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

Current setup:

DLP1 (priority 0, Rule1) → Stop processing additional rules enabled → means if Rule1 matches, later rules (including Rule2 with Tip2) will never be evaluated.

Requirement: Ensure that if all rules match, the user sees Tip2 (Rule2’s policy tip).

To fix this: Move DLP2 above DLP1 in priority (i.e., set DLP2 = priority 0). Then Rule2 will be evaluated first, and its policy tip (Tip2) will be displayed.

Why not others?

B. Prevent additional processing of the policies if there is a match for Rule2: That would stop processing later, but DLP1 would still block earlier due to its higher priority.

C. Change the priority of DLP2 to 3: That pushes it even lower, making it worse.

D. Enable additional processing for Rule1: Rule1 already has stop processing enabled. Changing that does not ensure Rule2 runs before Rule1, because priority is evaluated first.

Step 1 – Scenario

You need to create a Microsoft Purview Insider Risk Management policy that detects data theft from SharePoint Online by users who have submitted their resignation or are close to termination.

Step 2 – Understanding how insider risk management works

Insider Risk policies rely on signals that identify potential risk events. These signals include:

HR data (resignation dates, termination notices).

Office activity indicators (file downloads, sharing, printing).

Device indicators (file copy to USB, printing).

Physical access (badge-in/badge-out).

Step 3 – Why HR signals are required here

To detect resignation or termination risk events, Microsoft Purview must first know which users are flagged by HR.

This is done by configuring an HR data connector, which imports employee termination/resignation data from HR systems (Workday, SAP SuccessFactors, or CSV import).

Without this HR data connector, Purview has no knowledge of employees’ resignation or termination timelines, and the policy cannot function.

Step 4 – Why not the other options

B. Configure Office indicators: These detect risky activity (downloads, sharing), but cannot determine resignation status. They are used after HR signals identify at-risk users.

C. Configure a Physical badging connector: Useful for detecting anomalous physical access, but irrelevant to resignation-based detection.

D. Onboard devices to Microsoft Defender for Endpoint: Required for device activity signals, not for HR resignation detection.

Step 5 – Microsoft Reference

Microsoft documentation states: “To use HR resignation/termination triggers, you must configure an HR connector to import resignation and termination data into insider risk management.”

Trainable classifiers in Microsoft Purview require a source of documents that can be labeled as examples of what the classifier should recognize. Supported sources include SharePoint Online and Exchange Online mailboxes. On-premises SharePoint Server sites, Azure File shares, and NFS file shares are not supported for classifier training.

To create a trainable classifier that can be used in an auto-apply retention label policy, you need to follow these key steps:

1. Create the trainable classifier

This is the first step where you define the classifier, specifying the types of content it should identify.

2. Test the trainable classifier

Before using the classifier in production, you need to validate its accuracy by testing it against sample documents to ensure it correctly classifies the intended data.

3. Publish the trainable classifier

Once testing is successful, you must publish the classifier so that it can be used in policies like auto-apply retention labels in Microsoft Purview.

Microsoft Purview Insider Risk Management flags high-impact users based on various risk factors, including role, access to confidential data, and influence within an organization. Let ' s analyze each user:

User1 (Regional Manager, assigned Reader role, manages department managers)

Risk Factors:

● Holds a managerial position (regional manager).

● Manages multiple department managers, indicating organizational influence.

● Access to critical business information.

Flagged? -Yes (Managerial role and access to confidential data).

User2 (HR department manager, no Microsoft Entra roles, manages HR department users)

Risk Factors:

● Manages HR department users, meaning they likely handle sensitive employee data.

● HR roles are often considered high-risk due to access to personal and payroll data.

Flagged? -Yes (HR role and access to sensitive employee data).

User3 (Developer, reports to User2, only user in compliance, assigned Compliance Administrator role)

Risk Factors:

● Compliance Administrator role grants access to sensitive security and regulatory data.

● Only person in the compliance department, meaning they hold a critical role.

● Potentially high impact on compliance and security settings.

Flagged? -Yes (Privileged Compliance Administrator role).

User4 (Assistant to User1, no Entra roles, handles confidential data on behalf of User1)

Risk Factors:

● Handles a high volume of confidential data on behalf of a regional manager.

● Assistants with access to sensitive data are considered insider risk candidates.

Flagged? -Yes (High access to sensitive information).

Since all four users fit high-impact criteria (managerial roles, privileged compliance access, handling sensitive data), Microsoft Purview Insider Risk Management will flag all of them.

for each of the following you can have a retention policy

1.EXO, SPO, ODfB, M365 groups

2.Teams channel messages, teams chat

3.Teams private channel messages

The Set-AdminAuditLogConfig -AdminAuditLogEnabled $true -AdminAuditLogCmdlets *Mailbox* command is incorrect. This enables admin audit logging, which tracks changes to mailbox configurations (e.g., mailbox settings updates), not user activity inside the mailbox.

To track who accesses User1’s mailbox, you need to enable mailbox auditing for User1. By default, Exchange mailbox auditing is not enabled per mailbox (even though it is enabled tenant-wide).

The Set-Mailbox -Identity " User1 " -AuditEnabled $true command enables audit logging for mailbox actions like:

● Read emails

● Delete emails

● Send emails as User1

● Access by delegated users

Once enabled, you can search for future sign-ins and actions in the Microsoft Purview audit logs.

Forensic evidence in Microsoft Purview Insider Risk Management allows capturing screenshots/clips of user activity on endpoints.

Requirements for forensic evidence capture:

The device must be onboarded to Microsoft Purview (via Defender for Endpoint).

The Microsoft Purview client must be installed.

Supported platforms: Windows 10 and Windows 11 (macOS is not supported for forensic evidence).

Now check each device:

Device1 (Windows 11) → Client installed, but not onboarded → ❌ Not eligible.

Device2 (Windows 10) → Onboarded and client installed → ✅ Eligible.

Device3 (macOS) → Onboarded, but client not installed and macOS is not supported → ❌ Not eligible.

Therefore, only Device2 qualifies.

To implement Microsoft Purview Data Lifecycle Management for SharePoint Online (Site1), you need to create a retention label first. Retention labels define how long content should be retained or deleted based on compliance requirements. Once a retention label is created, it can be manually or automatically applied to content in SharePoint Online, Exchange, OneDrive, and Teams. After creating a retention label, you can configure label policies to apply them to Site1 and other locations.

To track interactions between users and generative AI websites in Microsoft Purview Audit, you need to deploy the Microsoft Purview browser extension to the devices. This extension enables tracking of user activities on web-based applications, including AI-related tools like ChatGPT, Microsoft Copilot, and other generative AI platforms.

Microsoft Purview extension provides visibility into browser-based activities, including AI tool usage, ensuring compliance and risk management within Microsoft Purview. This extension works with Microsoft Edge and Google Chrome to track and log user interactions.

Step 1 – Understanding the requirement

You want to retain specific audit log record types and activities for 3 years:

CopilotInteraction → All activities (1/1)

Compliance DLP endpoint → All activities (2/2)

Azure Active Directory → Only 2 out of 25 activities selected (Reset user password, Changed user password)

The goal is to minimize the number of audit retention policies while meeting the requirement to store only the selected record types and activities.

Step 2 – Audit retention policies in Microsoft Purview

Audit retention policies let you define which activities and record types are retained and for how long.

A single retention policy can include multiple record types and multiple activities.

Limitation: Each policy can only define one set of retention settings per included record types/activities.

If you want to retain different subsets of activities (e.g., only 2 out of 25 in Azure AD), you must create a separate policy for that.

???? Reference: Set up audit (Premium) retention policies in Microsoft Purview

Step 3 – Applying to the scenario

CopilotInteraction: Since you need all activities, you can include them in one policy.

Compliance DLP endpoint: Since you also need all activities, they can be added to the same policy as CopilotInteraction.

✅ These two can be covered by 1 policy.

Azure Active Directory: You only need 2 out of 25 activities. Since this requires activity-level filtering, it must be placed in a separate policy.

Thus:

Policy 1 → CopilotInteraction (all) + Compliance DLP endpoint (all)

Policy 2 → Azure AD “Reset user password”

Policy 3 → Azure AD “Changed user password”

That equals 3 total policies.

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.

Comprehensive Detailed Explanation with References

When multiple advanced DLP rules match content, Microsoft 365 DLP evaluates based on:

Rule priority

Lower number = higher priority (0 highest).

Among Rule2 (priority 1), Rule3 (priority 2), and Rule4 (priority 3), Rule2 has the highest priority.

Conflict resolution (single vs multiple rules applied)

By default, only the highest-priority rule applies if multiple rules match. → That’s why in the first dropdown, the correct answer is Only Rule2 takes effect.

However, you can configure advanced DLP to allow multiple matching rules to take effect simultaneously. If this setting is enabled, then Rule2, Rule3, and Rule4 all apply. → That’s why in the second dropdown, the correct answer is Rule2, Rule3, and Rule4 take effect.

Step 1 – Requirement

The scenario requires using Microsoft Purview Insider Risk Management to import HR data (such as employee hire dates, resignations, and department changes). HR data connectors allow insider risk policies to use workforce signals to detect risky user activities.

Step 2 – What to do first

Before importing HR data, you must configure Insider Risk Management settings in the Microsoft Purview compliance portal. This is a prerequisite step that enables HR data connectors and policies to be created.

Step 1 – Requirement

We need a custom sensitive information type (SIT) that detects:

An employee ID number in a specific format → hire date + three digits.

This is a pattern-based requirement.

Specific keywords within 300 characters of that ID → “Employee”, “ID”, or “Identification”.

This is a keyword proximity requirement.

Step 2 – Sensitive info type elements in Microsoft 365

When creating custom SITs, you define primary and secondary elements:

Primary element → The main pattern or data to detect (the most defining factor).

Secondary element → Supporting evidence that must be found near the primary element to increase confidence.

Available elements:

Regular expression → Used to define patterns such as date + digits (for employee ID).

Keyword list → Used for lists of words/phrases like " Employee " , " ID " , " Identification " .

Functions → Used for built-in validators like credit card checksum, not relevant here.

???? Reference: Create a custom sensitive information type in Microsoft 365

Step 3 – Apply to scenario

Employee ID pattern (hire date + 3 digits) → Needs a regular expression → This must be the Primary element.

Keywords (“Employee”, “ID”, “Identification”) within 300 characters → A keyword list → This must be the Secondary element.

Information protection scanner: Scans on-premises data, unrelated to forensic evidence.

Claim capacity: Required to enable forensic evidence collection in Insider Risk Management because forensic evidence consumes special storage (capacity units).

Adaptive Protection: Assigns policies dynamically, unrelated to forensic evidence.

Priority user groups: Helps scope users but not the prerequisite step for forensic capture.

You need to prevent users from sharing sensitive information with third-party generative AI websites.

A. Information Protection → Classifies and labels data but does not block sharing with external AI sites.

B. Information Barriers → Restricts communication between groups of users (e.g., compliance walls), not web uploads.

C. Insider Risk Management → Detects risky behavior (like data exfiltration), but does not actively block data sharing.

D. Data Loss Prevention (DLP) → Detects and prevents sensitive data being copied to browsers, USBs, or uploaded to restricted domains (like ChatGPT, Bard, etc.).

Step 1 – Understanding the scenario

The screenshot shows multiple Sensitive Information Types (SITs) in Microsoft Purview, including:

ABA Routing Number (Microsoft-built)

ASP.NET Machine Key (Microsoft-built)

Adatum document patterns (custom, Fingerprint type)

Adatum numbers (custom, Entity type)

Bundled SITs (like All Credential Types, All Full Names)

The question is asking:

Which SITs can you copy to create a new SIT?

Which SITs can you edit directly without copying?

Step 2 – Microsoft rules for SITs

Built-in SITs (published by Microsoft Corporation):

These cannot be edited directly. To modify them, you must create a copy first.

Custom SITs (created in your tenant, e.g., Contoso):

These can be edited directly without making a copy.

Step 1 – Label publishing and scope

The sensitivity label Label1 is published to User1 and Group1.

User1 → Directly included in label publishing.

User2 → Member of Group1, so also included indirectly.

This means both User1 and User2 are eligible to use Label1.

Step 2 – File vs Folder labeling with the Information Protection client

The Microsoft Purview Information Protection (AIP unified labeling) client can apply labels to files such as .docx, .png, .pdf, etc.

It cannot label folders directly. Labels are applied to items (files and emails), not folders.

When you create a communication compliance policy in Microsoft Purview and select " Detect Microsoft Copilot interactions, " certain trainable classifiers are automatically added to help detect sensitive or inappropriate AI usage.

The " Unauthorized disclosure " classifier helps detect cases where users might share confidential or sensitive information via Copilot interactions, preventing unintended data leaks. The " Protected Materials " classifier is used to identify sensitive or restricted content that should not be shared through Copilot, ensuring compliance with organizational policies.

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 " .

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:

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).

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.

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.

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.

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)

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:

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.