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Google Security Operations Engineer (Beta) Sample Questions:

1. You have noticed that a Google Security Operations (SecOps) detection rule that detects excessive network connections is triggering too frequently and creating too many false positive alerts. You want to improve the rule to reduce the noise without reducing the effectiveness of the rule. What change to the detection rule should you implement?

A) Add a threshold in the YARA-L condition: section to ensure that the rule only alerts after a certain number of connections.
B) Include a 10 minute timeframe for the same source and destination of network connections in the YARA-L match: section to aggregate the alerts.
C) Update the YARA-L events: section to exclude the most common IP addresses involved in the network connection alerts to reduce the number of alerts.
D) Assign a risk score in the YARA-L outcome: section to prioritize alerts more effectively in the alert queue.

2. Your organization has recently onboarded to Google Cloud with Security Command Center Enterprise (SCCE) and is now integrating it with your organization's SO You want to automate the response process and integrate with the existing SOW ticketing system. How should you implement this functionality?

A) Disable the generic posture finding playbook in Google Security Operations (SecOps) SOAR and enable the playbook for the ticketing system. Add a step in your Google SecOps SOAR playbook to generate a ticket based on the event type.
B) Configure the SCC notifications feed to use Pub/Sub for alerts. Create a Cloud Run function to trigger when an event arrives in the topic and generate a ticket by calling the API endpoint in the SOC ticketing system.
C) Evaluate each event within the SCC console. Create a ticket for each finding in the ticketing system, and include the remediation steps.
D) Use the SCC notifications feed to send alerts to Pub/Sub. Ingest these feeds using the relevant SIEM connector.

3. You are ingesting and parsing logs from an SSO provider and an on-premises appliance using Google Security Operations (SecOps). Users are tagged as "restricted" by an internal process. Restrictions last five days from the most recent flagging time. You need to create a rule to detect when restricted users log into the appliance. Your solution must be quickly implemented and easily maintained. What should you do?

A) Use a Google SecOps SOAR global context value to store a list of flagged users with their corresponding time to live values. Use a SOAR job to dynamically build and deploy a new version of the detection rule with the updated list of flagged users.
B) Ingest the user flags as custom enrichment data using a feed. Use a multi-event detection rule to find logins from users flagged in the entity graph.
C) Store the identifiers of the flagged users in the detection rule logic. Actively monitor for newly flagged users, and add them to the detection rule logic.
D) Store the flagged users in a data table column with their corresponding time to live values in a second column. Use row-based comparisons in your detection rule.

4. Your organization recently implemented Google Security Operations (SecOps) with Applied Threat Intelligence enabled. You were notified by the networking team about potentially anomalous communications to external domains in the last 30 days. You plan to start your threat hunting by looking at communications to external domains. You are ingesting the following logs into Google SecOps:
- Firewall logs
- Proxy logs
- DNS logs
- DHCP logs
What should you do? (Choose two.)

A) Navigate to the IOC Matches page and filter based on domain type over the last 30 days. Look for the first seen and last seen timestamps for the reported domains. Investigate these domains using the IOC drilldown link.
B) Identify the domains with the higher normalized risk in Risk Analytics. Drill down into those entities to determine their prevalence and if they were first seen in the last 30 days.
C) Perform a raw log search across the logs for domains with low prevalence that were first seen in the last 30 days.
D) Perform a UDM search across the logs for domains with geolocations that were first seen in the last 30 days.
E) Perform a UDM search across the logs for domains with low prevalence that were first seen in the last 30 days.

5. You are using Google Security Operations (SecOps) to hunt for signs of lateral movement through Remote Desktop Protocol (RDP) in your organization. You suspect that a compromised account was used to access multiple internal systems within a short time window. You want to construct a UDM-based search to identify this activity. How should you build this query? (Choose two.)

A) Filter for RDP connections with non-standard ports.
B) Use a saved search to identify all events with the LATERAL MOVEMENT tag over the past 30 days.
C) Filter for events using protocol-level attributes that indicate RDP connections.
D) Group events by user identity and time to identify repeated access patterns.
E) Correlate events based on the asset role or classification such as database or user workstation.

Solutions: