This is the seventh post in the long, long series (part 1, part 2, part 3 – all parts). A few tips on how you can use it in your organization can be found in Part 1. You can also retain me to customize or adapt it to your needs.
And so we continue with our Complete PCI DSS Log Review Procedures:
Building an Initial Baseline Using a Log Management Tool
To build a baseline using a log management tool perform the following:1. Make sure that relevant logs from a PCI application are aggregated by the log management tools
2. Confirm that the tool can “understand” (parse, tokenize, etc) the messages and identify the “event ID” or message type of each log. For pure indexing tools, see the manual procedures presented in the next section.
3. Select a time period for an initial baseline: “90 days” or “all time” if logs have been collected for less than 90 days. In some cases, 7-30 days periods can be used.
4. Run a report that shows counts for each message type. This report indicates all the log types that are encountered over the 90 day period of system operation
5. Assuming that no breaches of card data have been discovered , we can accept the above report as a baseline for “routine operation”
6. An additional step should be performed while creating a baseline: even though we assume that no compromise of card data has taken place, there is a chance that some of the log messages recorded over the 90 day period triggered some kind of action or remediation. Such messages are referred to as “known bad” and should be marked as such.
Let’s go through a complete example of the above strategy.
1. Make sure that relevant logs from a PCI DSS application are aggregated by the available log management tool
At this step, we look at the log management tools and verify that logs from PCI applications are aggregated. It can be accomplished by looking at report with all logging devices:
Timeframe: Jan 1, 2009 - Mar 31, 2009 (90 days) | ||
Device Type | Device Name | Log Messages |
Windows 2003 | Winserver1 | 215762 |
Windows 2003 | Winserver2 | 215756 |
SANITIZED1 | SANITIZED1 | 53445 |
SANITIZED2 | SANITIZED2 | 566 |
SANITIZED3 | SANITIZED3 | 3334444 |
2. Confirm that the tool can “understand” (parse, tokenize, etc) the messages and identify the “event ID” or message type of each log
This step is accomplished by comparing the counts of messages in the tool (such as the above report that shows log message counts) to the raw message counts in the original logs.
3. Select a time period for an initial baseline: “90 days” or “all time” if logs have been collected for less than 90 days
In this example, we are selecting 90 days since logs are available.
4. Run a report that shows counts for each message type. For example, the report might look something like this:
Timeframe: Jan 1, 2009 - Mar 31, 2009 (90 days) | |||
Event ID | Event Description | Count | Average Count/day |
1517 | Registry failure | 212 | 2.3 |
562 | Login failed | 200 | 2.2 |
563 | Login succeeded | 24 | 0.3 |
550 | User credentials updated | 12 | 0.1 |
5. Assuming that no breaches of card data have been discovered , we can accept the above report as a baseline for “routine operation”
During the first review it logs, it might be necessary to investigate some of the logged events before we accept them as normal. The next step explains how this is done.
6. An additional step should be performed while creating a baseline: even though we assume that no compromise of card data has taken place, there is a chance that some of the log messages recorded over the 90 day period triggered some kind of action or remediation. Such messages are referred to as “known bad” and should be marked as such.
Some of the logs in our 90 day summary actually indicative of the problems and require an investigation
Event ID | Event Description | Count | Average Count/day | Routine or “bad” |
1517 | Registry failure | 212 | 2.3 | |
562 | Login failed | 200 | 2.2 | |
563 | Login succeeded | 24 | 0.3 | |
550 | User credentials updated | 12 | 0.1 | |
666 | Memory exhausted | 1 | N/A | Action: restart system |
Creating a baseline manually is possible, but more complicated.
To be continued.
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