Google Professional Security Operations Engineer Practice Exam

Google Professional Security Operations Engineer Practice Exam

 

About the Google Professional Security Operations Engineer Exam

A Google Cloud Certified Professional Security Operations Engineer detects, monitors, analyzes, investigates, and responds to security threats against workloads, endpoints, and infrastructure. This individual uses Google Cloud resources to protect an enterprise environment and is proficient in writing detection rules, log prioritization and ingestion, orchestration, and response automation. Further, this individual has experience leveraging posture and threat intelligence for detection and response.

Skills Assessed

The Professional Security Operations Engineer exam assesses your ability to conduct:

• Platform operations
• Data management
• Threat hunting
• Detection engineering
• Incident response
• Observability

Exam Details

• Length: 2 hours

• Registration fee: $200 (plus tax where applicable)
• Language: English
• Exam format: 50-60 multiple-choice and multiple-select questions

Exam delivery method:

• a. Take the online-proctored exam from a remote location. Review the online testing requirements.
• b. Take the onsite-proctored exam at a testing center. Locate a test center near you.

Prerequisites: None

• Recommended experience: 3+ years of security industry experience, including 1+ years using Google Cloud security tooling
• Certification renewal: Candidates may renew their certification within the renewal eligibility period. For more information about the renewal process, eligibility period, and certification validity timeline, please refer to the Renewal FAQs below.

Google Professional Security Operations Engineer Course Outline

The Google Professional Security Operations Engineer Exam covers the following topics - 

Domain 1: Platform Operations (approx 14% )

1.1 Enhancing Detection and Response

• Prioritizing telemetry sources (e.g., SCC, Google SecOps, GTI, Cloud IDS) to detect incidents or misconfigurations
• Integrating multiple tools (e.g., SCC, Google SecOps, GTI, Cloud IDS, third-party systems) in the security architecture to improve detection
• Justifying the use of overlapping tools based on requirements
• Evaluating effectiveness of existing tools to identify coverage gaps and mitigate threats
• Assessing automation and cloud-based tools to strengthen detection and response

1.2 Configuring Access

• Configuring user and service account authentication for security tools (e.g., SCC, Google SecOps)
• Setting authorization for feature access using IAM roles and permissions
• Setting authorization for data access using IAM roles and permissions
• Configuring and analyzing audit logs (e.g., Cloud Audit Logs, data access logs)
• Configuring API access for automation in security tools (e.g., service accounts, API keys, SCC, Google SecOps, GTI)
• Provisioning identities via Workforce Identity Federation

Domain 2: Data Management (14%)

2.1 Ingesting Logs for Security Tooling

• Determining approaches for data ingestion in tools (e.g., SCC, Google SecOps)
• Configuring ingestion tools or built-in features (e.g., SCC, Google SecOps)
• Assessing required logs for detection and response (e.g., SCC Event Threat Detection, Google SecOps)
• Evaluating parsers for log ingestion in Google SecOps
• Modifying or extending parsers in Google SecOps
• Applying data normalization techniques from log sources in Google SecOps
• Evaluating and applying new labels for log ingestion
• Managing log ingestion costs

2.2 Identifying a Baseline of User, Asset, and Entity Context

• Identifying relevant threat intelligence within the enterprise environment
• Differentiating event and entity data log sources (e.g., Cloud Audit Logs, Active Directory context)
• Evaluating event and entity data matches for enrichment using aliasing fields

Domain 3: Threat Hunting 19%)

3.1 Performing Threat Hunting Across Environments

• Developing queries to analyze logs and detect anomalies
• Analyzing user behavior to uncover suspicious activity
• Investigating network, endpoints, and services to identify IOCs using Google Cloud tools (e.g., Logs Explorer, Log Analytics, BigQuery, Google SecOps)
• Collaborating with incident response teams to uncover active threats
• Formulating hypotheses from behavior, threat intel, posture, and incident data (e.g., SCC, GTI)

3.2 Leveraging Threat Intelligence for Threat Hunting

• Searching for IOCs in historical logs
• Detecting new attack patterns and techniques in real time using threat intel and risk assessments (e.g., GTI, detection rules, SCC toxic combinations)
• Analyzing entity risk scores to flag anomalous behavior
• Performing retrohunt on historical event data with enriched logs (e.g., Google SecOps rules engine, BigQuery, Cloud Logging)
• Proactively hunting for hidden threats using threat intel (e.g., GTI, detection rules)

Domain 4: Detection Engineering (22%)

4.1 Developing and Implementing Detection Mechanisms

• Reconciling threat intelligence with user and asset activity
• Analyzing logs and events for anomalies
• Detecting suspicious patterns using detection rules and timeline-based searches
• Designing detection rules with risk values (e.g., Google SecOps reference lists)
• Discovering anomalous behavior of assets/users and assigning risk values (e.g., SecOps Risk Analytics, curated rules)
• Designing rules to detect posture or risk profile changes (e.g., SCC SHA, SCC posture management, Google SecOps)
• Identifying rare or unknown processes, domains, and IPs using methods like YARA-L rules or dashboards
• Using entity/context data in rules for accuracy (e.g., Google SecOps entity graph)
• Configuring SCC Event Threat Detection custom detectors for IOCs

4.2 Leveraging Threat Intelligence for Detection

• Scoring alerts by IOC risk level
• Searching for latest IOCs in ingested telemetry
• Measuring repetitive alerts to reduce false positives

Domain 5: Incident Response (21%)

5.1 Containing and Investigating Incidents

• Collecting forensic evidence (e.g., images, artifacts)
• Observing and analyzing incident-related alerts (e.g., SCC, Google SecOps)
• Assessing incident scope using tools (e.g., Logs Explorer, Log Analytics, BigQuery, Cloud Logging, Cloud Monitoring)
• Collaborating with engineering teams on detection and remediation
• Isolating affected services and processes to prevent spread
• Analyzing artifacts via forensic methods (e.g., Hash, IP, URL, binaries in GTI)
• Conducting root cause analysis using tools (e.g., SCC, Google SecOps SIEM)

5.2 Building and Using Response Playbooks

• Defining response steps for automation
• Prioritizing enrichments based on threat profiles
• Evaluating integrations for playbook automation
• Designing processes in response to emerging attack patterns
• Recommending new automation and orchestration playbooks (e.g., Google SecOps SOAR)
• Implementing alerting mechanisms for analysts and stakeholders

5.3 Implementing Case Management Lifecycle

• Assigning cases to appropriate response stages
• Creating efficient escalation workflows
• Reviewing effectiveness of case handoffs

Domain 6: Observability (10%)

6.1 Developing and Maintaining Dashboards and Reports

• Identifying key security analytics (e.g., metrics, KPIs, trends)
• Creating dashboards to visualize telemetry, ingestion metrics, detections, alerts, and IOCs (e.g., Google SecOps SOAR, SIEM, Looker Studio)
• Generating and customizing reports (e.g., Google SecOps SOAR, SIEM)

6.2 Configuring Health Monitoring and Alerting

• Identifying important health metrics
• Creating centralized dashboards for metrics
• Setting thresholds and alerts for critical metrics
• Configuring notifications using Google Cloud tools (e.g., Cloud Monitoring)
• Detecting health issues with Google Cloud tools (e.g., Cloud Logging)
• Implementing silent source detection