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Google Security Operations Engineer (Beta) Sample Questions:

1. Your team is responsible for cybersecurity for a large multinational corporation. You have been tasked with identifying unknown command and control nodes (C2s) that are potentially active in your organization's environment. You need to generate a list of potential matches within the Next 24 hours. What should you do?

A) Write a YARA-L rule in Google Security Operations (SecOps) that compares network traffic of endpoints to low prevalence domains against recent WHOIS registrations.
B) Review Security Health Analytics (SHA) findings in Security Command Center (SCC).
C) Write a rule in Google Security Operations (SecOps) that scans historic network outbound connections against ingested threat intelligence Run the rule in a retrohunt against the full tenant.
D) Load network records into BigQuery to identify endpoints that are communicating with domains outside three standard deviations of normal.

2. You are an incident responder at your organization using Google Security Operations (SecOps) for monitonng and investigation. You discover that a critical production server, which handles financial transactions, shows signs of unauthorized file changes and network scanning from a suspicious IP address. You suspect that persistence mechanisms may have been installed. You need to use Google SecOps to immediately contain the threat while ensuring that forensic data remains available for investigation. What should you do first?

A) Use the EDR integration to quarantine the compromised asset.
B) Use VirusTotal to enrich the IP address and retrieve the domain. Add the domain to the proxy block list.
C) Deploy emergency patches, and reboot the server to remove malicious persistence.
D) Use the firewall integration to submit the IP address to a network block list to inhibit internet access from that machine.

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

4. You are working with your company's analyst team to automate the investigation of phishing alerts ingested directly into Google Security Operations (SecOps) SOAR from an email inbox.
The analyst team currently uses a SIEM query to search for related information. You need to design a solution to automatically include the query results in the Google SecOps case without writing any new code. What should you do?

A) Create a custom action in Google SecOps IDE that runs the SIEM query from a playbook through an API call and returns the results.
B) Add a widget to the Default Case View in Google SecOps SOAR that allows the analyst team to query directly from the widget.
C) Add an action to the playbook that runs the SIEM query and returns the results.
D) Modify the detection rule in the SIEM to include the query results as part of the detection.

5. Your company uses Google Security Operations (SecOps) Enterprise and is ingesting various logs. You need to proactively identify potentially compromised user accounts. Specifically, you need to detect when a user account downloads an unusually large volume of data compared to the user's established baseline activity. You want to detect this anomalous data access behavior using the least amount of effort. What should you do?

A) Develop a custom YARA-L detection rule in Google SecOps that counts download bytes per user per hour and triggers an alert if a threshold is exceeded.
B) Enable curated detection rules for User and Endpoint Behavioral Analytics (UEBA), and use the Risk Analytics dashboard in Google SecOps to identify metrics associated with the anomalous activity.
C) Inspect Security Command Center (SCC) default findings for data exfiltration in Google SecOps.
D) Create a log-based metric in Cloud Monitoring, and configure an alert to trigger if the data downloaded per user exceeds a predefined limit. Identify users who exceed the predefined limit in Google SecOps.

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