Monitoring up the Stack: DAM, part 2By Adrian Lane
The odds are, if you already have a SIEM/Log Management platform in place, you already look at some database audit logs. So why would you consider DAM in addition? The real question when thinking about how far up the stack (and where) to go with your monitoring strategy, is whether adding database activity monitoring data will help with threat detection and other security efforts. To answer that question, consider that DAM collects important events which are not in log files, provides real-time analysis and detection of database attacks, and blocks dangerous queries from reaching the database. These three features together are greater than the sum of their parts.
As we discussed in part 1 on Database Activity Monitoring, database audit logs lack critical information (e.g., SQL statements), events (e.g., system activity) and query results needed for forensic analysis. DAM focuses on event collection into areas SIEM/Log Management does not venture: parsing database memory, collecting OS and/or protocol traffic, intercepting database library calls, undocumented vendor APIs, and stored procedures & triggers. Each source contains important data which would otherwise be unavailable.
But the value is in turning this extra data into actionable information. Over and above attribute analysis (who, what, where, and when) that SIEM uses to analyze events, DAM uses lexical, behavioral, and content analysis techniques. By examining the components of a SQL statement, such as the
from clauses, and the type and number of parameters, SQL injection and buffer overflow attacks can be detected. By capturing normal behavior patterns by user and group, DAM effectively detects system misuse and account hijacking. By examining content – as it is both stored and retrieved – injection of code or leakage of credit card numbers can be detected as it occurs.
Once you have these two capabilities, blocking is possible. If you need to block unwanted or malicious events, you need to react in real time, and to deploy the technology in such a way that it can stop the query from being executed. Typical SIEM/LM deployments are designed to efficiently analyze events, which means only after data has been aggregated, normalized, and correlated. This is too late to stop an attack from taking place. By detecting threats before they hit the database, you have the capacity to block or quarantine the activity, and take corrective action. DAM, deployed in line with the database server, can block or provide ‘virtual database patching’ against known threats.
Those are the reasons to consider augmenting SIEM and Log Management with Database Activity Monitoring.
How do you get there? What needs to be done to include DAM technology within your SIEM deployment? There are two options: leverage a standalone DAM product to submit alerts and events, or select a SIEM/Log Management platform that embeds these feature. All the standalone DAM products have the capability to feed the collected events to third party SIEM and Log Management tools. Some can normalize events so that SQL queries can be aggregated and correlated with other network events. In some cases they can also send alerts as well, either directly or by posting them to
Fully integrated systems take this a step further by linking multiple SQL operations together into logical transactions, enriching the logs with event data, or performing subsequent query analysis. They embed the analysis engine and behavioral profiling tools – allowing for tighter policy integration, reporting, and management. In the past, most database activity monitoring within SIEM products was ‘DAM Light’ – monitoring only network traffic or standard audit logs, and performing very little analysis. Today full-featured options are available within SIEM and Log Management platforms.
To restate, DAM products offer much more granular inspection of database events that SIEM because DAM includes many more options for data collection, and database-specific analysis techniques. The degree to which you extract useful information depends on whether they are fully integrated with SIEM, and how much analysis and event sharing are established. If your requirement is to protect the database, you should consider this technology.