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| Section | Weight | Objectives |
|---|---|---|
| Security Operations Foundations | 20% | - SOC Roles and Responsibilities - Threat Intelligence Frameworks - Incident Response Lifecycle |
| Detection and Analysis | 30% | - Malware Triage - Log Analysis (XSIAM/Prisma) - Endpoint and Network Forensics |
| Reporting and Metrics | 20% | - Incident Reporting - Dashboard Customization - SOC Performance Metrics |
| XSOAR Automation and Orchestration | 30% | - Integration Management - Incident Classification and Severity - Playbook Development |
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NEW QUESTION # 124
What is the primary goal of the Post-Incident Activity phase in the NIST Incident Response Plan?
Answer: B
Explanation:
The post-incident activity phase focuses on reviewing the incident through lessons learned sessions to improve future response processes, controls, and overall security posture.
NEW QUESTION # 125
Which two functions are allowed when stitching logs in Cortex XDR? (Choose two.)
Answer: A,C
Explanation:
Log Stitching is the "secret sauce" of the Cortex XDR platform. It is the automated process of taking raw, fragmented data from various sources-such as Palo Alto Networks Next-Generation Firewalls, Prisma Access, and Cortex XDR agents-and "stitching" them into a unified causality chain.
* BIOC and Correlation Rules (B): Because log stitching links network activity (like a suspicious DNS request) directly to an endpoint process (like a specific cmd.exe instance), it allows analysts to write highly granular Behavioral Indicators of Compromise (BIOCs) . Without stitching, you could only write a rule for "Suspicious DNS" or "Suspicious Process." With stitching, you can write a rule for
"Process X making Suspicious DNS request Y," which drastically reduces false positives.
* Unified Investigation Queries (D): Log stitching enables the use of XQL to query across datasets simultaneously. An analyst can run a single query that returns a timeline showing exactly when a file was downloaded (Network Log) and the exact moment that file was executed on the host (Endpoint Log). This provides the "Full Picture" required for rapid root-cause analysis.
Why other options are incorrect:
* Option A: Prevention and remediation are handled by the Cortex XDR Agent and Firewall security profiles . While stitching informs these actions by providing context, the act of stitching itself is a data processing function, not a prevention mechanism.
* Option C: Custom scripts are part of the Response and Automation frameworks (Live Terminal or XSOAR/XSIAM playbooks). They are not a function or result of the log stitching process.
NEW QUESTION # 126
A sophisticated ransomware attack has breached your network. Your Cortex XSIAM deployment generated an incident for 'Ransomware Activity' on several endpoints. During the investigation, you observe encrypted files with a new extension and a ransom note. You also find suspicious PowerShell activity attempting to disable security features. To enhance your immediate response and create a high-fidelity 'incident response' rule, you need to enrich the incident details by automatically adding relevant threat intelligence, and more aggressively alert on this specific ransomware variant across your entire infrastructure. Which combination of Cortex XSIAM features, XQL, and incident enrichment capabilities would best achieve this, including automating a response action? (Select all that apply)
Answer: B,E
Explanation:
Options C and D are the most effective and aligned with advanced Cortex XSIAM capabilities for immediate response and high- fidelity incident handling. Option C: This leverages XSIAM's direct incident enrichment and automation features. Adding indicators directly from the incident to XSIAM's indicator store (which then feeds into detection engines) is a rapid response action. Configuring an 'Automation Rule' to trigger on specific incident types is key for automating playbooks for containment (like host isolation and firewall blocking) and enriching incidents with external threat intelligence (e.g., VirusTotal for hashes found on the compromised host). This is a core XSIAM strength for incident response. Option D: Creating a new 'Correlation Rule' is precisely how you build high-fidelity detections for multi-stage attacks like ransomware. Linking file encryption, security feature disablement, and C2 communication within a specific timeframe provides a very strong signal. Setting it to 'Critical' and triggering a comprehensive 'Security Playbook' (which can include automated containment, data collection, and notification) is the ideal programmatic response for a sophisticated threat. The XQL would indeed be complex, involving multiple joins, but this is the necessary approach for high-fidelity correlation. This proactively identifies future instances of this specific ransomware variant's behavior. Option A is good for adding indicators but doesn't fully capture the multi-faceted nature of the attack for rule creation and advanced automation. Option B's behavioral rule is too broad for high fidelity and might generate false positives without proper time-based correlation between the events. Option E involves manual steps and external systems, which is less efficient and proactive than XSIAM's integrated capabilities for immediate response.
NEW QUESTION # 127
A file hash is evaluated a Cortex XSOAR by using two unique threat feeds:
- VirusTotal feed (rating of B- usually reliable) and the file verdict
is malicious
- AlienVault feed (rating of B- usually reliable) and the file verdict
is benign
What is the file verdict in XSOAR?
Answer: C
Explanation:
Conflicting threat feed verdicts (malicious vs. benign) result in an "Unknown" verdict in Cortex XSOAR until further analysis resolves the conflict.
NEW QUESTION # 128
Which scripting language will allow the use of the Query Builder in Cortex XDR to show the top five accounts with failed Windows logons in the past 24 hours? (Choose one answer)
Answer: B
Explanation:
In the Cortex ecosystem, specifically within Cortex XDR and Cortex XSIAM, XQL (Cortex Query Language) is the mandatory language for all data retrieval and analysis tasks.
* Query Builder Integration: The Query Builder is the graphical user interface (GUI) designed to help analysts construct XQL queries without needing to memorize syntax. When you use the Query Builder to select filters, datasets, and time ranges, it is generating an XQL statement in the background.
* Aggregations: To show the "top five" of a specific category (like failed logons), XQL uses functions like comp (compute), count, and sort. This allows the system to process billions of logs in the Cortex Data Lake to return the specific dataset requested.
* Real-world use: An analyst would use XQL to search the authentication dataset, filter for result = FAILED, and then aggregate by user to find the most frequent occurrences.
Why other options are incorrect:
* PowerShell (A) and Python (D): These are used for endpoint management (scripts run on the host) or automation in XSOAR/XSIAM playbooks, but they cannot query the Cortex Data Lake directly via the Query Builder.
* JavaScript (B): This is not used for data querying within the Palo Alto Networks security platform.
NEW QUESTION # 129
......
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