So far this series has introduced Database Security Platforms, provided a full definition of DSP, discussed the origins and evolution of DAM to DSP, and described the technical platform architecture. We have covered the basics of a Database Security Platform. It might seem like a short list compared to all the other extended features we will cover later, but these are the most important ares, and the primary reasons to buy these tools.

Activity Monitoring

The single defining feature of Database Security Platforms is their ability to collect and monitor all database activity. This includes all administrator and system activity that touches data (short of things like indexing and other autonomous internal functions).

We have already covered the various event sources and collection techniques used to power this monitoring, but let’s briefly review what kinds of activity these products can monitor:

  • All SQL – DML, DDL, DCL, and TCL: Activity monitoring needs to include all interactions with the data in the database, which for most databases (even non-relational) involves some form of SQL (Structured Query Language). SQL breaks down into the Data Manipulation Language (DML, for select/update queries), the Data Definition Language (DDL, for creating and changing table structure), the Data Control Language (DCL, for managing permissions and such) and the Transaction Control Language (TCL, for things like rollbacks and commits). As you likely garnered from our discussion of event sources, depending on a product’s collection techniques, it may or may not cover all this activity.
  • SELECT queries: Although a SELECT query is merely one of the DML activities, due to the potential for data leakage, SELECT statements are monitored particularly closely for misuse. Common controls examine the type of data being requested and the size of the result set, and check for SQL injection.
  • Administrator activity: Most administrator activity is handled via queries, but administrators have a wider range of ways they can connect to database than regular users, and more ability to hide or erase traces of their activity. This is one of the biggest reasons to consider a DSP tool, rather than relying on native auditing.
  • Stored procedures, scripts, and code: Stored procedures and other forms of database scripting may be used in attacks to circumvent user-based monitoring controls. DSP tools should also track this internal activity (if necessary).
  • File activity, if necessary: While a traditional relational database relies on query activity to view and modify data, many newer systems (and a few old ones) work by manipulating files directly. If you can modify the data by skipping the Database Management System and editing files directly on disk (without breaking everything, as would happen with most relational systems), some level of monitoring is probably called for.

Even with a DSP tool, it isn’t always viable to collect everything, so the product should support custom monitoring policies to select what types of activities and/or user accounts to monitor. For example, many customers deploy a tool only to monitor administrator activity, or to monitor all administrators’ SELECT queries and all updates by everyone.

Policy Enforcement

One of the distinguishing characteristics of DSP tools is that they don’t just collect and log activity – they analyze it in real or near-real time for policy violations. While still technically a detective control (we will discuss preventative deployments later), the ability to alert and respond in or close to real time offers security capabilities far beyond simple log analysis. Successful database attacks are rarely the result of a single malicious query – they involve a sequence of events (such as exploits, alterations, and probing) leading to eventual damage. Ideally, policies are established to detect such activity early enough to prevent the final loss-bearing act. Even when an alert is triggered after the fact, it facilitates immediate incident response, and investigation can begin immediately rather than after days or weeks of analysis.

Monitoring policies fall into two basic categories:

  • Rule-based: Specific rules are established and monitored for violation. They can include specific queries, result counts, administrative functions (such as new user creation and rights changes), signature-based SQL injection detection, UPDATE or other transactions by users of a certain level on certain tables/fields, or any other activity that can be specifically described. Advanced rules can correlate across different parts of a database or even different databases, accounting for data sensitivity based on DBMS labels or through registration in the DAM tool.
  • Heuristic: Monitoring database activity builds a profile of ‘normal’ activity (we also call this “behavioral profiling”). Deviations then generate policy alerts. Heuristics are complicated and require tuning to work effectively. They are a good way to build a base policy set, especially with complex systems where manually creating deterministic rules by hand isn’t realistic. Policies are then tuned over time to reduce false positives. For well-defined systems where activity is consistent, such as an application talking to a database using a limited set of queries, they are very useful. Of course heuristics fail when malicious activity is mis-profiled as good activity.

Aggregation and Correlation

One characteristic which Database Security Platforms share with System Information and Event Management (SIEM) tools is their ability to collect disparate activity logs from a variety of database management systems – and then to aggregate, correlate, and enrich event data. The combination of multiple data sources across heterogenous database types enables more complete analysis of activity rather than working only on one isolated query at a time. And by understanding the Structured Query Language (SQL) syntax of each database platform, DSP can interpret queries and parse their meaning. While a simple SELECT statement might mean the same thing across different database platforms, each database management system (DBMS) is chock full of its own particular syntax. A DSP solution should understand the SQL for each covered platform and be able to normalize events so the analyst doesn’t need to know the ins and outs of each DBMS. For example, if you want to review all privilege escalations on all covered systems, a DSP tool will recognize those various events across platforms and present you with a complete report without you having to understand the SQL particulars of each one.


We typically see three types of assessment included in DSP products:

  • Vulnerability assessments: Credentialed and non-credentialed scans of databases to identify known vulnerabilities and missing security patches.
  • Configuration assessments: Credentialed and non-credentialed analysis of database internal and external configurations, for both security-related issues and configuration policy compliance.
  • Entitlement analysis: Credentialed scan of user accounts within a database, primarily to identify security and compliance issues, but also often used for general account cleanup. Database user accounts are often more complex than those of other systems due to the various ways user accounts are defined – for example, you could have one human with network user, database user, and system user accounts. Permissions are further complicated by group and role based entitlements the database provides.

Most of these tools also include database discovery to find databases on the network to assess.

In our next post we will delve into advanced features that really set DSP apart from basic DAM products.