Free Google Professional Security Operations Engineer Exam Questions (page: 2)

You are responsible for identifying suspicious activity and security events at your organization. You have been asked to search in Google Security Operations (SecOps) for network traffic associated with an active HTTP backdoor that runs on TCP port 5555. You want to use the most effective approach to identify traffic originating from the server that is running the backdoor.
What should you do?

  1. Detect on events where network.ApplicationProtocol is HTTP.
  2. Detect on events where target.port is 5555.
  3. Detect on events where principal.port is 5555.
  4. Detect on events where network.ip_protocol is TCP.

Answer(s): C

Explanation:

The backdoor is running on TCP port 5555 on the server, meaning the server is the source of the traffic. In Google Security Operations (SecOps), the field principal.port represents the source port of the traffic, while target.port represents the destination. Since you want to identify traffic originating from the compromised server, filtering on principal.port = 5555 is the most effective approach.



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?

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

Answer(s): C

Explanation:

The most effective first step in containment while preserving forensic data is to use the EDR integration to quarantine the compromised asset. Quarantine isolates the server from the network, preventing further malicious activity, but it does not wipe or reboot the system, ensuring that evidence such as persistence mechanisms, unauthorized file changes, and indicators of compromise remain intact for forensic investigation.



Your organization uses Google Security Operations (SecOps). You discover frequent file downloads from a shared workspace within a short time window. You need to configure a rule in Google SecOps that identifies these suspicious events and assigns higher risk scores to repeated anomalies.
What should you do?

  1. Configure a rule that flags file download events with the highest risk score, regardless of time frame.
  2. Create a frequency-based YARA-L detection rule that assigns a risk outcome score and is triggered when multiple suspicious downloads occur within a defined time frame.
  3. Configure a single-event YARA-L detection rule that assigns a risk outcome score and is triggered when a user downloads a large number of files in 24 hours.
  4. Enable default curated detections, and use automatic alerting for single file download events.

Answer(s): B

Explanation:

The correct approach is to create a frequency-based YARA-L detection rule in Google SecOps. Frequency- based rules allow you to detect repeated suspicious behavior, such as multiple file downloads within a short time window, and assign higher risk outcome scores accordingly. This ensures anomalies are prioritized based on their frequency and severity, rather than flagging isolated single events.



You are implementing Google Security Operations (SecOps) at your organization. You discover that the current detection rules are too noisy. Due to the high volume of alerts, some true positives might be missed. You want to ingest additional context sources to reduce false positives in your security detections and to improve the overall positive ratio of the alerts.
What should you do?

  1. Ingest high-value asset (HVA) data from your configuration management database (CMDB) system to increase the priority of the alerts based on the sensitivity of the assets found in the detection rules.
  2. Ingest dark web forum handlers from your threat intelligence system to match dark web principals within the detection rules.
  3. Ingest IOCs from your threat intelligence system to validate the IP addresses, domains and hashes with the detection rules.
  4. Ingest tactics, techniques, and procedures (TTPs) from your threat intelligence system to validate the processes and tools with the detection rules.

Answer(s): A

Explanation:

Ingesting high-value asset (HVA) data from the CMDB allows Google SecOps to prioritize alerts based on the sensitivity and criticality of the affected systems. This reduces noise by helping analysts focus on detections involving critical assets, improving the signal-to-noise ratio and ensuring true positives on important systems are not missed.



You are developing a new detection rule in Google Security Operations (SecOps). You are defining the YARA-L logic that includes complex event, match, and condition sections. You need to develop and test the rule to ensure that the detections are accurate before the rule is migrated to production. You want to minimize impact to production processes.
What should you do?

  1. Develop the rule logic in the UDM search, review the search output to inform changes to filters and logic, and copy the rule into the Rules Editor.
  2. Use Gemini in Google SecOps to develop the rule by providing a description of the parameters and conditions, and transfer the rule into the Rules Editor.
  3. Develop the rule in the Rules Editor, define the sections the rule logic, and test the rule using the test rule feature.
  4. Develop the rule in the Rules Editor, define the sections of the rule logic, and test the rule by setting it to live but not alerting. Run a YARA-L retrohunt from the rules dashboard.

Answer(s): A

Explanation:

The safest way to minimize production impact is to develop and refine the rule logic in UDM search first. By running searches and reviewing outputs, you can iteratively tune filters and conditions until the detections are accurate. Once validated, you then copy the tested query into the Rules Editor. This approach ensures accuracy without risking false positives or unnecessary load in production.



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