Free Paloalto Networks XDR-Analyst Practice Exam with Questions & Answers

 Cortex XDR allows you to schedule reports and forward them to Slack, a cloud-based collaboration platform. You can configure the Slack channel, frequency, and recipients of the scheduled reports. You can also view the report history and status in the Cortex XDR management console. References:

Scheduled Queries: This document explains how to create, edit, and manage scheduled queries and reports in Cortex XDR.

Forward Scheduled Reports to Slack: This document provides the steps to configure Slack integration and forward scheduled reports to a Slack channel.

Cortex XDR Analytics is a cloud-based service that uses machine learning and artificial intelligence to detect and prevent network attacks. Cortex XDR Analytics can interfere with the attack pattern as soon as it is observed on the endpoint by applying protection policies that block malicious processes, files, or network connections. This way, Cortex XDR Analytics can stop the attack before it causes any damage or compromises the system. References:

[Cortex XDR Analytics Overview]

[Cortex XDR Analytics Protection Policies]

 Live terminal session is a feature of Cortex XDR that allows you to remotely access and control endpoints from the Cortex XDR console. With live terminal session, you can execute various actions on the endpoints, such as:

Manage Processes: You can view, start, or kill processes on the endpoint, and monitor their CPU and memory usage.

Manage Files: You can view, create, delete, or move files and folders on the endpoint, and upload or download files to or from the endpoint.

Run Operating System Commands: You can run commands on the endpoint using the native command-line interface of the operating system, such as cmd.exe for Windows, bash for Linux, or zsh for macOS.

Run Python Commands and Scripts: You can run Python commands and scripts on the endpoint using the Python interpreter embedded in the Cortex XDR agent. You can use the Python commands and scripts to perform advanced tasks or automation on the endpoint.

The Managed Threat Hunting (MTH) team is a group of security experts who proactively hunt for threats in the Cortex XDR tenant and generate a report with the findings. The MTH team uses advanced queries and investigative actions to identify and analyze potential threats, such as zero-day exploits, that may have bypassed the prevention and detection capabilities of Cortex XDR. The MTH team also provides recommendations and best practices to help customers remediate the threats and improve their security posture. References:

Managed Threat Hunting Service

Managed Threat Hunting Report

The report output shows the number of endpoints that have forensic inventory data collection enabled, which is a feature of Cortex XDR that allows the collection of detailed information about the endpoint’s hardware, software, and network configuration. This feature helps analysts to investigate and respond to incidents more effectively by providing a comprehensive view of the endpoint’s state and activity. Forensic inventory data collection can be enabled or disabled per policy in Cortex XDR. References:

Forensic Inventory Data Collection

Cortex XDR 3: Getting Started with Endpoint Protection

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 acts as a data broker between third-party data sources and the Cortex Data Lake. It can ingest different types of data, such as syslog, netflow, database, and pathfinder. The Syslog Collector functionality of the Broker VM allows it to receive syslog messages from third-party devices, such as firewalls, routers, switches, and servers, and forward them to the Cortex Data Lake. The Syslog Collector can be configured to filter, parse, and enrich the syslog messages before sending them to the Cortex Data Lake. The Syslog Collector can also be used to ingest logs from third-party firewall vendors, such as Cisco, Fortinet, and Check Point, to the Cortex Data Lake. This enables Cortex XDR to analyze the firewall logs and provide visibility and threat detection across the network perimeter. References:

Cortex XDR Data Broker VM

Syslog Collector

Supported Third-Party Firewall Vendors

 When creating a scheduled report in Cortex XDR, the option to run quarterly on a certain day and time is not available. You can only schedule reports to run daily, weekly, or monthly. You can also specify the start and end dates, the time zone, and the recipients of the report. Scheduled reports are useful for generating regular reports on the security events, incidents, alerts, or endpoints in your network. You can create scheduled reports from the Reports page in the Cortex XDR console, or from the Query Center by saving a query as a report. References:

Run or Schedule Reports

Create a Scheduled Report

 The statement that best describes how Behavioral Threat Protection (BTP) works is D, BTP uses machine learning to recognize malicious activity even if it is not known. BTP is a feature of Cortex XDR that allows you to define custom rules to detect and block malicious behaviors on endpoints. BTP uses machine learning to profile behavior and detect anomalies indicative of attack. BTP can recognize malicious activity based on file attributes, registry keys, processes, network connections, and other criteria, even if the activity is not associated with any known malware or threat. BTP rules are updated through content updates and can be managed from the Cortex XDR console.

The other statements are incorrect for the following reasons:

A is incorrect because BTP does not inject into known vulnerable processes to detect malicious activity. BTP does not rely on process injection, which is a technique used by some malware to hide or execute code within another process. BTP monitors the behavior of all processes on the endpoint, regardless of their vulnerability status, and compares them with the BTP rules.

B is incorrect because BTP does not run on the Cortex XDR and distribute behavioral signatures to all agents. BTP runs on the Cortex XDR agent, which is installed on the endpoint, and analyzes the endpoint data locally. BTP does not use behavioral signatures, which are predefined patterns of malicious behavior, but rather uses machine learning to identify anomalies and deviations from normal behavior.

C is incorrect because BTP does not match EDR data with rules provided by Cortex XDR. BTP is part of the EDR (Endpoint Detection and Response) capabilities of Cortex XDR, and uses the EDR data collected by the Cortex XDR agent to perform behavioral analysis. BTP does not match the EDR data with rules provided by Cortex XDR, but rather applies the BTP rules defined by the Cortex XDR administrator or the Palo Alto Networks threat research team.

 WildFire is a cloud-based service that accepts and analyses samples from various sources, including Cortex XDR, to provide a verdict of malware, benign, or grayware. WildFire also generates detailed analysis reports that show the behaviour and characteristics of the samples. Cortex XDR uses WildFire verdicts and reports to enhance its detection and prevention capabilities, as well as to provide more visibility and context into the threats. References:

WildFire Analysis Concepts

WildFire Overview