XDR-Analyst Exam Dumps - Paloalto Networks Security Operations Questions and Answers

Cortex XDR allows you to define IOC rules based on various types of indicators of compromise (IOC) that you can use to detect and respond to threats in your network. One of the types of IOC that you can define in Cortex XDR is destination IP address, which is the IP address of the remote host that a local endpoint is communicating with. You can use this type of IOC to identify malicious network activity, such as connections to command and control servers, phishing sites, or malware distribution hosts. You can also specify the direction of the network traffic (inbound or outbound) and the protocol (TCP or UDP) for the destination IP address IOC. References:

Cortex XDR documentation portal

Is there a possibility to create an IOC list to employ it in a query?

Cortex XDR Datasheet

 Live terminal uses Python 3 with standard Python libraries to run Python commands and scripts on the endpoint. Live terminal does not support Python 2 or any custom or external Python libraries. Live terminal uses the Python interpreter embedded in the Cortex XDR agent, which is based on Python 3.7.4. The standard Python libraries are the modules that are included with the Python installation and provide a wide range of functionalities, such as operating system interfaces, network programming, data processing, and more. You can use the Python commands and scripts to perform advanced tasks or automation on the endpoint, such as querying system information, modifying files or registry keys, or running other applications. References:

Run Python Commands and Scripts

Python Standard Library

 You can star security events in Cortex XDR in two ways: manually star an alert or an incident, or create an alert-starring or incident-starring configuration. Starring security events helps you prioritize and track the events that are most important to you. You can also filter and sort the events by their star status in the Cortex XDR console.

To manually star an alert or an incident, you can use the star icon in the Alerts table or the Incidents table. You can also star an alert from the Causality View or the Query Center Results table. You can star an incident from the Incident View or the Query Center Results table. You can also unstar an event by clicking the star icon again.

To create an alert-starring or incident-starring configuration, you can use the Alert Starring Configuration or the Incident Starring Configuration pages in the Cortex XDR console. You can define the criteria for starring alerts or incidents based on their severity, category, source, or other attributes. You can also enable or disable the configurations as needed.

Remediation Suggestions is a feature of Cortex XDR that provides you with recommended actions to remediate the root cause and impact of an incident. Remediation Suggestions are based on the analysis of the causality chain, the behavior of the malicious files or processes, and the best practices for incident response. Remediation Suggestions can help you to quickly and effectively contain and resolve an incident, as well as prevent future recurrence.

To activate Remediation Suggestions, you need to follow these steps:

In the Cortex XDR management console, go to Incidents and select an incident that you want to remediate.

Click Causality View to see the graphical representation of the causality chain of the incident.

Click Actions and select Remediation Suggestions. This will open a new window that shows the suggested actions for each node in the causality chain.

Review the suggested actions and select the ones that you want to apply. You can also edit or delete the suggested actions, or add your own custom actions.

Click Apply to execute the selected actions on the affected endpoints. You can also schedule the actions to run at a later time or date.

The correct relation of alerts to incidents is that alerts with same causality chains that occur within a given time frame are grouped together into an incident. A causality chain is a sequence of events that are related to the same malicious activity, such as a malware infection, a lateral movement, or a data exfiltration. Cortex XDR uses a set of rules that take into account different attributes of the alerts, such as the alert source, type, and time period, to determine if they belong to the same causality chain. By grouping related alerts into incidents, Cortex XDR reduces the number of individual events to review and provides a complete picture of the attack with rich investigative details1.

Option A is incorrect, because alerts with the same host are not necessarily grouped together into one incident in a given time frame. Alerts with the same host may belong to different causality chains, or may be unrelated to any malicious activity. For example, if a host has a malware infection and a network anomaly, these alerts may not be grouped into the same incident, unless they are part of the same attack.

Option B is incorrect, because alerts that occur within a three hour time frame are not always grouped together into one incident. The time frame is not the only criterion for grouping alerts into incidents. Alerts that occur within a three hour time frame may belong to different causality chains, or may be unrelated to any malicious activity. For example, if a host has a file download and a registry modification within a three hour time frame, these alerts may not be grouped into the same incident, unless they are part of the same attack.

Option D is incorrect, because every alert does not create a new incident. Creating a new incident for every alert would result in alert fatigue and inefficient investigations. Cortex XDR aims to reduce the number of incidents by grouping related alerts into one incident, based on their causality chains and other attributes.

The Broker VM is a virtual machine that you can deploy in your network to provide various services and functionalities to the Cortex XDR agents. One of the services that the Broker VM offers is the Local Agent Settings applet, which allows you to configure the agent proxy, agent installer, and content caching settings for the agents. The Local Agent Settings applet can support a maximum number of 10,000 agents per Broker VM. If you have more than 10,000 agents in your network, you need to deploy additional Broker VMs and distribute the load among them. References:

Broker VM Overview: This document provides an overview of the Broker VM and its features, requirements, and deployment options.

Configure the Broker VM: This document explains how to install, set up, and configure the Broker VM in an ESXi environment.

Manage Broker VM from the Cortex XDR Management Console: This document describes how to activate and manage the Broker VM applets from the Cortex XDR management console.

When deploying Cortex XDR agent on Kubernetes clusters as a DaemonSet, the license required is Cortex XDR Cloud per Host. This license allows you to protect and monitor your cloud workloads, such as Kubernetes clusters, containers, and serverless functions, using Cortex XDR. With Cortex XDR Cloud per Host license, you can deploy Cortex XDR agents as DaemonSets on your Kubernetes clusters, which ensures that every node in the cluster runs a copy of the agent. The Cortex XDR agent collects and sends data from the Kubernetes cluster, such as pod events, container logs, and network traffic, to the Cortex Data Lake for analysis and correlation. Cortex XDR can then detect and respond to threats across your cloud environment, and provide visibility and context into your cloud workloads. The Cortex XDR Cloud per Host license is based on the number of hosts that run the Cortex XDR agent, regardless of the number of containers or functions on each host. A host is defined as a virtual machine, a physical server, or a Kubernetes node that runs the Cortex XDR agent. You can read more about the Cortex XDR Cloud per Host license and how to deploy Cortex XDR agent on Kubernetes clusters here1 and here2. References:

Cortex XDR Cloud per Host License

Deploy Cortex XDR Agent on Kubernetes Clusters as a DaemonSet