Microsoft SC-401 Administering Information Security in Microsoft 365 Exam Practice Test

The requirement states that all Microsoft 365 data for users must be retained for at least one year. In Microsoft 365, retention policies must be configured for each type of data storage.

Step 1: Identifying Where Data is Stored

From the case study, users store data in the following locations:

● SharePoint Online sites

● OneDrive accounts

● Exchange email

● Exchange public folders

● Teams chats

● Teams channel messages

Since these locations fall under two broad categories:

● Microsoft Exchange data (Emails, Public folders)

● SharePoint, OneDrive, and Teams data

Step 2: Required Retention Policies

1️. A single retention policy can cover:

● SharePoint Online

● OneDrive

● Microsoft Teams

2. A second retention policy is required for:

● Exchange (Emails & Public Folders)

Thus, the minimum number of retention policies required to meet the requirement is 2.

Microsoft 365 retention policies can be applied broadly across multiple services with just two policies:

● One for Exchange & Public Folders

● One for SharePoint, OneDrive, and Teams

There's no need for separate policies for each individual workload unless different retention durations are required, which is not stated in the requirement.

To meet the requirement that all administrative users must be able to create Microsoft 365 sensitivity labels, we need to assign the Sensitivity Label Administrator role to the correct users.

Sensitivity Label Administrator Role Responsibilities

This role allows users to:

● Create and manage sensitivity labels in Microsoft Purview.

● Publish and configure auto-labeling policies.

● Modify label encryption and content marking settings.

Review of Admin Roles from the Table:

A screenshot of a computer AI-generated content may be incorrect.

Users that must be assigned the Sensitivity Label Administrator role:

● Admin2 (Compliance Data Administrator)

● Admin3 (Compliance Administrator)

● Admin1 (Global Reader) (should be assigned this role to fulfill the requirement that all admins can create labels).

A screenshot of a computer AI-generated content may be incorrect.

To detect and protect confidential documents, we need a custom rule to identify project codes that start with 999 (since they are classified as confidential).

Box 1: A Sensitive Info Type (SIT) allows Microsoft Purview DLP policies to recognize structured data (e.g., project codes). DLP policies require a sensitive info type to detect content based on patterns, keywords, or dictionary terms. A sensitivity label alone does not define detection logic—it is used for classification and protection after content is identified.

Box 2: Since project codes follow a structured 10-digit pattern, we should use a Regular Expression (Regex) to match project codes that start with 999.

Example Regex pattern:

999\d{7}

This pattern detects a 10-digit number starting with "999".

A white paper with black text AI-generated content may be incorrect.

Understanding Site4's Retention Policies:

● Site4RetentionPolicy1 deletes items older than 2 years from creation. If a file was created on January 1, 2021, it would be deleted after January 1, 2023.

● Site4RetentionPolicy2 retains files for 4 years from creation. If a file was created on January 1, 2021, it will be kept until January 1, 2025, but not deleted after that (policy states "Do nothing").

Statement 1 - Yes, because Site4RetentionPolicy2 ensures files are retained for 4 years.

Statement 2 - Yes, because Site4RetentionPolicy2 retains the file for 4 years (until January 1, 2025).

Statement 3 - No, because retention is only for 4 years (until January 1, 2025). After that, the policy does "nothing," meaning the file is no longer recoverable after that period.

A screenshot of a computer AI-generated content may be incorrect.

Understanding DLP Policy Impact on File Access

The DLP policy (DLPpolicy1) applies to Site2 and restricts access when:

● Content contains SWIFT Codes.

● Instance count is 2 or more.

File Analysis (Based on SWIFT Codes Count)

A screenshot of a computer AI-generated content may be incorrect.

Files that remain accessible (not restricted by DLP):

● File1.docx (Contains only 1 SWIFT Code → Below restriction threshold)

User access after DLP policy is applied:

A screenshot of a computer AI-generated content may be incorrect.

User1 (Site Owner):

● Has higher privileges and can override DLP restrictions (through admin intervention).

● Can access 2 files (File1.docx + override access to another file).

User2 (Site Visitor):

● Has read-only access but DLP blocks access to restricted files.

● Can only access 1 file (File1.docx), since all others are restricted.

A screenshot of a questionnaire AI-generated content may be incorrect.

The goal is to automatically label documents in Site1 that contain credit card numbers. To achieve this, we need a sensitivity label with an auto-labeling policy based on a sensitive info type that detects credit card numbers.

Step 1: Create a Sensitive Info Type

● A sensitive info type is needed to detect credit card numbers in documents.

● Microsoft Purview includes built-in sensitive info types for credit card numbers, but we can also create a custom one if necessary.

Step 2: Create a Sensitivity Label

● A sensitivity label is required to classify and protect documents containing sensitive information.

● This label can apply encryption, watermarking, or access controls to credit card data.

Step 3: Create an Auto-Labeling Policy

● An auto-labeling policy ensures that the sensitivity label is applied automatically when credit card numbers are detected in Site1.

● This policy is configured to scan files and automatically apply the correct sensitivity label.

Box 1: Since you are looking for a specific pattern (PA followed by eight digits, e.g., PA 12345678), the best classification method is Sensitive Info Type. Sensitive Info Types allow pattern-based matching to identify structured data. Exact Data Match (EDM) is not needed because you're not comparing against a fixed dataset. Trainable classifier is not appropriate because this is a structured pattern, not an unstructured document classification.

Box 2: Since PA 12345678 follows a structured pattern, the most effective method is Regular Expression (Regex). A Regular Expression (Regex) can be written to match "PA" followed by exactly eight digits (e.g., PA\s\d{8}). Keyword dictionary is not ideal because it works for predefined words, not number patterns. Function is unnecessary because there is no need for checksum validation or predefined validation rules.

To ensure User1 can perform insider risk management tasks only for the users and devices in Office1, the first step is to create an administrative unit in Microsoft Entra ID (formerly Azure AD).

Administrative units allow you to scope permissions to specific users, devices, and locations. By creating an administrative unit for Office1 and assigning User1 to the Insider Risk Management Admins role group within that unit, User1 will only have access to users and devices in Office1.

When implementing Microsoft Purview Insider Risk Management and using the HR data connector, you must prepare HR data in CSV (Comma-Separated Values) format. This format is required because Microsoft Purview supports CSV files for importing user employment details, termination dates, role changes, and other HR-related attributes.