Microsoft SC-200 Practice Test Questions, Exam Dumps

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SC-200 Microsoft Practice Test Questions and Exam Dumps

Question No 1:

You are a security administrator managing Microsoft 365 in your organization. Your goal is to proactively detect suspicious sign-in activity that could indicate a compromised user account. Specifically, you want to receive security alerts when a user attempts to sign in from a geographic location that has never been used by anyone else in your organization for signing in.This can help detect early signs of account compromise, especially from attackers using unfamiliar locations.

Which anomaly detection policy should you configure in Microsoft Entra ID Protection or Microsoft 365 Defender?

A. Impossible travel
B. Activity from anonymous IP addresses
C. Activity from infrequent country
D. Malware detection

Correct Answer: C. Activity from infrequent country

Explanation:

Microsoft Entra ID Protection (formerly Azure AD Identity Protection) and Microsoft 365 Defender offer anomaly detection policies to help identify potential threats based on unusual user behavior.

The "Activity from infrequent country" policy is designed to detect sign-ins that originate from countries where no other users in the organization have previously signed in from. This helps identify potentially malicious activity — for instance, an attacker signing in from a country that doesn't normally interact with your environment. This anomaly is based on the organization's typical location profile, which is built over time.

Let’s compare the options:

Impossible travel detects when a user logs in from two geographically distant locations in a time frame that makes travel between them impossible. It's about improbable login timing, not rare locations.
Activity from anonymous IP addresses triggers on logins from TOR exit nodes or other anonymizing services. It doesn’t consider geographic rarity.
Malware detection is unrelated to sign-ins; it detects known malware threats across Microsoft Defender tools.

Hence, "Activity from infrequent country" is the only policy that fits the requirement of alerting based on a location never used by anyone else in your organization. It’s especially useful in early breach detection scenarios where attackers might be attempting access from foreign regions.

Question No 2 :

Your organization uses Microsoft Defender for Office 365 as part of your Microsoft 365 subscription, and you are managing sensitive data stored on SharePoint Online sites. The sensitive documents on these sites contain customer account numbers, each consisting of 32 alphanumeric characters (e.g., A9F1B7D3C5E8G2H6...).

In this context, you need to implement a Data Loss Prevention (DLP) policy to protect these sensitive documents from unauthorized access or sharing, ensuring that any actions taken with these documents are compliant with your organization's data protection policies.

Which feature should you use to detect which documents are sensitive and contain these account numbers?

A. SharePoint search
B. A hunting query in Microsoft 365 Defender
C. Azure Information Protection
D. RegEx pattern matching

Correct Answer: D. RegEx pattern matching

Explanation:

Overview: In Microsoft 365, Data Loss Prevention (DLP) policies allow you to define rules that prevent the sharing, movement, or accidental leakage of sensitive data. These policies are designed to monitor and protect sensitive information in various Microsoft services, including SharePoint Online, OneDrive, Exchange, and Teams.

In your scenario, you need to detect sensitive documents stored in SharePoint Online that contain customer account numbers in the form of 32 alphanumeric characters. The key challenge here is to accurately identify these specific account numbers in documents that may be stored across SharePoint Online.

Let's break down each option in the context of detecting sensitive data:

A. SharePoint search

SharePoint search is a tool that allows users to search for files, documents, and content across SharePoint libraries. While it helps locate content by keywords, it is not designed to detect sensitive data patterns (such as account numbers) or to enforce DLP policies. SharePoint search doesn’t have the capability to scan documents for specific sensitive information based on data patterns (e.g., a 32-character alphanumeric string).
Limitation: SharePoint search is a basic search tool and doesn’t provide the functionality needed to create data loss prevention policies based on custom data types like customer account numbers.

B. A hunting query in Microsoft 365 Defender

Hunting queries in Microsoft 365 Defender are typically used for threat hunting to investigate and track suspicious activity or potential security incidents across an organization’s environment. While these queries can be effective for analyzing logs, event data, and alerts, they are not designed to detect or classify sensitive data types in documents.
Limitation: Hunting queries are better suited for tracking security incidents such as malware or suspicious user activity, rather than for detecting and classifying sensitive information within documents. It is not the appropriate tool for creating DLP rules focused on sensitive document protection.

C. Azure Information Protection

Azure Information Protection (AIP) is a data classification and protection solution that allows organizations to apply labels to documents and emails to protect sensitive information. While AIP can classify and protect documents (e.g., by applying encryption or rights management), it primarily focuses on manually or automatically labeling content based on predefined categories or classifications.
Limitation: Azure Information Protection is useful for classifying and protecting sensitive documents, but it doesn’t inherently provide detection capabilities based on specific data patterns (such as a 32-character customer account number). While AIP can be used in combination with DLP policies to apply protection to labeled documents, it is not designed to detect specific data types like account numbers.

D. RegEx pattern matching

RegEx (Regular Expressions) pattern matching is a powerful tool used to identify text that matches a specific pattern or format. In the context of Data Loss Prevention (DLP) policies, RegEx can be used to define custom patterns for sensitive information types. In your case, you can use a custom RegEx pattern to detect the specific format of the 32 alphanumeric customer account numbers.

How RegEx works in DLP: With RegEx, you can define a pattern like ^[A-Z0-9]{32}$, which matches strings that are exactly 32 characters long and contain uppercase letters and digits. This pattern can be used within a DLP policy to scan documents for specific sensitive information and trigger actions (like blocking sharing, sending alerts, or encrypting files) when such patterns are found.

Advantage: RegEx pattern matching is the most effective way to identify and protect documents containing specific types of sensitive information, especially when the format is known and can be defined with a pattern (such as customer account numbers). This allows for fine-grained detection and protection, which is crucial for DLP enforcement.

To detect and protect the sensitive customer account numbers in SharePoint Online documents, you should use RegEx pattern matching (D) within your DLP policy. By defining a custom pattern to match the 32 alphanumeric character format, you can ensure that documents containing these numbers are detected, and the appropriate actions are taken to prevent unauthorized access or sharing.

This method allows for targeted, automated identification of sensitive data, which is essential for maintaining compliance with data protection regulations and safeguarding customer information.

Question No 3:

Your organization utilizes Microsoft Defender for Endpoint to protect its devices. The company regularly works with Microsoft Word documents that contain macros, which are often used by the accounting team. However, these macro-enabled documents are generating false positive alerts in the Alerts queue.

You need to configure Microsoft Defender for Endpoint in a way that hides these false positives without compromising the overall security posture of the organization.

Which three actions should you take to hide false positive alerts related to macro usage, while maintaining security?

A. Resolve the alert automatically
B. Hide the alert
C. Create a suppression rule scoped to any device
D. Create a suppression rule scoped to a device group
E. Generate the alert

Correct Answer: B. Hide the alert, C. Create a suppression rule scoped to any device, D. Create a suppression rule scoped to a device group

Explanation:

In Microsoft Defender for Endpoint, managing false positives effectively is essential to ensure that security alerts remain meaningful and actionable without overwhelming security teams. In your scenario, the macro-enabled documents used by the accounting team trigger false positive alerts. The goal is to prevent these alerts from cluttering the Alerts queue while maintaining security.

Let's break down the correct steps:

Hide the alert (B):

Hiding the alert helps ensure that false positives do not appear in the queue anymore, reducing noise. However, hiding an alert doesn't resolve it permanently — it only prevents it from cluttering the list, allowing the security team to focus on more critical alerts.

Create a suppression rule scoped to any device (C):

A suppression rule can be configured to suppress specific types of alerts, such as those related to macros, across any device in the environment. This is useful when you know that certain types of activity (e.g., macros in Word documents) are part of the normal workflow and don’t pose a threat.

Create a suppression rule scoped to a device group (D):

Rather than suppressing alerts for all devices, it might be more efficient to apply a suppression rule to a specific device group, such as the accounting team’s devices. This ensures that only the relevant devices are excluded from generating the false positive alerts, maintaining the effectiveness of alerts on other devices.

Incorrect Options:

Resolve the alert automatically (A): Automatically resolving alerts does not allow for customization of which alerts should be hidden or suppressed. It could lead to missing out on valid alerts that require attention.
Generate the alert (E): This action would simply create more alerts and is not part of a solution to hide false positives.

By applying these steps, you can effectively manage false positives from the accounting team’s use of macros while ensuring the security posture remains intact.

Question No 4:

In Microsoft 365 Defender, you are tasked with configuring an alert for a specific security event. The event you're focusing on is when System Restore is disabled on a device managed by Microsoft Defender. You have an advanced hunting query that helps track such activities, and you want to receive an alert when this event happens in the past 24 hours.

Which two actions should you take to configure this alert correctly using your advanced hunting query?

A. Create a detection rule
B. Create a suppression rule
C. Add | order by Timestamp to the query
D. Replace DeviceProcessEvents with DeviceNetworkEvents
E. Add DeviceId and ReportId to the output of the query

Correct Answer: A. Create a detection rule, C. Add | order by Timestamp to the query

Explanation:

In Microsoft 365 Defender, advanced hunting is a powerful tool for querying device and network events. To configure an alert for when System Restore is disabled, you need to ensure the query is properly structured and that it triggers an alert when the event occurs. Here's why the correct answers are A and C:

Create a detection rule (A):

The detection rule is a critical step to ensure that you’re notified when a relevant event (in this case, disabling System Restore) occurs. While advanced hunting queries help gather the data, a detection rule is necessary to generate alerts from the query results. Detection rules are designed to monitor and trigger alerts on specific activities like the disabling of critical system features (e.g., System Restore) over time, especially within the last 24 hours.

Add | order by Timestamp to the query (C):

Adding | order by Timestamp to the query helps sort the results by the event's timestamp. This is especially useful when you're dealing with large volumes of data, as it ensures that the most recent events are shown first, making it easier to detect any critical changes that have occurred within the last 24 hours. This ensures your query returns only relevant and up-to-date data, improving its efficiency.

Incorrect Options:

Create a suppression rule (B): Suppression rules are used to hide alerts for specific events, not to trigger them. This is not needed if your goal is to generate an alert.
Replace DeviceProcessEvents with DeviceNetworkEvents (D): DeviceProcessEvents is the correct table to query for processes and system-related activities like disabling System Restore. DeviceNetworkEvents focuses on network activities, which is not relevant to this query.
Add DeviceId and ReportId to the output of the query (E): While adding these fields might provide more context, they are not essential for triggering alerts based on the event. The core requirement is creating a detection rule and sorting the results.

By following these steps, you can set up an effective alerting mechanism to monitor and respond to critical system changes within your devices.

Question No 5:

You are investigating a potential attack involving a newly discovered ransomware strain. The affected devices belong to three custom device groups that store highly sensitive information. You plan to perform automated actions on these devices to mitigate the threat.To streamline this process, you need to temporarily group the devices in a way that allows you to perform actions on them collectively.

Which three actions should you take to achieve this goal?

Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Assign a tag to the device group.
B. Add the device users to the admin role.
C. Add a tag to the machines.
D. Create a new device group that has a rank of 1.
E. Create a new admin role.
F. Create a new device group that has a rank of 4.

Correct Answers:

A, C, F

Explanation:

In the scenario described, you are tasked with performing automated actions on devices that belong to custom groups, and you need to temporarily group them for efficient management during the investigation. To achieve this, you must use Microsoft Defender for Endpoint's grouping and tagging features to ensure that the correct devices are targeted for remediation.

Option A (Assign a tag to the device group):
Assigning a tag to the device group helps you label and categorize groups of devices. This makes it easier to filter and perform actions on devices with specific characteristics or locations. Tagging provides a flexible and efficient way to identify and manage groups within the security console.
Option C (Add a tag to the machines):
Similarly, tagging individual devices allows you to group them logically based on attributes like device type, user role, or sensitivity of data stored. This helps ensure that only relevant machines are selected for action. Tags can be applied dynamically or manually, providing flexibility in your investigation.
Option F (Create a new device group that has a rank of 4):
Creating a new device group with a higher rank (rank of 4) helps prioritize these machines for automated actions. In Defender for Endpoint, device groups are ranked to assign priority for handling incidents. A rank of 4 ensures that the group is treated with higher importance, allowing for quick and automated actions to mitigate the ransomware threat.

Why Other Options Are Incorrect:

Option B (Add the device users to the admin role):
This action gives users administrative rights, which is unnecessary for grouping devices for automated actions. It's not relevant to the goal of grouping devices for investigation.
Option D (Create a new device group with rank 1):
A rank of 1 usually means a lower priority, which is counterproductive in urgent attack response scenarios.
Option E (Create a new admin role):
Creating new admin roles is not necessary for simply grouping devices and applying automated actions.

By applying tags and creating appropriately ranked device groups, you can streamline the remediation process while ensuring that sensitive devices are prioritized for protection against the ransomware attack.

Question No 6:

You are configuring Microsoft Defender for Identity integration with Active Directory.
From the Microsoft Defender for Identity portal, you need to configure several accounts to be used for attacker exploitation.From the Entity tags section, you add the accounts as Honeytoken accounts.

Does this solution meet the goal?

A. Yes
B. No

Detailed Answer:

The correct answer is A. Yes.

Explanation:

Microsoft Defender for Identity is a cloud-based security solution that integrates with Active Directory (AD) to help identify and respond to potential security threats and advanced persistent threats (APTs). One of the key strategies for improving security visibility and deception is to use Honeytoken accounts. These are specially designed accounts that serve as "decoys" or "trap" accounts, meant to detect and alert when an attacker interacts with them, as they are not intended for legitimate use.

In this scenario, the goal is to configure several accounts that attackers can exploit, which aligns perfectly with the concept of Honeytoken accounts. Here's a breakdown of why the proposed solution meets the goal:

What are Honeytoken Accounts? Honeytoken accounts are special, fictitious accounts set up within an environment that have no legitimate user or role. These accounts are designed specifically to lure attackers. When attackers attempt to interact with these accounts (for example, by trying to log in, access resources, or use them in any way), it triggers alerts within security systems, revealing malicious activity. Essentially, they are used as a detection mechanism to flag unauthorized actions that would otherwise go unnoticed.
How does Microsoft Defender for Identity work with Honeytoken Accounts? In Microsoft Defender for Identity, administrators can configure Entity Tags to label various accounts within the environment. This allows the system to track these accounts for unusual behavior. When setting up Honeytoken accounts, these accounts are tagged appropriately within Defender for Identity so that any interaction with them will generate alerts. If an attacker tries to use one of these Honeytoken accounts to gain unauthorized access, Defender for Identity will recognize this as suspicious and trigger an alert.
Defender for Identity’s Role in Detecting Attacks By adding accounts as Honeytokens in the Entity Tags section, you are effectively configuring your system to detect unauthorized access or attack attempts on accounts that are not supposed to be used under any normal circumstances. Microsoft Defender for Identity can then monitor these accounts for any abnormal actions, helping security teams quickly identify if an attacker is attempting to exploit or gain access through these decoy accounts.
The Solution’s Effectiveness The solution mentioned in the question — adding accounts as Honeytoken accounts from the Entity tags section — directly supports the goal of setting up accounts that attackers can exploit, but in a controlled manner that alerts defenders to suspicious activity. This method is a proactive approach in defending against advanced threats, as attackers will often target accounts to gain privilege escalation, lateral movement, or access to sensitive information.
Why This Meets the Goal By tagging certain accounts as Honeytokens within the Microsoft Defender for Identity portal, you're ensuring that these accounts will act as traps. When an attacker interacts with these accounts, the system will immediately generate an alert, thereby helping security teams identify the attacker and stop the attack before it causes significant damage. This method is aligned with the goal of configuring accounts for exploitation in a way that leads to detection and response.

The solution provided meets the goal of configuring accounts that attackers could potentially exploit by leveraging Honeytoken accounts. This method allows you to set up accounts as decoys that can trigger alerts when interacted with by attackers, enabling effective detection of malicious activity. Therefore, the correct answer is A. Yes.