Uncheck the Audit this rule option and be sure Enforce radio button is checked. I just put in "Message contains words or phrases that have been identified as profanity and this message has been blocked due to company policy". Enter the text you want the reject email to show to the end user when this rule kicks in. In the Create New Rule window give the rule a name (ProfanityList1, ProfanityList2, etc) then drop down the Apply This Rule If list and choose The Subject Or Body Includes., Put one place holder word in (Profanity1) and then hit ok.ĭrop down Do The Following and choose Reject Message With The Explanation. You have other options, including built in pattern matching rules that you can add to this DLP policy so do explore those when you have time. In this example I clicked Create A New Rule to allow me to create a custom rule. Open the DLP policy you created (edit) then click the rules link on the left and finally click the plus sign drop down to create a new transport rule. Basically you will create a rule for each of the CSV files (150 word list) that you created in step one. In this example I created 5 ProfanityList rules to hold the 150 words each to get me to my total number of blocked rules. Now that the parent rule has been created you can then edit it and create the transport rules that it will monitor. Microsoft does not condone these words and I hope you understand I am only doing this for demonstration purposes to help the community with a task of this nature.ĭownload the file and change the Extension from. If you are offended by bad words please do not use this list and just create your own. With a good sized reject message and average words I settled on 150 words per CSV file that I would import into each rule after creating the shell using the DLP GUI in the portal.ĭisclaimer - I have attached the first of 5 CSV text files for example purposes. Both those added up have to be under this 8192 limit for the rule to apply and update correctly. What I found is that this limit is based on two things in the rule, the words and how long or short they are as well as the reject message text. So the next logical solution was to figure out the average number of words per rule and then break the list up. I tried in vain to get around this limit and have just one big rule for all the keywords, but I was unable to. One of the challenges I hit was after creating the DLP policy rule and then the transport rules underneith I was hitting character size limits for the transport rules (8192). You can adjust the word list as your SOW demands so the idea is the same. I searched the web and found a list of about 450 bad words that I used to prove this solution out.
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