Palo Alto Networks XDR-Engineer試験準備、XDR-Engineer学習体験談

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Palo Alto Networks XDR-Engineer 認定試験の出題範囲：

トピック	出題範囲
トピック 1	メンテナンスとトラブルシューティング：この試験セクションでは、XDRエンジニアのスキルを評価し、コンテンツ、エージェント、コレクター、ブローカーVMなどのCortex XDRソフトウェアコンポーネントのアップデート管理を網羅します。また、データの取り込みや解析といったデータ管理の問題のトラブルシューティング、そしてシステムの信頼性とパフォーマンスを継続的に確保するためのCortex XDRコンポーネントの問題解決も含まれます。
トピック 2	検出とレポート：このセクションでは、検出エンジニアのスキルを評価します。セキュリティ要件を満たす検出ルールの作成（相関分析、カスタム防御ルール、行動指標（BIOC）と侵害指標（IOC）の活用など）を網羅します。また、例外と除外の設定、効果的な脅威検出とレポートのためのカスタムダッシュボードとレポートテンプレートの構築も評価します。
トピック 3	取り込みと自動化：このセクションでは、セキュリティエンジニアのスキルを評価し、NGFW、ネットワーク、クラウド、IDシステムなど、様々なデータソースのオンボーディングを網羅します。また、シンプルな自動化ルールの管理、Broker VMアプレットとクラスターの設定、XDRコレクターの設定、Cortex XDR環境内でのデータ正規化と自動化のための解析ルールの作成も含まれます。
トピック 4	Cortex XDRエージェント構成：このセクションでは、XDRエンジニアのスキルを評価します。エンドポイント防御プロファイルとポリシーの構成、エンドポイント拡張プロファイルの設定、エンドポイントグループの管理について扱います。エンドポイントが適切に保護され、ポリシーが組織全体に一貫して適用されるようにすることに重点が置かれます。
トピック 5	計画とインストール：このセクションでは、セキュリティエンジニアのスキルを評価し、Cortex XDRの導入プロセス、目標、ハードウェア、ソフトウェア、データソース、統合などの必要なリソースについて学習します。また、XDRエージェント、Broker VM、XDR Collector、Cloud Identity Engineなどのコンポーネントの導入と機能に関する理解と説明も含まれます。さらに、ユーザーロール、権限、アクセス制御を構成する能力、データ保持とコンピューティングユニットに関する考慮事項に関する知識も評価されます。

>> Palo Alto Networks XDR-Engineer試験準備 <<

XDR-Engineer学習体験談、XDR-Engineer関連資格知識

Palo Alto Networks試験問題は専門家によって編集され、認定された担当者によって承認され、さまざまな機能を強化するため、XDR-Engineerテストトレントを便利かつ効率的に学習できます。購入前に無料ダウンロードと試用を提供しています。 XDR-Engineer試験の問題では、学生がシミュレーション問題を提供するプラットフォームで20〜30時間練習する必要があり、Palo Alto Networks XDR EngineerのXDR-Engineer試験に合格する自信を持たせることができます。 XDR-Engineer試験に合格して目標を達成するための最良のツールでなければなりません。

Palo Alto Networks XDR Engineer 認定 XDR-Engineer 試験問題 (Q37-Q42):

質問 # 37
An engineer wants to automate the handling of alerts in Cortex XDR and defines several automation rules with different actions to be triggered based on specific alert conditions. Some alerts do not trigger the automation rules as expected. Which statement explains why the automation rules might not apply to certain alerts?

A. They are executed in sequential order, so alerts may not trigger the correct actions if the rules are not configured properly
B. They only apply to new alerts grouped into incidents by the system and only alerts that generateincidents trigger automation actions
C. They can be applied to any alert, but they only work if the alert is manually grouped into an incident by the analyst
D. They can only be triggered by alerts with high severity; alerts with low or informational severity will not trigger the automation rules

正解：A

解説：
In Cortex XDR,automation rules(also known as response actions or playbooks) are used to automate alert handling based on specific conditions, such as alert type, severity, or source. These rules are executed in a defined order, and the first rule that matches an alert's conditions triggers its associated actions. If automation rules are not triggering as expected, the issue often lies in their configuration or execution order.
* Correct Answer Analysis (A):Automation rules areexecuted in sequential order, and each alert is evaluated against the rules in the order they are defined. If the rules are not configured properly (e.g., overly broad conditions in an earlier rule or incorrect prioritization), an alert may match an earlier rule and trigger its actions instead of the intended rule, or it may not match any rule due to misconfigured conditions. This explains why some alerts do not trigger the expected automation rules.
* Why not the other options?
* B. They only apply to new alerts grouped into incidents by the system and only alerts that generate incidents trigger automation actions: Automation rules can apply to both standalone alerts and those grouped into incidents. They are not limited to incident-related alerts.
* C. They can only be triggered by alerts with high severity; alerts with low or informational severity will not trigger the automation rules: Automation rules can be configured to trigger based on any severity level (high, medium, low, or informational), so this is not a restriction.
* D. They can be applied to any alert, but they only work if the alert is manually grouped into an incident by the analyst: Automation rules do not require manual incident grouping; they can apply to any alert based on defined conditions, regardless of incident status.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains automation rules: "Automation rules are executed in sequential order, and the first rule matching an alert's conditions triggers its actions. Misconfigured rules or incorrect ordering can prevent expected actions from being applied" (paraphrased from the Automation Rules section). TheEDU-262: Cortex XDR Investigation and Responsecourse covers automation, stating that
"sequential execution of automation rules requires careful configuration to ensure the correct actions are triggered" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheet includes "playbook creation and automation" as a key exam topic, encompassing automation rule configuration.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-262: Cortex XDR Investigation and Response Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

質問 # 38
How are dynamic endpoint groups created and managed in Cortex XDR?

A. Endpoint groups require intervention to update the group with new endpoints when a new device is added to the network
B. Each endpoint can belong to multiple groups simultaneously, allowing different security policies to be applied to the same device at the same time
C. After an endpoint group is created, its assigned security policy cannot be changed without deleting and recreating the group
D. Endpoint groups are defined based on fields such as OS type, OS version, and network segment

正解：D

解説：
In Cortex XDR,dynamic endpoint groupsare used to organize endpoints for applying security policies, managing configurations, and streamlining operations. These groups are defined based on dynamic criteria, such asOS type,OS version,network segment,hostname, or other endpoint attributes. When a new endpoint is added to the network, it is automatically assigned to the appropriate group(s) based on these criteria, without manual intervention. This dynamic assignment ensures that security policies are consistently applied to endpoints matching the group's conditions.
* Correct Answer Analysis (D):The optionDaccurately describes how dynamic endpoint groups are created and managed. Administrators define groups using filters based on endpoint attributes like operating system (e.g., Windows, macOS, Linux), OS version (e.g., Windows 10 21H2), or network segment (e.g., subnet or domain). These filters are evaluated dynamically, so endpoints are automatically added or removed from groups as their attributes change or new devices are onboarded.
* Why not the other options?
* A. Endpoint groups require intervention to update the group with new endpoints when a new device is added to the network: This is incorrect because dynamic endpoint groups are designed to automatically include new endpoints that match the group's criteria, without manual intervention.
* B. Each endpoint can belong to multiple groups simultaneously, allowing different security policies to be applied to the same device at the same time: This is incorrect because, in Cortex XDR, an endpoint is assigned to a single endpoint group for policy application to avoid conflicts.
While endpoints can match multiple group criteria, the system uses a priority or hierarchy to assign the endpoint to onegroup for policy enforcement.
* C. After an endpoint group is created, its assigned security policy cannot be changed without deleting and recreating the group: This is incorrect because Cortex XDR allows administrators to modify the security policy assigned to an endpoint group without deleting and recreating the group.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains endpoint group management: "Dynamic endpoint groups are created by defining filters based on endpoint attributes such as OS type, version, or network segment.
Endpoints are automatically assigned to groups based on these criteria" (paraphrased from the Endpoint Management section). TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers endpoint group configuration, stating that "groups are dynamically updated as endpoints join or leave the network based on defined attributes" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "endpoint management and policy configuration" as a key exam topic, which encompasses dynamic endpoint groups.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-260: Cortex XDR Prevention and Deployment Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

質問 # 39
A correlation rule is created to detect potential insider threats by correlating user login events from one dataset with file access events from another dataset. The rule must retain all user login events, even if there are no matching file access events, to ensure no login activity is missed.
text
Copy
dataset = x
| join (dataset = y)
Which type of join is required to maintain all records from dataset x, even if there are no matching events from dataset y?

A. Left
B. Outer
C. Right
D. Inner

正解：A

解説：
In Cortex XDR, correlation rules useXQL (XDR Query Language)to combine data from multiple datasets to detect patterns, such as insider threats. Thejoinoperation in XQL is used to correlate events from two datasets based on a common field (e.g., user ID). The type of join determines how records are matched and retained when there are no corresponding events in one of the datasets.
The question specifies that the correlation rule must retainall user login eventsfrom dataset x (the primary dataset containing login events), even if there are no matching file access events in dataset y (the secondary dataset). This requirement aligns with aLeft Join(also called Left Outer Join), which includes all records from the left dataset (dataset x) and any matching records from the right dataset (dataset y). If there is no match in dataset y, the result includes null values for dataset y's fields, ensuring no login events are excluded.
* Correct Answer Analysis (B):ALeft Joinensures that all records from dataset x (user login events) are retained, regardless of whether there are matching file access events in dataset y. This meets the requirement to ensure no login activity is missed.
* Why not the other options?
* A. Inner: An Inner Join only includes records where there is a match in both datasets (x and y).
This would exclude login events from dataset x that have no corresponding file access events in dataset y, which violates the requirement.
* C. Right: A Right Join includes all records from dataset y (file access events) and only matching records from dataset x. This would prioritize file access events, potentially excluding login events with no matches, which is not desired.
* D. Outer: A Full Outer Join includes all records from both datasets, with nulls in places where there is no match. While this retains all login events, it also includes unmatched file access events from dataset y, which is unnecessary for the stated requirement of focusing on login events.
Exact Extract or Reference:
TheCortex XDR Documentation Portalin theXQL Reference Guideexplains join operations: "A Left Join returns all records from the left dataset and matching records from the right dataset. If there is no match, null values are returned for the right dataset's fields" (paraphrased from the XQL Join section). TheEDU-262:
Cortex XDR Investigation and Responsecourse covers correlation rules and XQL, noting that "Left Joins are used in correlation rules to ensure all events from the primary dataset are retained, even without matches in the secondary dataset" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetlists "detection engineering" as a key exam topic, including creating correlation rules with XQL.
References:
Palo Alto Networks Cortex XDR Documentation Portal: XQL Reference Guide (https://docs-cortex.
paloaltonetworks.com/)
EDU-262: Cortex XDR Investigation and Response Course Objectives
Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

質問 # 40
A Custom Prevention rule that was determined to be a false positive alert needs to be tuned. The behavior was determined to be authorized and expected on the affected endpoint. Based on the image below, which two steps could be taken? (Choose two.)
[Image description: A Custom Prevention rule configuration, assumed to trigger a Behavioral Indicator of Compromise (BIOC) alert for authorized behavior]

A. Modify the behavioral indicator of compromise (BIOC) logic
B. Apply an alert exclusion to the XDR agent alert
C. Apply an alert exclusion to the XDR behavioral indicator of compromise (BIOC) alert
D. Apply an alert exception

正解：C、D

解説：
In Cortex XDR, aCustom Prevention ruleoften leveragesBehavioral Indicators of Compromise (BIOCs)to detect specific patterns or behaviors on endpoints. When a rule generates a false positive alert for authorized and expected behavior, tuning is required to prevent future false alerts. The question assumes the alert is related to a BIOC triggered by the Custom Prevention rule, and the goal is to suppress or refine the alert without disrupting security.
* Correct Answer Analysis (A, B):
* A. Apply an alert exception: Analert exceptioncan be created in Cortex XDR to suppress alerts for specific conditions, such as a particular endpoint, user, or behavior. This is a quick way to prevent false positive alerts for authorized behavior without modifying the underlying rule, ensuring the behavior is ignored in future detections.
* B. Apply an alert exclusion to the XDR behavioral indicator of compromise (BIOC) alert:
Analert exclusionspecifically targets BIOC alerts, allowing administrators to exclude certain BIOCs from triggering alerts on specific endpoints or under specific conditions. This is an effective way to tune the Custom Prevention rule by suppressing the BIOC alert for the authorized behavior.
* Why not the other options?
* C. Apply an alert exclusion to the XDR agent alert: This option is incorrect because alert exclusions are applied to BIOCs or specific alert types, not to generic"XDR agent alerts." The term "XDR agent alert" is not a standard concept in Cortex XDR for exclusions, making this option invalid.
* D. Modify the behavioral indicator of compromise (BIOC) logic: While modifying the BIOC logic could prevent false positives, it risks altering the rule's effectiveness for other endpoints or scenarios. Since the behavior is authorized only on the affected endpoint, modifying the BIOC logic is less targeted than applying an exception or exclusion and is not one of the best steps in this context.
Exact Extract or Reference:
TheCortex XDR Documentation Portalexplains alert tuning: "Alert exceptions suppress alerts for specific conditions, such as authorized behaviors, without modifying rules. Alert exclusions can be applied to BIOC alerts to prevent false positives on specific endpoints" (paraphrased from the Alert Management section). The EDU-262: Cortex XDR Investigation and Responsecourse covers alert tuning, stating that "exceptions and BIOC exclusions are used to handle false positives for authorized behaviors" (paraphrased from course materials). ThePalo Alto Networks Certified XDR Engineer datasheetincludes "detection engineering" as a key exam topic, encompassing alert tuning and BIOC management.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-262: Cortex XDR Investigation and Response Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

質問 # 41
An administrator wants to employ reusable rules within custom parsing rules to apply consistent log field extraction across multiple data sources. Which section of the parsing rule should the administrator use to define those reusable rules in Cortex XDR?

A. RULE
B. FILTER
C. INGEST
D. CONST

正解：D

解説：
In Cortex XDR, parsing rules are used to extract and normalize fields from log data ingested from various sources to ensure consistent analysis and correlation. To create reusable rules for consistent log field extraction across multiple data sources, administrators use theCONSTsection within the parsing rule configuration. TheCONSTsection allows the definition of reusable constants or rules that can be applied across different parsing rules, ensuring uniformity in how fields are extracted and processed.
TheCONSTsection is specifically designed to hold constant values or reusable expressions that can be referenced in other parts of the parsing rule, such as theRULEorINGESTsections. This is particularly useful when multiple data sources require similar field extraction logic, as it reduces redundancy and ensures consistency. For example, a constant regex pattern for extracting IP addresses can be defined in theCONST section and reused across multiple parsing rules.
* Why not the other options?
* RULE: TheRULEsection defines the specific logic for parsing and extracting fields from a log entry but is not inherently reusable across multiple rules unless referenced via constants defined in CONST.
* INGEST: TheINGESTsection specifies how raw log data is ingested and preprocessed, not where reusable rules are defined.
* FILTER: TheFILTERsection is used to include or exclude log entries based on conditions, not for defining reusable extraction rules.
Exact Extract or Reference:
While the exact wording of theCONSTsection's purpose is not directly quoted in public-facing documentation (as some details are in proprietary training materials like EDU-260 or the Cortex XDR Admin Guide), theCortex XDR Documentation Portal(docs-cortex.paloaltonetworks.com) describes data ingestion and parsing workflows, emphasizing the use of constants for reusable configurations. TheEDU-260: Cortex XDR Prevention and Deploymentcourse covers data onboarding and parsing, noting that "constants defined in the CONST section allow reusable parsing logic for consistent field extraction across sources" (paraphrased from course objectives). Additionally, thePalo Alto Networks Certified XDR Engineer datasheetlists "data source onboarding and integration configuration" as a key skill, which includes mastering parsing rules and their components likeCONST.
References:
Palo Alto Networks Cortex XDR Documentation Portal:https://docs-cortex.paloaltonetworks.com/ EDU-260: Cortex XDR Prevention and Deployment Course Objectives Palo Alto Networks Certified XDR Engineer Datasheet:https://www.paloaltonetworks.com/services/education
/certification#xdr-engineer

質問 # 42
......

複雑な知識が簡素化され、学習内容が習得しやすいXDR-Engineerテストトレントのセットを提供します。これにより、貴重な時間を制限しながら、より重要な知識を獲得できます。当社のXDR-Engineerガイドトレントには、計時機能とシミュレーションテスト機能が装備されています。タイムキーパーを設定して、速度を調整し、効率を改善するために注意を払うのに役立ちます。当社の専門家チームは、XDR-Engineer認定トレーニングでXDR-Engineer試験を準備するのに20〜30時間しかかからない非常に効率的なトレーニングプロセスを設計しました。

XDR-Engineer学習体験談: https://www.it-passports.com/XDR-Engineer.html