Understanding and Selecting a Database Security Platform: Defining DSP

As I stated in the intro, Database Security Platform (DSP, to save us writing time and piss off the anti-acronym crowd) differs from DAM in a couple ways. Let’s jump right in with a definition of DSP, and then highlight the critical differences between DAM and DSP. Defining DSP Our old definition for Database Activity Monitoring has been modified as follows: Database Security Platforms, at a minimum, assess database security, capture and record all database activity in real time or near real time (including administrator activity); across multiple database types and platforms; and alert and block on policy violations. This distinguishes Database Security Platforms from Database Activity Monitoring in four key ways: Database security platforms support both relational and non-relational databases. All Database Security Platforms include security assessment capabilities. Database Security Platforms must have blocking capabilities, although they aren’t always used. Database Security Platforms often include additional protection features, such as masking or application security, which aren’t necessarily included in Database Activity Monitors. We are building a new definition due to the dramatic changes in the market. Almost no tools are limited to merely activity monitoring any more, and we see an incredible array of (different) major features being added to these products. They are truly becoming a platform for multiple database security functions, just as antivirus morphed into Endpoint Protection Platforms by adding everything from whitelisting to intrusion prevention and data loss prevention. Here is some additional detail: The ability to remotely audit all user permissions and configuration settings. Connecting to a remote database with user level credentials, scanning the configuration settings, then comparing captured data against an established baseline. This includes all external initialization files as well as all internal configuration settings, and may include additional vulnerability tests. The ability to independently monitor and audit all database activity including administrator activity, transactions, and data (SELECT) requests. For relational platforms this includes DML, DDL, DCL, and sometimes TCL activity. For non-relational systems this includes ownership, indexing, permissions and content changes. In all cases read access is recorded, along with the meta-data associated with the action (user identity, time, source IP, application, etc). The ability to store this activity securely outside the database. The ability to aggregate and correlate activity from multiple, heterogeneous Database Management Systems (DBMS). These tools work with multiple relational (e.g., Oracle, Microsoft, and IBM) and quasi-relational (ISAM, Terradata, and Document management) platforms. The ability to enforce separation of duties on database administrators. Auditing activity must include monitoring of DBA activity, and prevent database administrators from tampering with logs and activity records – or at least make it nearly impossible. The ability to protect data and databases – both alerting on policy violations and taking preventative measure to prevent database attacks. Tools don’t just record activity – they provide real-time monitoring, analysis, and rule-based response. For example, you can create a rule that masks query results when a remote SELECT command on a credit card column returns more than one row. The ability to collect activity and data from multiple sources. DSP collects events from the network, OS layer, internal database structures, memory scanning, and native audit layer support. Users can tailor deployments to their performance and compliance requirements, and collect data from sources best for their requirements. DAM tools have traditionally offered event aggregation but DSP requires correlation capabilities as well. DSP is, in essence, a superset of DAM applied to a broader range of database types and platforms. Let’s cover the highlights in more detail: Databases: It’s no longer only about big relational platforms with highly structured data – but now also in non-relational platforms. Unstructured data repositories, document management systems, quasi-relational storage structures, and tagged-index files are being covered. So the number of query languages being analyzed continues to grow. Assessment: “Database Vulnerability Assessment” is offered by nearly every Database Activity Monitoring vendor, but it is seldom sold separately. These assessment scans are similar to general platform assessment scanners but focus on databases – leveraging database credentials to scan internal structures and metadata. The tools have evolved to scan not only for known vulnerabilities and security best practices, but to include a full scan of user accounts and permissions. Assessment is the most basic preventative security measure and a core database protection feature. Blocking: Every database security platform provider can alert on suspicious activity, and the majority can block suspect activity. Blocking is a common customer requirement – it is only applied to a very small fraction of databases, but has nonetheless become a must-have feature. Blocking requires the agent or security platform to be deployed ‘inline’ in order to intercept and block incoming requests before they execute. Protection: Over and above blocking, we see traditional monitoring products evolving protection capabilities focused more on data and less on database containers. While Web Application Firewalls to protect from SQL injection attacks have been bundled with DAM for some time, we now also see several types of query result filtering. One of the most interesting aspects of this evolution is how few architectural changes are needed to provide these new capabilities. DSP still looks a lot like DAM, but functions quite differently. We will get into architecture later in this series. Next we will go into detail on the features that define DSP and illustrate how they all work together. Share:

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Implementing DLP: Integration Priorities and Components

It might be obvious by now, but the following charts show which DLP components, integrated with which existing infrastructure, you need based on your priorities. I have broken this out into three different images to make them more readable. Why images? Because I have to dump all this into a white paper later, and building them in a spreadsheet and taking screenshots is a lot easier than mucking with HTML-formatted charts Between this and our priorities post and chart you should have an excellent idea of where to start, and how to organize, your DLP deployment. Share:

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