figure out how you can do your work faster and better. Of course, it’s almost impossible to improve things you don’t control. So we will focus on activities that can be directly impacted by the CSO and/or the security team. As we work through this series we will look at logical groupings of metrics that can be used for both operational and benchmarking purposes. But before we get ahead of ourselves, let’s define security benchmarking at a high level. Security Benchmarking Given our general failure to define and collect a set of objective, defendable measures of security effectiveness, impact, etc., a technique that can yield very interesting insight into your security environment is to compare your numbers to others. If you can get a fairly broad set of consistent data (both quantitative and qualitative), then compare your numbers to the dataset, you can get a feel for relative performance. This is what we mean by security benchmarking. Benchmarks have been used in other IT disciplines for decades. Whether for data center performance or network utilization, companies have always felt compelled to compare themselves to others. This hasn’t happened in security to date, mostly because we haven’t been sure what to count. If we can build some consensus on that, and figure out a way to collect and share that data safely, then benchmarking becomes much more feasible. Let’s discuss some metrics and why they would be interesting to compare to others: Number of incidents: Are you overly targeted? Or less effective at stopping attacks? The number of incidents doesn’t tell the entire story, but knowing how you fare relative to other is certainly interesting. Downtime for security issues: How effective you are at stopping attacks? And how severe is their impact? The downtime metric doesn’t capture everything, but it does get at the most visible impact of an attack. Number of activities: By tracking activity at a high level, you