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Figure 9-2. Offset and pattern location On the Network Monitor toolbar, click the Edit Capture Filter button. In the Capture Filter dialog box, click Pattern and enter your pattern for port 3389 as a hexadecimal value, 0D3D. For the offset, enter a value of 22, and leave From Start of Frame checked. Next, because you want to exclude these frames, select each pattern, click Not to add the exclusion to the tree, and then click OK, as shown in Figure 9-3.

The configuration consists of selecting the columns from which to extract terms (Figure 10-29), the specification of where to find term exclusions, and properties that specify how the extraction is performed.

One of the services that receives little to no attention in literature on Mac OS X Server is using the server as a default gateway for your environment. This primarily is because most environments don t actually use Mac OS X Server as a router. A number of other

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Now, click the Start Capture button, and let the capture run as you view a report with Report Manager. You will want to make sure you access a report that could have identifiable information in it. The Employee Service Cost report that you have been working with does, so you can use it for this purpose. You are concerned not only with capturing user login information potentially passed in a URL but also with any information that may identity a patient. If this is the case, and you allow access to the report over the Internet, you would have a serious problem and be out of compliance with HIPAA regulations. After executing the report, analyzing the captured frames reveals the disturbing news. You can see the name of one of the patients (whose true identity has been altered to be Bill Shakespeare) returned directly in an HTTP frame, as clearly shown in Figure 9-4. In this case, you have not analyzed other types of traffic, such as SQL requests on port 1433, to see whether other protocols are potentially sending plain-text information, but you can use the same tool to do that.

Figure 10-29. Select the columns from which to extract terms. As with other advanced transformations such as the fuzzy-match tasks, an extracted term gets a score value when extracted that signifies the confidence the extraction engine has that the extracted value is a valid term. The output from this transform consists of only two columns, the names of which are specified on the first tab of the task editor: Term: Name to use for the column containing an extracted term. Score: Name to use for the column containing the extracted term score.

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