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NEW QUESTION # 58
A security engineer is designing a playbook task to automatically reassign an incident to a specific owner and update the Details field with new information gathered during the investigation.
Which script should be selected in the playbook task to perform these updates?
Answer: B
Explanation:
The setIncident script is used in playbook tasks to set or update incident fields, including system fields such as owner and text fields such as Details. Palo Alto documentation specifically states that during investigation, playbooks can use setIncident to update incident fields.
Reference: https://docs-cortex.paloaltonetworks.com/r/Cortex-XSOAR/8.9/Cortex-XSOAR-On- prem-Documentation/Set-and-update-incident-fields
NEW QUESTION # 59
Which cytool command will look up the policy being applied to a Cortex XDR agent?
Answer: B
Explanation:
The cytool adaptive_policy recalc command is used to look up and recalculate the policy being applied to a Cortex XDR agent, allowing engineers to verify the active policy enforcement on the endpoint.
NEW QUESTION # 60
Consider the following XSIAM correlation rule pseudo-code designed to detect a suspicious 'Golden Ticket' attack attempt, where an attacker might try to use a forged Kerberos ticket:
Based on a new threat intelligence report, a 'Golden Ticket' attack can now be executed without 'mimikatz.exe' and often involves a 'service ticket' request from a newly created user account. How should this XSIAM rule be optimized to align with the updated threat intelligence, while maintaining a low false positive rate?
Answer: C
Explanation:
Option A is the most effective and accurate optimization. The updated threat intelligence states that Mimikatz is not always present and new user accounts are involved, along with 'service_ticket' requests. Removing the Mimikatz correlation and adding a 'new_user_creation_log' correlation with an 'account_age' condition directly addresses these points. Adjusting the service_name to include 'service_ticket' broadens the initial detection phase to cover the new attack vector. Options B, C, D, and E either degrade the rule's effectiveness, introduce new false negatives, or are not directly relevant to the described threat intelligence update.
NEW QUESTION # 61
A security engineer is developing a custom detection rule in XSIAM that needs to leverage a combination of endpoint process activity (from Cortex XDR), cloud API calls (from AWS CloudTrail), and identity authentication attempts (from Okta). The rule aims to identify a specific insider threat scenario where a compromised cloud administrative account is used to deploy malicious code via an EC2 instance, followed by unauthorized data exfiltration. Write an XQL query snippet that demonstrates the core logic for correlating these disparate data sources to detect this multi-stage attack. Assume relevant fields are available and normalized.
Answer: C
Explanation:
The scenario describes a multi-stage attack: compromised cloud admin account (likely weak auth), deploying malicious code via EC2, and data exfiltration (implied by 'malicious code' and 'insider threat'). The XQL query needs to chain these events chronologically or contextually. Option E best captures this logic: 1. 'dataset = okta_authentication I filter outcome = 'SUCCESS' and authentication_method = : This is a strong indicator of a potentially compromised cloud administrative account, as it looks for successful logins using only a password, which is a common vulnerability for insider threats or compromised credentials. 2. 'join (dataset = aws_cloudtrail I filter event_name = 'Runlnstances' and event_source = 'ec2.amazonaws.com') on user_id = : This joins the Okta authentication event with AWS CloudTrail logs specifically for 'Runlnstances' (EC2 instance launch/deployment) using the common user identifier ('user_id' from Okta, from CloudTrail). This links the suspicious login to the cloud resource deployment. 3. 'join (dataset = xdr_data I filter event_type = 'Process' and process_name = 'malicious_payload.exe' and action_type = 'Process Started') on user_id = event_user and host_ip = aws_cloudtrail.source_ip_addresS : This final join correlates the cloud activity with endpoint process execution. It looks for a 'malicious_payload.exe' process start (endpoint data from XDR) where the user context matches the user from the previous joins Cuser_id = event_user') and, crucially, the endpoint's IP address matches the source IP from the CloudTrail 'RunlnstanceS event, indicating the malicious payload was run on the newly deployed EC2 instance or an instance associated with that activity. This provides the full chain of events. Other options have flaws: - A: Joins with failed Okta attempts (doesn't fit successful compromise) and 'mfaAuthenticated= false' might be too broad or miss the specific password-only weak authentication. - B: Joining XDR first is less logical for a multi-stage attack starting with identity/cloud, and the = join condition is generic without dataset qualification. - C: Joining src_ip_address = peer_ip_addresS is ambiguous and may not correctly link the cloud activity to the endpoint. It also looks for 'factor_type 'MFA'S which is broader than 'password_only'. - D: The 'source_ip = aws_cloudtrail.source_ip_addresS join without proper dataset aliasing can be problematic, and the 'user_id = principal_user_id' is generic. It doesn't start with the identity event, which is the initial trigger in this scenario.
NEW QUESTION # 62
Which two requirements must be met for a Cortex XDR agent to successfully use the Broker VM as a download source for content updates? (Choose two.)
Answer: A,C
Explanation:
For Cortex XDR agents to use the Broker VM as a download source, the Agent Settings profile must specify the Broker VM as the update source, and the Broker VM must be configured with an FQDN so agents can reliably resolve and connect to it.
NEW QUESTION # 63
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