XDR-Analyst Exam Dumps - Palo Alto Networks XDR Analyst

The engine that determines the most relevant artifacts in each alert and aggregates all alerts related to an event into an incident is the Causality Analysis Engine. The Causality Analysis Engine is one of the core components of Cortex XDR that performs advanced analytics on the data collected from various sources, such as endpoints, networks, and clouds. The Causality Analysis Engine uses machine learning and behavioral analysis to identify the root cause, the attack chain, and the impact of each alert. It also groups related alerts into incidents based on the temporal and logical relationships among the alerts. The Causality Analysis Engine helps to reduce the noise and complexity of alerts and incidents, and provides a clear and concise view of the attack story12.

Let’s briefly discuss the other options to provide a comprehensive explanation:

A. Sensor Engine: This is not the correct answer. The Sensor Engine is not responsible for determining the most relevant artifacts in each alert and aggregating all alerts related to an event into an incident. The Sensor Engine is the component that runs on the Cortex XDR agents installed on the endpoints. The Sensor Engine collects and analyzes endpoint data, such as processes, files, registry keys, network connections, and user activities. The Sensor Engine also enforces the endpoint security policies and performs prevention and response actions3.

C. Log Stitching Engine: This is not the correct answer. The Log Stitching Engine is not responsible for determining the most relevant artifacts in each alert and aggregating all alerts related to an event into an incident. The Log Stitching Engine is the component that runs on the Cortex Data Lake, which is the cloud-based data storage and processing platform for Cortex XDR. The Log Stitching Engine normalizes and stitches together the data from different sources, such as firewalls, proxies, endpoints, and clouds. The Log Stitching Engine enables Cortex XDR to correlate and analyze data from multiple sources and provide a unified view of the network activity and threat landscape4.

D. Causality Chain Engine: This is not the correct answer. Causality Chain Engine is not a valid name for any of the Cortex XDR engines. There is no such engine in Cortex XDR that performs the function of determining the most relevant artifacts in each alert and aggregating all alerts related to an event into an incident.

In conclusion, the Causality Analysis Engine is the engine that determines the most relevant artifacts in each alert and aggregates all alerts related to an event into an incident. By using the Causality Analysis Engine, Cortex XDR can provide a comprehensive and accurate detection and response capability for security analysts.

Cortex XDR allows you to create two types of exception profiles: agent exception profiles and global exception profiles. Agent exception profiles apply to specific endpoints that are assigned to the profile. Global exception profiles apply to all endpoints in your network. You can use exception profiles to configure different types of exceptions, such as process exceptions, support exceptions, behavioral threat protection rule exceptions, local analysis rules exceptions, advanced analysis exceptions, or digital signer exceptions. Exception profiles help you fine-tune the security policies for your endpoints and reduce false positives. References:

Exception Security Profiles

Create an Agent Exception Profile

Create a Global Exception Profile

The outcome of creating and implementing an alert exclusion is that the Cortex XDR console will hide those alerts that match the exclusion criteria. An alert exclusion is a policy that allows you to filter out alerts that are not relevant, false positives, or low priority, and focus on the alerts that require your attention. When you create an alert exclusion, you can specify the criteria that define which alerts you want to exclude, such as alert name, severity, source, or endpoint. After you create an alert exclusion, Cortex XDR will hide any future alerts that match the criteria, and exclude them from incidents and search query results. However, the alert exclusion does not affect the behavior of the Cortex XDR agent or the security policy on the endpoint. The Cortex XDR agent will still create an alert for the event and apply the appropriate action, such as blocking or quarantining, according to the security policy. The alert exclusion only affects the visibility of the alert on the Cortex XDR console, not the actual protection of the endpoint. Therefore, the correct answer is B, the Cortex XDR console will hide those alerts12

 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.

The Host Insights module provides the best visibility to view vulnerabilities on your endpoints. The Host Insights module is an add-on feature for Cortex XDR that combines vulnerability management, application and system visibility, and a Search and Destroy feature to help you identify and contain threats. The vulnerability management feature allows you to scan your Windows endpoints for known vulnerabilities and missing patches, and view the results in the Cortex XDR console. You can also filter and sort the vulnerabilities by severity, CVSS score, CVE ID, or patch availability. The Host Insights module helps you reduce your exposure to threats and improve your security posture. References:

Host Insights

Vulnerability Management

 Local Analysis is a feature of Cortex XDR that allows the agent to evaluate files locally on the endpoint, without sending them to WildFire for analysis. Local Analysis is evoked when the following conditions are met:

The endpoint is disconnected from the internet or the Cortex XDR management console, and therefore cannot communicate with WildFire.

The verdict from WildFire is of a type unknown, meaning that WildFire has not yet analyzed the file or has not reached a conclusive verdict.

Local Analysis uses machine learning models to assess the behavior and characteristics of the file and assign it a verdict of either benign, malware, or grayware. If the verdict is malware or grayware, the agent will block the file from running and report it to the Cortex XDR management console. If the verdict is benign, the agent will allow the file to run and report it to the Cortex XDR management console. References:

Local Analysis

WildFire File Verdicts

 To create a BIOC rule with XQL query, you must at a minimum filter on the event_type field in order for it to be a valid BIOC rule. The event_type field indicates the type of event that triggered the alert, such as PROCESS, FILE, REGISTRY, NETWORK, or USER_ACCOUNT. Filtering on this field helps you narrow down the scope of your query and focus on the relevant events for your use case. Other fields, such as causality_chain, endpoint_name, threat_event, are optional and can be used to further refine your query or display additional information in the alert. References:

Palo Alto Networks Certified Detection and Remediation Analyst (PCDRA) Study Guide, page 9

Palo Alto Networks Cortex XDR Documentation, BIOC Rule Query Syntax

 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