Manage and respond to data loss prevention policy violations
When a DLP policy alert informs you about a DLP policy violation, it can mean many things. Not all alerts mean that data loss is imminent or was prevented. DLP policies will not make decisions about the reason for attempting to share protected data, but they will alert you if a violation is observed. Reacting to policy violations can include escalating issues to your security team and working closely with other business stakeholders. You should know the process for contacting other teams and security before it is necessary.
For example, you protect financial information in your organization to prevent sharing of customer data with third parties but at the end of the first month you get alerts about rule violations on your financial information policy. Reviewing the reports shows a high number of e-mails from the accounting department including billing information for your customers. The policy reacted to the sensitive customer information without taking context into account. A compliance administrators' role is to assess and evaluate policy violations and act accordingly. In this instance, you should accept that the end of the month information will trigger alerts because it correctly identifies protected data and informs you about this fact. You might want to adjust the instance count of the policy to reduce the number of alerts, but this could have negative effects on the policy at other times of the month.
Now consider that you later created a personal data policy that displays an alert spike around the same time at the end of each month as the financial information policy. Looking at the new spike in your personal data policy shows you the violation happens on the same items as the financial information policy. You decide to take a closer look at the billing documents and notice that they include personal identifiable information beyond what is immediately necessary for billing documents. In this case, you should not adjust the policies to avoid triggering at the end of the month. Instead, you should reach out to the responsible party and identify if this information is needed in the current business process and if not, why it is created in the first place.
A technical solution to this problem would be to allow the accounting department to override the block action of the personal data policy but this will increase the time they need to send out billing information because they would need to override each policy match. If you cannot work with the accounting department on reducing the amount of shared personal data you can still adjust the sensitivity, instance count, or exclusions of your policy to reduce the number of alerts at the end of each month.
DLP reports can also help you identify users who create a high number of matches. There may be multiple reasons and your role as a compliance administrator is to evaluate if the matches are benign or malevolent. For example, a user in the accounting department might generate a high number of matches at the end of each month because of the financial information policy and the monthly business process of sending out billing information. This is most likely benign, but you should take a closer look at all occurrences of a high alert count. Users who are aware of these policies, because of policy tips or because they have worked with you on creating them, might use that knowledge to share information they should not share. If a malevolent user decides to send out financial information, they could use the end of the month to hide the malevolent mails in between the legitimate mails from your business process.
You can also use the reports to allow your users to help you with refining the DLP policies. For this, you can use the DLP false reports and overrides report. If you allow users, the ability to override using a business justification they not only hold themselves accountable by choosing the override, but they also allow you to review the reason and identify business processes that warrant an adjustment to your policy or the business process itself.
For example, you open the false positives and overrides report and notice a high number of false positives on your Tax Identification Number policy. Opening the details of these false positives you see that your internal product numbers look like European tax identification numbers, which result in users reporting these matches as false positives.
Configure DLP rule exclusions
You decide to adjust the Tax identification number DLP policy to exclude instances where it matches your custom sensitive information type for Product Number. To do this, follow these steps:
In the M365 compliance center, on the Policies page, expand Data and select Data loss prevention.
Check the Tax identification number policy and select Edit Policy.
Select Next twice to get to the rules page and edit the rule that creates numerous false positives.
Expand Exceptions and select Add Exception.
From the dropdown menu, select Except if content contains.
Select Add and select sensitive info types.
From the pop-up select the custom product number info type and select Add.
Select Next twice, review the policy and select submit.
This will reduce the number of false positives of your policy because now it won't apply when it identifies product numbers in your users shared content.
If a malevolent user is aware of the matching indicators, they can use them to create a match on the product numbers exclusion and circumvent the protective actions of this rule by purposefully including a matching exclusion.