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During a malware outbreak, a Palo Alto Networks security engineer needs to quickly determine if any newly submitted files to WildFire from endpoints are exhibiting specific command-and-control (C2) beaconing patterns or attempting to exploit a recently discovered zero-day vulnerability. Which of the following Cortex XDR and WildFire features or functionalities would be most effective for this real- time monitoring and proactive threat hunting, and why?
A. Monitoring the 'WildFire Submissions' dashboard in Cortex XDR for any 'Pending Analysis' status, then manually reviewing each report for C2 indicators. This is effective due to its granular control.
B. Leveraging Cortex XDR's 'Threat Hunting' module with XQL queries to search for specific network connections (e.g., unusual ports, C2 domains) and file execution events related to new WildFire submissions. Simultaneously, WildFire's dynamic analysis (sandboxing) will analyze unknown files for behavioral patterns indicative of C2 or zero-day exploitation, regardless of known signatures.
C. Utilizing WildFire's 'File Hash Lookup' for every suspicious file detected by XDR. This allows for quick verdicts but doesn't proactively identify new C2 or zero-day exploitation attempts unless the hash is already known malicious.
D. Configuring the firewall to block all traffic to external C2 domains based on threat intelligence feeds, which will prevent C2 communication, and assuming WildFire will automatically detect and prevent the zero-day exploit if the file is unknown.
E. Creating a new custom rule in Cortex XDR's Behavioral Threat Protection to specifically look for the zero-day exploit's signature, and configuring WildFire to perform static analysis on all incoming files, as static analysis is faster.
Answer: B
Explanation:
Option D is the most comprehensive and effective approach. Cortex XDR's Threat Hunting with XQL allows proactive searching across endpoint data, including network connections and file executions, to identify C2 patterns. Concurrently, WildFire's core strength lies in dynamic analysis (sandboxing) of unknown files, where it executes the file in a safe environment to observe its true behavior, including C2 beaconing attempts and exploitation techniques, even for zero-days not yet covered by static signatures. This combination provides both proactive hunting and behavioral analysis for unknown threats.
NEW QUESTION # 88
A Security Operations Center (SOC) is leveraging Cortex XSOAR and has identified a critical vulnerability in their internal web application. They need to quickly orchestrate a patching process that involves fetching the vulnerability details from a threat intelligence platform, creating a Jira ticket for the development team, and then pushing the patch through their CI/CD pipeline. Which Marketplace packs would be most crucial for achieving this end-to-end automation, and what is the primary benefit of using these Marketplace packs over custom script development for this scenario?
A. Threat Intelligence Management Pack, Jira Pack, and DevOps Pack. The primary benefit is accelerated time-to-value by utilizing certified and maintained integrations, reducing the burden of integration maintenance and updates.
B. Security Orchestration Pack and Incident Response Pack. The primary benefit is enhanced visibility into incident lifecycle and automated reporting capabilities for compliance.
C. Vulnerability Management Pack and CI/CD Automation Pack. The primary benefit is leveraging validated, community-contributed content, offering broader coverage for various vulnerability types and CIICD tools.
D. Threat Intelligence Management Pack and Jira Pack. The primary benefit is access to pre-built integrations with no custom code required, ensuring rapid deployment and reduced development overhead.
E. Threat Intelligence Management Pack, Jira Pack, and a custom CI/CD integration script. The primary benefit is gaining fine-grained control over the CI/CD process through custom scripting while using Marketplace packs for standard integrations.
Answer: A
Explanation:
Option E is the most comprehensive and accurate answer. The 'Threat Intelligence Management Pack' would be used to fetch vulnerability details, the 'Jira Pack' for ticket creation, and a 'DevOps Pack' (or a specific CI/CD tool pack within DevOps) would be essential for interacting with the CI/CD pipeline. The primary benefit of using Marketplace packs, especially certified ones, is indeed accelerated time-to-value due to pre-built, tested, and maintained integrations, reducing the need for custom development and ongoing maintenance. Option A and B are partially correct but don't capture the full scope or the most significant benefit as well as E. Option C defeats the purpose of leveraging Marketplace for CI/CD, and Option D is focused on different aspects of XSOAR functionality.
NEW QUESTION # 89
An advanced persistent threat (APT) group is suspected of using living-off-the-land (LOTL) techniques on a critical server, specifically leveraging the Windows Management Instrumentation (WMI) service for persistence and execution. Cortex XDR has raised a 'Suspicious WMI Event Subscriber' alert. To fully understand the attacker's WMI activity, including the exact WMI queries, associated processes, and any network activity generated by the WMI commands, which key Cortex XDR data sources and features would be indispensable for a thorough investigation?
A. WMI event logs collected by the XDR agent, combined with process execution telemetry and network connection logs. The Incident Graph for visualizing the WMI event causality.
B. File system activity logs to detect new executables, and DNS query logs to identify C2 domains. Threat intelligence lookup for known APT indicators.
C. Active Directory logs for user authentication, coupled with network flow data and firewall logs to identify unusual traffic patterns.
D. Cloud audit logs for suspicious API calls, and email security logs for phishing attempts.
E. Vulnerability scan reports to identify unpatched systems, and endpoint isolation using Live Response to contain the threat.
Answer: A
Explanation:
Investigating WMI-based attacks requires specific and granular data. Cortex XDR agents are capable of collecting detailed WMI event logs, including WMI object modifications, event consumers, and providers. This directly addresses understanding the 'WMI queries' and changes. Combining this with process execution telemetry (to see which processes initiated WMI actions) and network connection logs (to see if WMI led to network communication, e.g., for data exfiltration or C2) is crucial. The Incident Graph in Cortex XDR is invaluable for visualizing the causality chain of these complex events, making it easier to trace the attacker's actions. Options B, C, D, and E provide relevant security data but are not as directly tailored to dissecting WMI-specific attack techniques and their immediate consequences.
NEW QUESTION # 90
A large enterprise utilizes Cortex Data Lake (CDL) as its central repository for security logs. The SecOps team needs to generate a compliance report every quarter that lists all network connections initiated from internal corporate subnets to known malicious IP addresses, along with the source user and process, for the past 90 days. The report must be in a machine-readable format (e.g., JSON or CSV) and automatically delivered to a specific S3 bucket. Which combination of Cortex tools and programmatic approaches would be the most efficient and scalable solution?
A. Configure a SIEM connector to pull data from CDL into an external SIEM. Generate the report within the SIEM, then use the SIEM's export capabilities to send it to S3. This adds an unnecessary dependency on an external SIEM for a CDL-native reporting requirement.
B. Use the XDR 'Report' module to create a custom report with an XQL query filtering for malicious IPs. Manually export the report as CSV/JSON every quarter and upload it to S3. This is inefficient due to manual intervention.
C. Utilize Cortex XDR's 'Threat Hunting' features to identify the malicious connections. For reporting, create an alert rule that triggers on such connections, and then configure the alert to send an email notification with an attached summary to a distribution list. This doesn't provide a comprehensive quarterly report in a machine-readable format to S3.
D. Develop a serverless function (e.g., AWS Lambda) that periodically queries CDL directly via the XQLAPI, processes the results, and uploads them to the S3 bucket. This requires external infrastructure and direct API interaction, which can be complex to manage for large datasets.
E. Leverage Cortex XSOAR's 'Data Collection & Export' capabilities. Create a scheduled job in XSOAR that runs an XQL query against CDL for the specified data. Use a pre-built or custom integration in XSOAR to connect to the S3 bucket and upload the generated report in the desired format. This offers a robust, automated, and integrated solution.
Answer: E
Explanation:
Option C is the most suitable and scalable solution. Cortex XSOAR is designed for security orchestration and automation. It can directly interact with CDL via XQL queries, process the results, and leverage its extensive integration ecosystem (including S3 integrations) to automate the entire report generation and delivery process. This eliminates manual steps, is highly scalable for large datasets, and keeps the solution within the Cortex ecosystem.
NEW QUESTION # 91
A global organization uses Cortex XSIAM and has stringent data residency requirements. They operate data centers in regions where XSIAM's cloud-native log ingestion endpoints are not yet available. They need to ingest logs from their on-premise infrastructure, including Windows Event Logs, Linux Syslog, and custom application logs, ensuring all data remains within specific regional boundaries before being processed and analyzed by XSIAM. What is the most appropriate and compliant ingestion architecture for this scenario, and what specific XSIAM components are critical?
A. Implement an on-premise Splunk instance in each region, forward all logs to Splunk, and then use the Splunk Data Exporter to push processed data to XSIAM.
B. Deploy multiple dedicated Log Collectors within each required regional data center. These Log Collectors will process and normalize logs locally, then forward them to their respective XSIAM tenant, ensuring data residency is maintained at all stages.
C. Utilize Cortex XDR Agents on all endpoints and servers, as they inherently store logs locally before forwarding to the nearest XSIAM cloud region.
D. Leverage public cloud providers' regional log aggregation services (e.g., Azure Log Analytics, AWS CloudWatch Logs) and then configure XSIAM Cloud Feeds to pull from these regional services.
E. Configure all on-premise devices to send logs directly via HTTPS to a regional XSIAM Ingestion API endpoint, relying on network routing to maintain data residency.
Answer: B
Explanation:
For strict data residency requirements where XSIAM cloud-native ingestion endpoints are not available in specific regions, the most appropriate and compliant architecture is to deploy dedicated Log Collectors within each required regional data center (Option B). Cortex XSIAM Log Collectors are designed to be deployed on-premise or within private cloud environments. They act as a local aggregation and processing point, ensuring that logs remain within the specified regional boundaries before being securely forwarded to the XSIAM tenant. This architecture explicitly addresses the 'data remains within specific regional boundaries' constraint. XDR Agents (A) forward to XSIAM cloud, not necessarily a specific regional tenant for residency. Direct HTTPS to API (C) might still route through non-compliant regions if the XSIAM endpoint isn't local. Splunk (D) adds unnecessary cost and complexity for what XSIAM can do natively. Public cloud aggregation (E) means the data resides in a public cloud, which might violate strict on-premise residency requirements.
NEW QUESTION # 92
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