Lookup the MD5s in our lookup table, returning the date first seen: lookup md5tracker.csv MD5 as MD5 OUTPUT FirstSeen as LookupFirstSeen Index=windows MD5=* | dedup MD5 | lookup md5tracker.csv MD5 as MD5 OUTPUT FirstSeen as LookupFirstSeen | where NOT LookupFirstSeen LIKE “%” | eval FirstSeen=_time | table FirstSeen, MD5, BaseFileName, CompanyName, FileDescription, FileVersion, InternalName, Language, Signed, Length | inputlookup md5tracker.csv append=t | dedup MD5 | outputlookup md5tracker.csvįind the desired records: index=windows MD5=* I like to preserve some of the metadata that WLS reports with each record for later use – avoid re-searching, etc. Next, we need to search for and add the desired data to the csv file. This will create an empty csv file named “md5tracker.csv”. Now that we are receiving hashes for all executed files and loaded modules, let’s start tracking them in Splunk.įirst we’ll need to create a lookup table, there are a few ways to do this, a quick way is simply: I also enabled the “ModuleMonitor” in WLS which tracks loaded modules by processĪnd configured it to provide MD5 hashes for these as well. ![]() I’ve enabled Process Auditing via the Group Policy Editor and configured WLS to provide MD5 hashes. “ 29” and “ 19” respectively, they are still single value row.The method presented below can be used to track any log attribute in Splunk this example demonstrates watching MD5 hashes of executed files and loaded modules. “ 22”, that’s why they have together created a multivalue row inside the name field.īut, as the “ name” field values “ Shilpa” and “ Palash” have unique “ age” field values i.e. “ 34”, that’s why they are grouped together created a multivalue row inside the name field.Īlso, as the “ name” field values “ Neha” and “ Mohan” have the same “ age” field value i.e. Now, as the “ name” field values “ Rehan” and “ Ayush” have the same “ age” field value i.e. Please, see the below query, index=test_index | table name,age | dedup name,age | mvcombine name Now, in this case, if you want to make the “ name” field multivalue, what will be the result, let’s see that. “ 22”.Īnd, the “ name” field values “ Shilpa” and “ Palash” have unique “ age” field values i.e. “ 34”.Īnd, also for, the “ name” field values “ Neha” and “ Mohan”, the value of the “ age” field is the same i.e. Now, if you will see the above image properly, you will see that,įor, the “ name” field values “ Rehan” and “ Ayush”, the value of the “ age” field is the same i.e. Then, using the “ table” and “ dedup” command we are showing the unique combination of values of the “ name” and “ age” fields in tabular form. Here, we are using the “ test_index” index, where we have our sample data. Please see the below query, index=test_index | table name,age | dedup name,age Here, we have used “ | mvcombine name”, As a result, we can see in the above image the “ name” field has become a multivalue field now.įirst, let’s see the data for this example. Please, see the below query, index=test_index | table name | dedup name | mvcombine name Now, if you want this single value field “ name” to appear as a multivalue field, we will use “ mvcombine” command. Then, using the “ table” and “ dedup” commands we are showing the unique values of the “ name” field in tabular form.Īs, you can see in the above image, that “ name” is a single value field. Please, see the below query, index=test_index | table name | dedup name ![]() : The name of a field, from which you want to generate a multivalue field.įirst, we will show you the data on which we will use the “ mvcombine” command. “ mvcombine” command is used to create a multivalue field from a single value field. Today we have come with another new command i.e.
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