GCP Professional Cloud Security Engineer Sample Questions -PCSE‑001 ( 2026 )

Crack the GCP Professional Cloud Security Engineer certification with this expert-crafted set of GCP Professional Cloud Security Engineer Sample Questions, aligned with the PCSE‑001 exam format. Whether you're reviewing with GCP security engineer practice exams, solving exam questions, or working through full-length Google Cloud security practice tests, this resource helps you build deep understanding across IAM, VPC security, data protection, and incident response. These questions simulate real-world security scenarios, providing an ideal prep experience for aspirants pursuing the Google Cloud Security Engineer certification. Pair these with GCP security certification dumps, mock tests, and high-yield practice sets to increase your pass rate and confidently earn your credential.

GCP Professional Cloud Security Engineer Sample Questions List :

1. You are investigating a security alert that indicates potential lateral movement in your Google Cloud environment. Security Command Center (SCC) has flagged unusual permissions granted across multiple projects. You want to determine how the compromised principal gained elevated access in the first place. What is the most effective approach to perform root cause analysis using native Google Cloud security tools?

1. Use SCC’s Findings Explorer to trace the IAM policy changes by querying audit logs directly within SCC

2. Create a metric-based alert in Cloud Monitoring to flag IAM privilege escalations

3. Enable Security Health Analytics to start collecting misconfiguration data

4. Export all findings to BigQuery and use manual filtering to identify recent permissions changes

2. Your team has implemented log ingestion from all Compute Engine VMs into Cloud Logging. You’ve noticed that when a VM is stopped or misconfigured, its logs stop appearing, leaving a blind spot in your security telemetry. To mitigate this, you want to configure an alert that flags when expected logs are not received. Which of the following is the most appropriate setup?

1. Schedule a daily Pub/Sub message from the VM to verify activity and monitor Pub/Sub delivery metrics

2. Configure an alert based on the absence of log entries from the VM over a defined interval using logs-based metrics

3. Set an alert policy on the CPU utilization metric to detect when it reaches zero

4. Use the Ops Agent on the VM and monitor for memory usage drops

3. Your SOC receives frequent alerts from Security Command Center (SCC) Event Threat Detection indicating access attempts to a sensitive Cloud Storage bucket. Upon investigation, your team confirms that the traffic originates from an internal data processing pipeline operating as expected. You suspect these repetitive alerts are false positives. What should you do to systematically reduce these false positives while maintaining detection coverage?

1. Disable the ETD rule for Cloud Storage to avoid alert fatigue

2. Analyze the alert frequency, update your detection logic with allowlisted patterns, and document alert suppression criteria

3. Add the source IP addresses to an SCC exclusion rule and tag them as internal

4. Forward all ETD alerts to BigQuery for future threat hunting but take no immediate action

4. A new threat intelligence report from Google Threat Intelligence (GTI) warns of a campaign using a specific IP address range to scan for public-facing Compute Engine instances with open SSH ports. As a security engineer, what is the most effective proactive hunting query to run?

1. Analyze firewall rules for any rule allowing ingress from the reported IP range.

2. Review Security Command Center findings for misconfigured IAM roles.

3. Query VPC Flow Logs for traffic from the malicious IP range on port 22.

4. Check Cloud Billing reports for unexpected network egress.

5. Your organization uses Security Command Center Premium to detect misconfigurations and threats, and has recently deployed a network-based Intrusion Detection System on select Virtual Private Cloud networks. To improve detection accuracy and streamline investigations, you are asked to integrate SCC with other Google Cloud services and ensure incidents are automatically enriched with network-level insights and forwarded to a centralized threat investigation tool. Which approach best meets these requirements?

1. Enable SCC Premium and use Google SecOps to automatically correlate SCC findings with IDS alerts for deeper investigation.

2. Configure SCC findings to be exported directly to a third-party SIEM via Pub/Sub and use Dataflow to enrich them with IDS logs.

3. Use Event Threat Detection to replace SCC and IDS entirely for real-time threat correlation.

4. Set up Cloud Logging to export VPC Flow Logs and SCC findings to a BigQuery dataset for manual correlation.

6. A suspicious login to a sensitive BigQuery dataset triggers an alert. The SOC engineer initiates the incident response playbook and begins enrichment steps. You want to prioritize enrichments that offer strategic value based on common attack tactics seen in prior threat intelligence reports on data exfiltration campaigns. Which enrichment action provides the most actionable intelligence early in the investigation?

1. Checking Cloud Logging for the number of API calls made by the user

2. Cross-referencing the source IP address against VirusTotal’s threat actor attribution

3. Performing WHOIS lookup on the IP address to identify the ISP

4. Reviewing the labels of the BigQuery dataset for environment classification

7. A security engineer is a using a new threat intelligence feed with Indicators of Compromise (IOCs) to enhance their detection capabilities. They want to create a detection rule that automatically matches these IOCs against their ingested logs in Google Cloud to generate findings in Security Command Center. Which SCC feature should they configure?

1. Event Threat Detection (ETD) custom detector

2. Web Security Scanner

3. Security Health Analytics (SHA)

4. Container Threat Detection

8. Your CISO requests a report that shows trends in high-severity security findings over time across all projects. These findings are ingested into Google SecOps via Security Command Center (SCC). What is the most maintainable and scalable method to satisfy this request?

1. Use GKE Metrics Server to generate cluster-level findings visualizations.

2. Use Looker Studio with BigQuery exports of SCC findings to build automated dashboards and reports.

3. Create a Cloud Monitoring dashboard using custom metrics pushed from SCC API queries.

4. Export findings to a CSV file weekly and manually compile graphs in Google Sheets.

9. During an active incident response, a security operations team is using a case management system. The team has contained the threat and is now in the recovery phase. What is a key activity to document and track in the case management system at this stage?

1. Implementing long-term remediation actions to prevent recurrence.

2. Notifying customers of the incident.

3. Starting the forensic acquisition of disk images.

4. Performing root cause analysis.

10. Your organization has experienced a surge in phishing emails containing malicious links. The security operations team wants to formalize their response to such incidents to ensure quick and consistent handling. You are tasked with developing a response playbook for phishing campaigns. Which element is the most critical to include in the initial steps of the phishing incident response playbook?

1. Isolate impacted user accounts and collect email headers and samples.

2. Perform a post-mortem analysis to assess business impact.

3. Immediately escalate the incident to executive leadership for visibility.

4. Reconfigure mail routing policies to allow all attachments for further inspection.

11. Your organization has deployed resources across multiple Google Cloud projects and uses third-party SaaS platforms that log authentication activity. You are leading a threat hunting exercise to detect signs of credential abuse and session hijacking across this distributed environment. Which of the following is the best approach?

1. Monitor only Identity and Access Management (IAM) policy changes in the GCP Admin Activity logs.

2. Investigate login anomalies in Identity-Aware Proxy (IAP) logs only within the primary GCP project.

3. Use Google Security Operations with UDM to normalize and correlate logs from all GCP projects and external SaaS authentication sources.

4. Configure Eventarc to trigger alerts for all login failures across your GCP projects.

12. Your organization suspects that a compromised service account has been used to exfiltrate data from Cloud Storage to an unknown external IP. You are tasked with identifying any signs of unusual data transfer patterns or known IOCs using Google Cloud’s native tools. Which of the following is the best method to begin your investigation?

1. Use Cloud Monitoring to review alert policies triggered by the service account.

2. Use Log Analytics to analyze service account permission changes in IAM logs.

3. Use Google SecOps to correlate Cloud Storage access logs with known IOC IP addresses.

4. Use BigQuery to query VPC Flow Logs for access to Cloud Storage buckets.

13. Your SOC team receives a new batch of threat intelligence that includes recently published malicious IP addresses and domain names associated with an active malware campaign. You want to search for any evidence of compromise in your Google Cloud environment using ingested telemetry from Cloud Audit Logs, VPC Flow Logs, and DNS logs. Which approach should you use to efficiently search for these IOCs within Google SecOps?

1. Create a detection rule that hardcodes all IOCs and scans only new incoming logs.

2. Upload the IOCs into a reference list and use a retrospective search in Google SecOps to look across historical telemetry.

3. Use BigQuery to manually upload the IOCs and write ad hoc queries across exported logs.

4. Use Cloud Monitoring to build custom metrics that count log entries containing the IOCs.

14. Your security operations team is designing a threat detection strategy that enables real-time response to potentially malicious behavior across multiple GCP projects. They need to correlate data from various sources to prioritize incidents like misconfigured firewalls, public buckets, or external IPs on sensitive workloads. Which telemetry source should be considered the central aggregator to prioritize and surface these types of risks across projects?

1. Google Security Operations (SecOps)

2. Cloud Logging

3. Security Command Center (SCC)

4. Google Cloud IDS

15. After reviewing SCC misconfiguration findings and detecting repeated failed login attempts from unfamiliar IP ranges, your SOC receives GTI alerts identifying a known threat actor using brute-force tactics to access GCP-hosted web applications. You’re tasked with performing threat hunting across environments to determine if the environment has been compromised. Which hypothesis best aligns with the observed data and should guide your investigation?

1. Monitoring tools are generating false positives due to a recent upgrade in the logging format.

2. The IAM roles for GCP workloads are misconfigured due to incomplete Terraform deployments.

3. A known threat actor is attempting credential stuffing or brute-force attacks on exposed endpoints.

4. A misconfigured Cloud Armor policy has inadvertently blocked internal application traffic.

16. You are writing a detection rule in Google SecOps to identify potential account compromise. You want to reduce false positives by incorporating contextual awareness. Which of the following strategies best leverages entity/context data from the entity graph to enhance detection accuracy?

1. Identify any logins outside of regular business hours as suspicious

2. Compare login behavior to the user’s historical geolocation and device usage patterns

3. Trigger alerts only when multiple users fail login attempts within 10 minutes

4. Match login events from uncommon IP addresses against a fixed list of known bad IPs

17. Your SOC is investigating a Compute Engine VM that initiated outbound connections to a domain flagged in your threat intelligence feed. The asset in question is used for batch processing in a healthcare application and typically only connects to internal services. Which of the following is the most appropriate next step in context-aware threat investigation?

1. Immediately shut down the asset to prevent further communication

2. Analyze the baseline network behavior of the asset to determine whether such outbound traffic is typical

3. Confirm that the asset’s firewall rules allow outbound traffic to the flagged domain

4. Create a policy to block all outbound traffic from the asset

18. Your security team has built a new response playbook to address potential abuse of overly permissive IAM roles. During a simulated test, a detection alert identifies a service account listing secrets from multiple unrelated projects. Which step should be defined in the "containment" phase of this IAM abuse playbook?

1. Revoke affected IAM permissions and rotate associated service account credentials.

2. Run the gcloud iam list-testable-permissions command to validate permissions.

3. Create a new IAM policy binding and document justification for broad access.

4. Archive logs from Cloud Audit Logs to Coldline storage for retention.

19. A container in a GKE cluster shows signs of compromise, with unexpected outbound traffic to suspicious IPs. The container is part of a mission-critical workload. You are tasked with containing the threat without disrupting the entire service. What is the most effective isolation strategy in this situation?

1. Drain the node where the container is running and cordon it from the cluster.

2. Apply a Kubernetes NetworkPolicy to deny all egress traffic from the affected pod.

3. Delete the compromised container and trigger auto-scaling to restore service.

4. Stop the entire GKE node pool hosting the container to ensure complete isolation.

20. You are designing a data pipeline for a Google Cloud project that processes and stores sensitive customer data. Your security policy requires that data must be encrypted using a customer-supplied encryption key (CSEK) and that keys must not be managed by Google. The pipeline writes processed data into BigQuery and Cloud Storage. What is a limitation you must account for when planning encryption and access?

1. Cloud Storage cannot support CSEK for writing data

2. CSEK allows automatic key rotation through Cloud KMS

3. You cannot use IAM policies with Cloud Storage when CSEK is enabled

4. BigQuery does not support CSEK and requires CMEK or Google-managed keys

21. Your security team detects unusual outbound connections from a Compute Engine VM. Initial triage suggests the instance might be compromised. You are tasked with collecting evidence to support a forensic investigation while minimizing the risk of tampering or data loss. Which of the following is the most appropriate approach to collect forensic evidence while preserving integrity and scope in Google Cloud?

1. Use OS Login to SSH into the instance and run memory dump scripts to capture RAM content before powering off the VM.

2. Clone the VM using the image feature, deploy it in an isolated VPC, and observe its behavior to identify attacker tools and techniques.

3. Immediately stop the VM, take a disk snapshot, and export the snapshot to Cloud Storage for forensic imaging.

4. Take a snapshot of the attached persistent disk while the VM is still running and allow the instance to continue operating to avoid service disruption.

22. You’ve recently received a threat intelligence report from your threat intel provider indicating an active campaign using a newly discovered command-and-control (C2) domain. You want to proactively search for any evidence that your environment may have communicated with this domain. What is the most effective approach using Google Cloud native tools to begin threat hunting based on this intelligence?

1. Enable Event Threat Detection (ETD) and wait for detections to appear

2. Set up a Google Cloud Armor policy to block the C2 domain in the future

3. Apply a VPC Service Controls perimeter to prevent future data exfiltration

4. Search for the C2 domain across Cloud Logging using Logs Explorer with a custom filter

23. Your security team suspects that an advanced persistent threat (APT) group is exfiltrating data from a GCP project. You’ve been asked to lead a proactive threat hunting operation. You want to focus on identifying suspicious behavior rather than responding to alerts. Which of the following is the most effective initial step to begin this threat hunting activity in the Google Cloud environment?

1. Use Google SecOps to search for anomalous login activity patterns across Identity and Access logs.

2. Use IAM policy analysis to validate user permissions and enforce least privilege.

3. Export all logs to BigQuery and rely on Looker dashboards for compliance auditing.

4. Wait for SCC Event Threat Detection alerts and investigate them using Google SecOps.

24. Your organization is using Google SecOps to develop custom detection rules. You want to detect connections to IP addresses associated with known threat actors. Your team maintains an up-to-date reference list of high-risk IPs obtained from threat intelligence feeds. You want to ensure the detection rule flags any match with these IPs during VPC network activity. Which approach should you take to meet this requirement effectively?

1. Export all VPC Flow Logs to BigQuery and query them manually for matches against a CSV list of high-risk IPs.

2. Write a rule that uses regex pattern matching to compare IP addresses in VPC Flow Logs to hardcoded values in the rule.

3. Create a detection rule that uses the in operator to compare destination IPs against a dynamic reference list stored in Google SecOps.

4. Use Firewall Rules to block all known malicious IPs and log all blocked traffic for manual review.

25. Your security operations team needs to ingest logs from multiple sources, including Google Cloud Audit Logs, VPC Flow Logs, and third-party SaaS APIs, into a central location for correlation and threat detection. The team wants to use native GCP services to ingest and process logs with minimal custom scripting and maximum integration with security tooling. Which solution best supports this requirement?

1. Use log sinks to export logs to Cloud Storage, and periodically batch-import them into a security platform.

2. Route logs using log sinks to Pub/Sub and use a Log Router integration with a supported SIEM or SOAR via a subscription.

3. Use Pub/Sub for all logs, write a custom parser in Cloud Functions, and forward them to a third-party SIEM via HTTP.

4. Export all logs to BigQuery, use scheduled queries to parse them, and build dashboards for detection rules.

26. A security engineer is investigating a possible data exfiltration incident involving a Compute Engine VM. They want to understand if any large outbound connections were made to unknown IP addresses and correlate those activities with user account actions. Which combination of tools should the engineer use to provide end-to-end observability of network activity and user behavior?

1. VPC Flow Logs and Identity-Aware Proxy

2. VPC Flow Logs and Cloud Audit Logs (Data Access)

3. Firewall Rules Logging and Cloud NAT Logs

4. Cloud Logging exclusion filters and Cloud Storage audit logs

27. A security operations team is ingesting logs from various sources, including on-premises systems and Google Cloud, into Google SecOps. The team notices that different log sources use different field names for the same data, such as source_ip, src_ip, and client_ip. What is the primary benefit of normalizing these fields in Google SecOps?

1. It automatically enriches logs with threat intelligence data.

2. It reduces the total volume of ingested log data.

3. It ensures logs are stored in an encrypted format.

4. It allows for consistent searches and unified detections across all log sources.

28. A security engineer has configured a new alerting policy in Cloud Monitoring for a critical service. The policy is configured with a Notification channel for email. However, the engineer also wants to send these alerts to a custom webhook to trigger an automated remediation script. How can they add this new notification method?

1. Add a new notification channel for the webhook to the existing alerting policy.

2. Export the alerts to a BigQuery table and trigger the webhook from there.

3. Create a new alerting policy and link it to a webhook notification channel.

4. Modify the existing email notification channel to include the webhook URL.

29. You are developing a new detection rule to monitor for suspicious IAM role changes. You want to analyze audit logs in real-time for iam.roles.update events where a custom role with elevated permissions is granted to a user outside of a predefined group. Which of the following is the most efficient method to process these logs and trigger an alert?

1. Creating a log-based metric and a corresponding alerting policy.

2. Using scheduled BigQuery queries to analyze logs.

3. Manually reviewing Cloud Logging entries for the specific event.

4. Exporting logs to a Pub/Sub topic and processing them with a self-hosted application.

30. Your organization has deployed several critical applications on Google Cloud using Compute Engine and GKE. Recently, your SOC has been struggling with alert fatigue due to a high volume of low-priority security findings. You are tasked with enhancing detection and response to focus on the most relevant threats while minimizing noise. What is the most effective way to reduce alert fatigue and prioritize actionable threats using Google Cloud’s native tools?

1. Deploy custom alerting rules in Cloud Monitoring for every possible IAM permission change

2. Implement Security Command Center Premium and configure event threat prioritization based on severity levels

3. Increase the logging verbosity of all services to ensure no event is missed

4. Enable VPC flow logs and export them to BigQuery for manual querying and threat detection

31. During a recent investigation, your team identified a suspicious binary running on a Compute Engine VM. The binary is not recognized in threat intelligence databases, but its behavior and origin are concerning. You want to detect future occurrences of similar rare processes using scalable and automated techniques. Which strategy would best support detecting such low-prevalence binaries across your cloud fleet?

1. Use Security Health Analytics to identify known malware signatures on GCE instances.

2. Enable OS Login and monitor audit logs for rare usernames accessing the VM.

3. Write a YARA-L rule that flags process hashes not seen in internal logs over the past 30 days and not present in external threat feeds.

4. Build a scheduled query in BigQuery to join Cloud Audit Logs and list all user-installed packages weekly.

32. You are investigating a potential insider threat. A series of alerts from Google SecOps show unusual read activity from Cloud Storage buckets labeled “confidential”. You want to validate whether this access pattern is malicious or expected. Which approach will give you the most context-rich view of the situation using Google-native tooling?

1. Use Security Command Center to view asset inventory and check for public exposure

2. Change the IAM policy on the bucket to deny all access while you investigate

3. Use Google SecOps to construct a timeline of access events by querying Cloud Audit Logs and IAM logs for the suspected principal

4. Enable Data Loss Prevention (DLP) API on the bucket and rerun the alert to see if any sensitive data was accessed

33. A SOC lead is building an escalation path for data exfiltration alerts in Google SecOps. The workflow must ensure that if an alert remains unassigned after 15 minutes, it is escalated to a Tier 2 analyst. Additionally, if no action is taken within 30 minutes, the case should be auto-prioritized to “Urgent” and reassigned. Which configuration best fulfills these escalation requirements?

1. Use case SLA policies and automation rules in Google SecOps to auto-escalate and reassign based on time thresholds

2. Set up a Google Cloud Monitoring alert on log activity and manually reassign unacknowledged cases

3. Rely on BigQuery scheduled queries to identify stale cases and notify via Slack

4. Define playbook steps that include human approval for every alert before escalation

34. You are implementing a detection engineering pipeline in your GCP environment. Your goal is to identify lateral movement activity involving service accounts accessing multiple GKE clusters in a short time span, which deviates from baseline behavior. You want to prioritize these detections based on risk. What is the most effective approach to achieve this using Google Cloud tools?

1. Use Google SecOps to detect access anomalies using Risk Analytics and prioritize high-risk service account behavior.

2. Query Cloud Audit Logs in Logs Explorer to find IAM role changes across clusters.

3. Enable OS Login to restrict SSH-based access between nodes in GKE.

4. Set up a budget alert in Cloud Billing for unexpected compute costs across clusters.

35. Your SecOps team is building a baseline of user activity by correlating login events across different systems. While evaluating identity-related logs, you observe that user.name appears as an email address in some sources (e.g., alice@example.com) and as a shortname in others (e.g., alice). You want to ensure consistent enrichment and user tracking across your detection pipelines in Google SecOps. Which action should you take to ensure reliable correlation and enrichment of user identity across different log sources?

1. Normalize usernames during log ingestion using a Cloud Function in Pub/Sub

2. Apply a log exclusion filter to remove logs with unmatched usernames

3. Use aliasing fields to map user.name values to a canonical username in enrichment rules

4. Use Event Threat Detection to automatically correlate usernames from different sources

36. A data science team in your organization needs to read BigQuery tables from a dataset in a different project. The dataset resides in Project A, and the team works within Project B. You want to use IAM best practices to grant read-only access to the tables without granting broader dataset or project permissions. What is the recommended way to grant access?

1. Grant the roles/bigquery.admin role to the users on Project A

2. Assign the roles/viewer role at the project level in Project A

3. Share the dataset using a public link and allow all users to access it

4. Assign the roles/bigquery.dataViewer role on the dataset to the users or group from Project B

37. A security engineer is tasked with creating a Cloud Monitoring alert for suspicious activity in their Google Cloud organization. The alert should trigger if a user performs more than 50 "delete" operations on Cloud Storage objects within a 5-minute window. Which log-based metric and threshold would best achieve this?

1. A counter metric on storage.objects.get events with a threshold of 50.

2. A counter metric on storage.objects.delete events with a threshold of 50.

3. A distribution metric on storage.objects.list events with a threshold of 50.

4. A counter metric on storage.buckets.delete events with a threshold of 1.

38. Your company has adopted multiple GCP services, and your team uses Security Command Center to monitor potential threats. However, your CISO wants to move toward a more automated response model for high-confidence detections (e.g., leaked service account keys or public storage buckets) to reduce mean time to respond (MTTR). Which solution most effectively aligns with this goal?

1. Configure SCC to export high-severity findings to Pub/Sub and trigger Cloud Functions that execute remediation tasks.

2. Use Google Workspace Admin audit logs to detect unusual document sharing behavior.

3. Schedule a weekly manual review of SCC findings and notify owners via Google Chat.

4. Use Cloud Billing alerts to detect usage spikes and infer potential compromises.

39. Your organization is designing an automated response playbook in Google SecOps to handle credential leakage incidents. When a service account's key is found on a public GitHub repository, the team wants to automate containment while avoiding accidental disruption of production workloads. Which step is the most appropriate candidate for automation in the playbook?

1. Automatically remove IAM roles from all users in the project as a precaution.

2. Automatically disable the exposed key and notify the security team.

3. Automatically shut down all Compute Engine instances using the affected service account.

4. Automatically delete the service account associated with the exposed key.

40. Your security operations team has received an alert about a known C2 domain linked to recent phishing activity. You want to verify if any internal users have connected to this domain and reconcile this with asset activity to understand the blast radius and potential compromise. What is the most effective way to reconcile this external threat intelligence with user and asset activity in your Google Cloud environment?

1. Review the Web Security Scanner findings in SCC for URLs matching the C2 domain.

2. Check Cloud Billing reports for unusual egress charges indicating large data transfers.

3. Query VPC flow logs in BigQuery for connections to the domain and enrich with Cloud Identity data for user attribution.

4. Enable SCC’s default detectors and wait for automated alerts.

41. You are configuring alerting policies in Cloud Monitoring for your organization’s App Engine-based application. A recent alert storm due to short-lived CPU spikes has led to alert fatigue in your team. You want to ensure that alerts are triggered only if sustained issues occur, and reduce noise from transient conditions. What should you do to reduce alert noise while maintaining timely awareness of legitimate issues?

1. Set a static threshold of 75% CPU and disable notifications for minor incidents

2. Enable a lower threshold (e.g., 50%) to detect issues earlier and investigate manually

3. Use alerting conditions with an aggregation period and a minimum window duration of 5 minutes

4. Set up a log-based alert only for ERROR-level messages

42. A security engineer is tasked with creating a detection rule to identify suspicious login activity in their Google Cloud environment. They want to detect brute-force attacks by monitoring for a high number of failed login attempts from a single IP address within a short time frame. Which of the following approaches is most effective for this detection use case?

1. Manually review all LOGIN_FAILURE events in Cloud Logging on a daily basis.

2. Develop a correlation rule that aggregates LOGIN_FAILURE events based on the source IP address and triggers a detection when a predefined threshold is exceeded.

3. Write a custom search that looks for LOGIN_FAILURE events within a 24-hour window.

4. Create a simple log-based alert that triggers on every LOGIN_FAILURE event.

43. A security analyst wants to identify low-prevalence domains that a user's machine is communicating with, which are not listed in public threat intelligence feeds. To find these rare connections using the Google Cloud Security Analytics Platform, what type of YARA-L rule logic would be most effective?

1. Anomaly detection rule using a baseline.

2. A rule correlating with a known malware family.

3. Simple IOC (Indicator of Compromise) matching rule.

4. A rule using a simple regex for domain names.

44. Your organization wants to create a detection rule that identifies access to sensitive data from a geographically sanctioned country, as defined by a security operations reference list named sanctioned_countries. What type of a field in a log would be most critical to map in your rule to effectively use this reference list?

1. user.email

2. event.action

3. http.request.method

4. client.ip

45. Your organization ingests logs from multiple sources into Google Cloud SecOps, including VPC Flow Logs, GKE Audit Logs, and third-party firewall logs. You’ve noticed that similar security-relevant fields (e.g., source IP, destination IP, and action) appear under different field names depending on the source. The team wants to perform consistent threat detection and analytics. Which approach within Google Cloud SecOps will best help normalize these fields for consistent detection rule creation?

1. Create BigQuery views that map all fields to a standard schema post-ingestion

2. Use custom ingestion parsers to transform fields during the ingestion pipeline

3. Export all logs to a Cloud Storage bucket and write a Cloud Function to reformat them manually

4. Utilize Unified Data Model (UDM) mapping during ingestion to standardize field names and types

46. Your organization is piloting a new threat intel integration that pushes known malicious domain names to your security team. To detect their presence in DNS queries, you decide to build a custom Event Threat Detection rule in SCC. What is a required configuration step when defining this custom detector to ensure it triggers accurately?

1. Use SCC built-in detectors for domain detection and configure threat lists in the SCC UI.

2. Define a custom detector with a log type filter for dns.googleapis.com, and use matches_any with your domain list in the conditions.

3. Add the custom domains to a GCP allowlist and enable SCC anomaly detection.

4. Enable Data Loss Prevention (DLP) API and configure it to forward domain matches to SCC.

47. Your organization’s security policy mandates that all Compute Engine instances must use the latest approved OS image with Shielded VM features enabled. During a quarterly audit, you are tasked with detecting deviations from this policy in real time and integrating findings into your detection pipeline for posture management. Which solution most effectively fulfills this requirement using Google Cloud’s native tools?

1. Rely on Forseti Security to scan for misconfigurations and report non-compliance.

2. Use Security Health Analytics in SCC to define a custom module that continuously scans for outdated OS images and disabled Shielded VM features.

3. Configure Cloud Asset Inventory to export daily snapshots of VM metadata and review them in BigQuery.

4. Enable Cloud Logging and manually parse log entries from Compute Engine API for non-compliant instances.

48. During an investigation, a security analyst uses Google SecOps SIEM to analyze logs from multiple sources. The analyst notices suspicious API calls from a service account. What is the most effective next step to perform a root cause analysis using available security tools?

1. Use Google Cloud console's Activity logs to trace the user who created the service account.

2. Review the service account's IAM policy to check its permissions.

3. Leverage Google SecOps SIEM to correlate the suspicious API calls with other events, such as network logs and audit trails, to identify a pattern.

4. Create a custom dashboard in Google SecOps SIEM to monitor similar API calls.

49. A Security Command Center (SCC) Premium user receives a high-severity finding for a compromised virtual machine. The security team needs to perform a root cause analysis. What is the most effective approach to determine the initial vector of compromise using SCC and other tools?

1. Use Google SecOps SIEM to search for a public IP address that connected to the VM.

2. Analyze the SCC finding details to identify the specific vulnerability exploited.

3. Use SCC's Event Threat Detection to correlate the finding with preceding events and potential attack paths.

4. Review the firewall logs in Cloud Logging to identify unauthorized inbound connections.

50. A security analyst is investigating a potential compromise in their Google Cloud environment. They suspect an attacker is using a compromised service account to access sensitive data in multiple projects. Which of the following is the most effective approach for threat hunting this activity?

1. Review IAM policies for the service account to check for excessive permissions.

2. Use Security Command Center to review all findings related to service accounts.

3. Configure VPC Flow Logs to identify suspicious network traffic from the service account.

4. Create a custom query in BigQuery to analyze Cloud Audit Logs for serviceAccount principals accessing BigQuery tables across projects.

51. Your security team receives a threat intelligence update from GTI (Google Threat Intelligence) indicating that a specific User-Agent string is being used by an APT group in their reconnaissance campaigns. You want to determine whether this User-Agent has appeared in your environment over the past 90 days across multiple GCP projects. Which of the following is the most effective approach to perform this retrohunt?

1. Use Cloud Asset Inventory to list all HTTP requests over the last 90 days.

2. Use the Google SecOps rules engine to scan real-time logs for the specified User-Agent.

3. Create a Cloud Monitoring alert policy with a threshold for the User-Agent string.

4. Export relevant logs to BigQuery and run SQL queries against historical HTTP request logs.

52. A security team is ingesting custom application logs into Google Security Operations. The logs are in a JSON format with nested fields. The team needs to extract a specific value from a nested field to use in a detection rule. What is the most appropriate type of parser to create in Google SecOps?

1. A custom JSON parser.

2. A regular expression (regex) parser.

3. A key-value pair parser.

4. A delimiter-based parser.

53. Your security team recently investigated a breach in which attackers exfiltrated sensitive data by abusing service accounts with excessive permissions and uploading data to an external storage endpoint using a Compute Engine instance. Based on this incident, the team wants to design a new response process to handle similar misuse scenarios. Which process change should be prioritized in the updated response playbook?

1. Replace Cloud Logging with BigQuery export for performance optimization.

2. Integrate VPC Service Controls to restrict data exfiltration paths for sensitive resources.

3. Configure firewall rules to allow all egress traffic for incident analysis.

4. Automatically delete service accounts after 30 days of inactivity.

54. A Security Operations Engineer is tasked with building a detection mechanism to identify suspicious new binaries running on Compute Engine instances that were not seen in the past week and are absent from all threat intelligence sources. Which detection method should the engineer use in Google Security Operations to most effectively surface these binaries for analysis?

1. Use Cloud Armor to block Compute Engine instances from launching binaries outside /usr/bin.

2. Query the BigQuery billing export logs to detect high-cost binaries and flag them as suspicious.

3. Write a policy in Google Security Command Center that prevents the execution of unsigned binaries on Compute Engine VMs.

4. Build a YARA-L rule that flags processes whose SHA256 hash is missing from external threat intel and has not appeared in internal logs over the last 7 days.

55. Your organization has detected anomalous authentication attempts to a critical internal web application hosted on Google Cloud. You are part of the Security Operations team tasked with managing the incident. After verifying the incident and isolating the affected instance, what is the most appropriate next step in your incident response process?

1. Begin forensic evidence collection and preserve logs and memory dumps

2. Notify Google Cloud Support to take over the incident handling

3. Immediately delete the affected VM to stop the attack

4. Reboot the VM to remove any malicious processes from memory

56. A security engineer in a Google SecOps environment wants to create a new detection rule to identify potential command-and-control (C2) communication. The rule should prioritize alerts for network connections to domains or IP addresses that are known to be malicious. What is the most effective way to leverage threat intelligence for this scoring?

1. Ingest a threat intelligence feed of known C2 infrastructure and use it as a reference list within the detection rule's logic.

2. Manually add a list of malicious IPs to a lookup table that the rule checks.

3. Write a rule that triggers on any DNS query for a non-Google domain.

4. Create a simple rule that triggers on any network connection to an external IP.

57. An external threat intelligence feed notifies your organization about a set of SHA256 file hashes linked to ransomware activity. You want to determine if any of these files have been executed, downloaded, or transferred within your Google Cloud environment over the past 30 days. How should you best proceed using Google SecOps?

1. Enable Access Transparency and inspect service access logs for any mentions of the provided hashes.

2. Create a static detection rule with each SHA256 hash and monitor for future occurrences only.

3. Load the hashes into a reference list and run a search across existing telemetry using file.hash.sha256 field.

4. Rely on VPC Flow Logs to detect file downloads by searching for hash values in IP packet data.

58. Your threat intel team shared an IOC report containing SHA256 hashes related to a recent malware campaign. You need to check if any of these hashes were seen in your organization over the past 60 days. You’ve already exported your Cloud Logging data to BigQuery. Which log type and query logic should you prioritize for effective detection?

1. Query OS Login logs for user activity tied to file hash values

2. Query IAM policy logs for file modification activity involving known hashes

3. Query Data Access logs for compute.instances.start events matching SHA256 hashes

4. Query File Integrity Monitoring (FIM) logs exported from Cloud Logging for matching SHA256 file hashes

59. During a routine inspection of your SecOps environment, you notice that alerts from a workload in one region stopped arriving. You suspect an issue in the Cloud Logging pipeline. You want to confirm whether logs from that region are being properly ingested into Cloud Logging. Which action using Cloud Logging provides the most direct evidence of a regional ingestion issue?

1. Check for recent entries in the activity log within the Admin Activity audit log

2. Check GKE node metrics in Cloud Monitoring to confirm container health in the region

3. Use Log Explorer to filter logs by region and time range, then check for absence of expected entries

4. Review Security Command Center findings for that region

60. A security operations team uses Google Cloud Security Operations to ingest logs from multiple sources. They need to be alerted if a critical data source, such as VPC Flow Logs from a specific project, stops sending logs, indicating a potential pipeline failure or malicious tampering. What is the most effective way to configure a detection for this "silent source" issue?

1. Implement a log-based metric in Cloud Monitoring that counts events from the source and alerts if the count drops to zero.

2. Set up a custom Event Threat Detection detector in SCC for this purpose.

3. Use a Security Command Center finding to detect the log flow stoppage.

4. Create a dashboard to manually check the log volume from the source.

FAQs

1. What is the GCP Professional Cloud Security Engineer certification?

This certification validates a professional’s ability to design, implement, and manage secure infrastructure on Google Cloud.

2. Is GCP Cloud Security Engineer certification worth it?

Yes, it's highly valuable for cybersecurity professionals working in cloud environments, especially with Google Cloud.

3. What does a GCP Cloud Security Engineer do?

They design secure infrastructure, ensure compliance, manage identity and access, and protect workloads in the cloud.

4. What are the benefits of becoming a GCP Cloud Security Engineer?

Benefits include higher salary potential, recognition in the cloud security field, and access to advanced job roles.

5. Who should take the GCP Professional Cloud Security Engineer certification?

Security professionals, cloud architects, and engineers who focus on secure cloud infrastructure.

6. How difficult is the GCP Cloud Security Engineer exam?

The exam is moderately difficult, requiring both theoretical knowledge and practical cloud security experience.

7. What is the format of the GCP Cloud Security Engineer exam?

The exam includes multiple-choice and multiple-select questions.

8. How many questions are on the GCP Cloud Security Engineer exam?

The exam typically contains 50–60 questions.

9. Is the GCP Cloud Security Engineer exam multiple choice or scenario-based?

It is primarily multiple choice with scenario-based case studies.

10. What topics are covered in the GCP Cloud Security Engineer exam?

Topics include identity and access management, data protection, compliance, network security, and workload protection.

11. How do I prepare for the GCP Professional Cloud Security Engineer exam?

You can prepare using CertiMaan's practice tests and Google Cloud's official training.

12. What are the best resources to study for GCP Cloud Security Engineer?

CertiMaan provides curated dumps and mock tests. Google Cloud’s learning portal offers training paths and documentation.

13. Are there free practice tests for GCP Cloud Security Engineer certification?

Yes, CertiMaan provides free sample questions. Google Cloud offers practice materials on their official site.

14. How long does it take to prepare for GCP Cloud Security Engineer exam?

On average, it takes 6 to 8 weeks of study with consistent effort.

15. Can I pass GCP Cloud Security Engineer without experience?

It’s possible, but hands-on experience significantly improves your chances of passing.

16. How much does the GCP Cloud Security Engineer certification cost?

The exam costs $200 USD.

17. Are there any prerequisites for GCP Professional Cloud Security Engineer?

There are no official prerequisites, but prior experience with GCP and cloud security is recommended.

18. How do I register for the GCP Cloud Security Engineer exam?

Register through Google Cloud's official certification site.

19. Can I retake the GCP Cloud Security Engineer exam if I fail?

Yes, you can retake the exam after a 14-day waiting period.

20. What is the passing score for the GCP Cloud Security Engineer exam?

Google does not publish an exact passing score, but 70% is generally considered a safe benchmark.

21. How is the GCP Cloud Security Engineer exam scored?

The exam uses a scaled scoring system. Results are pass/fail without specific breakdowns.

22. How long is the GCP Cloud Security Engineer certification valid?

It is valid for two years.

23. How do I renew my GCP Cloud Security Engineer certification?

You must retake the current version of the exam to renew.

24. What is the average salary of a GCP Cloud Security Engineer?

In the U.S., salaries typically range from $110,000 to $150,000 annually.

25. What jobs can I get with a GCP Cloud Security Engineer certification?

You can work as a cloud security engineer, cloud architect, or security consultant.

26. Does Google hire GCP Cloud Security Engineers?

Yes, Google and many other tech firms hire professionals with this certification.

27. Is GCP Cloud Security Engineer better than AWS Security certification?

It depends on your target cloud environment; both are valuable and respected in the industry.

28. Can GCP Cloud Security Engineer certification help in a cybersecurity career?

Absolutely. It’s an excellent credential for progressing in cloud-focused cybersecurity roles.