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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: SOC Concepts and Frameworks | 20% | - Security incident analysis and adversary behavior identification - Fortinet SOC enterprise architecture - Industry frameworks (MITRE ATT&CK, NIST) - Integration of FortiSIEM and FortiSOAR with Security Fabric |
| Topic 2: Detection Capabilities | 25% | - Log analysis, query building and event correlation - Data normalization and aggregation - Threat detection and visibility design - FortiSIEM rule configuration and alert management |
| Topic 3: SOAR Playbook Development and Automation | 30% | - Data transformation and Jinja filters - Troubleshooting automation workflows - Playbook design, development and debugging - Connector configuration and integration |
| Topic 4: SOAR Incident Handling and Threat Hunting | 25% | - Threat hunting methodologies and data usage - Incident lifecycle management in FortiSOAR - Collaborative response and war room features - SOC workflow, queues and shift management |
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NEW QUESTION # 82
Refer to the exhibits.
How is the investigation and remediation output generated on FortiSIEM? (Choose one answer)
Answer: D
Explanation:
In FortiSIEM 7.3 , a key innovation is the integration of FortiAI , which provides generative AI capabilities to assist SOC analysts during the triage and response process.
* Generative AI Summary: When an incident occurs, FortiAI can automatically analyze the underlying logs, correlation logic, and MITRE ATT & CK techniques (such as " Exfiltration Over Alternative Protocol " shown in the exhibit) to generate a human-readable summary.
* Structured Output: The output displayed in the exhibit-specifically the categorized Investigation Actions (identifying affected systems, analyzing traffic) and Remediation Actions (immediate containment, patching, user training)-is the typical result of a FortiAI summary request.
* Analyst Efficiency: This feature is designed to reduce the " mean time to respond " (MTTR) by providing analysts with immediate, actionable steps without requiring them to manually piece together the recommended response plan from static documentation or disparate log views.
Why other options are incorrect:
* Exporting an incident (A): Exporting an incident typically results in a raw data file (CSV/JSON/PDF) containing the log data and metadata, rather than an AI-generated strategic plan for investigation and remediation.
* Running an incident report (B): Standard incident reports provide statistical and historical data about incidents over time. They do not dynamically generate specific, numbered investigation steps tailored to the unique context of a single live incident.
* Context tab (D): The Context tab in FortiSIEM is primarily used to view the CMDB information of the involved assets (e.g., host details, owner, location) and related historical events. While it provides the data needed for an investigation, it does not provide the list of actions to take.
NEW QUESTION # 83
A FortiSOAR playbook includes a Wait step that is configured to pause execution after initiating a reputation lookup on an indicator. Which two configurations of the Wait step are valid? Choose two answers.
Answer: B,C
Explanation:
Exact Extract: "Use the Wait step to specify the time that the playbook should wait after a specific step before continuing with the remaining steps in the playbook. Alternatively, specify the conditions that must be met before the playbook continues. For example, investigation playbooks should wait for enrichment to finish before continuing with the subsequent steps." The correct answers are A and B . A Wait step can resume after a defined duration, so option A is valid. It can also resume when a condition is met, such as the indicator record being updated after the reputation lookup or enrichment process completes, so option B is also valid. Option C is not a Wait-step function; retrying failed actions at intervals belongs to step execution/error-handling behavior, not the Wait step's purpose. Option D is also wrong because executing another playbook is handled by a separate reference
/playbook execution step, not by the Wait step while it is paused. The guide separately identifies "Reference a Playbook" as the step used to execute another playbook.
Technical Deep Dive: In FortiSOAR playbooks, Wait is a control-flow gate. Use time-based waiting when an external system has predictable processing latency, for example waiting 60 seconds after submitting an IOC to a sandbox or reputation service. Use condition-based waiting when the downstream update is asynchronous, for example waiting until an indicator's reputation, enrichment status, or related field changes. This prevents the playbook from reading incomplete enrichment data.
This is SOAR workflow orchestration; FortiGate NP/CP hardware offloading is irrelevant because no traffic forwarding, session acceleration, or content processor inspection is involved.
NEW QUESTION # 84
Refer to this partial incident output:
Condition: if this pattern occurs within any 1800-second time window.
Host Interface Name: Red Hat VirtIO Ethernet Adapter
Recv Packet Errors: 0
Sent Packet Errors: 0
Recv Packet Discards: 37
Sent Packet Discards: 0
Recv Packet Error Pct: 0.00
Sent Packet Error Pct: 0.00
Recv Packet Discard Pct: 7.17
Sent Packet Discard Pct: 0.00
Avg Recv Interface Error: 0.00
Avg Sent Interface Error: 0.00
Avg Recv Interface Discard: 16.45
Avg Sent Interface Discard: 0.00
Which conclusion can you make about this incident? Choose one answer.
Answer: D
Explanation:
Exact Extract: "Take baselines of traffic: Understanding what normal traffic looks like in your environment is critical. By taking accurate baselines and distinguishing them from abnormal activity, you can create more true positives and reduce false positives." Exact Extract: "Incident: An incident in FortiSIEM is created when a correlation rule is triggered. These rules analyze incoming events and group them into incidents when a pattern or threat condition is met within a specific time period." The correct answer is A . The giveaway is the presence of Avg Recv Interface Discard , Avg Sent Interface Discard , and other average interface values. Those fields indicate the incident is comparing current interface behavior against a learned or stored baseline. A standard correlation rule can trigger incidents, but the more precise conclusion from this output is that the rule is baseline-profile driven. B is wrong because nothing in the output indicates FortiAI or machine-learning generated detection. D is wrong because a lookup table would enrich or match values; it would not explain baseline-average performance metrics.
Technical Deep Dive: This is a performance/anomaly style FortiSIEM incident. The current receive discard count and percentage are being evaluated against average baseline behavior for the same interface. That is materially different from a simple fixed threshold rule. In production, you would validate whether the baseline was trained during normal traffic conditions; otherwise, bad baselines create noisy incidents. FortiGate NP/CP offloading is not the deciding factor here because the detection is based on FortiSIEM telemetry and baseline analytics, not firewall packet acceleration.
NEW QUESTION # 85
You are trying to create a playbook that creates a manual task showing a list of public IPv6 addresses. You were successful in extracting all IP addresses from a previous action into a variable called ip_list , which contains both private and public IPv4 and IPv6 addresses. You must now filter the results to display only public IPv6 addresses. Which two Jinja expressions can accomplish this task? (Choose two answers)
Answer: A,B
Explanation:
In FortiSOAR 7.6 , the playbook engine utilizes the powerful ipaddr family of Jinja filters (derived from the Ansible netaddr library) to manipulate network data. To isolate public IPv6 addresses from a mixed list, the order of operations in the filter chain ensures the correct data is extracted:
* Double Filtering Sequence (B): In the expression {{ vars.ip_list | ipaddr( ' public ' ) | ipv6 }}, the first filter ipaddr( ' public ' ) processes the entire list and retains only public addresses, including both IPv4 and IPv6 versions. The second filter in the pipe, | ipv6, then takes that subset of public addresses and filters them again to keep only those that conform to the IPv6 standard. The final result is a list containing only public IPv6 addresses.
* Version-First Filtering (D): In the expression {{ vars.ip_list | ipv6 | ipaddr( ' public ' ) }}, the logic is reversed but equally effective. The first filter | ipv6 immediately strips all IPv4 and non-IP strings from the list, leaving only IPv6 addresses (both private and public). The subsequent filter | ipaddr( ' public ' ) then evaluates these IPv6 addresses and discards any that fall within the private/unique-local ranges (like ULA or link-local), resulting in the same set of public IPv6 addresses.
Why other options are incorrect:
* A (ipv6addr ' public ' ): While ipv6addr is a valid filter in many Ansible environments, FortiSOAR ' s standard documentation for manual task creation and data manipulation primarily emphasizes the use of the generic ipaddr filter with specific flags or chained version filters (like | ipv6) to ensure cross- compatibility with the underlying Python libraries used by the SOAR engine.
* C (!private syntax): The ipaddr filter utilizes specific keywords for classification. While " not private " is the logical requirement, the filter expects positive assertions such as ' public ' , ' private ' , or ' multicast ' . The !private syntax is not a supported or documented operator for this filter within the Fortinet SOC ecosystem.
NEW QUESTION # 86
An analyst prioritizes blocking IP addresses and domains from every phishing campaign. Based on the Pyramid of Pain model, which two statements accurately describe this approach? Choose two answers.
Answer: A,B
Explanation:
Exact Extract: "The Pyramid of Pain illustrates why focusing on adversary TTPs is important: They are the most descriptive IOCs of a given adversary and the toughest for threat actors to change." The guide ranks Domain Names as "Simple" and IP Addresses as "Easy," while TTPs are "Tough." Exact Extract: "As you progress from the top of the pyramid to the bottom, the disruption of an element becomes easier for the adversary to recover from... once those IP addresses start to be widely recognized as malicious and potentially blocked, it is easy for the attacker to start using other IP addresses." The correct answers are C and D . Blocking IP addresses and domains is useful, but it targets low-level observable indicators, not the adversary's deeper behavior. In the Pyramid of Pain, IP addresses and domain names sit near the bottom because attackers can replace them quickly by rotating infrastructure, registering new domains, using compromised hosts, or changing hosting providers. Therefore, this approach focuses on network indicators and creates only limited disruption.
Option A is too strong. IPs and domains may reveal infrastructure, but blocking them does not necessarily identify strategic weaknesses in the adversary's operation. Option B is wrong because high operational cost is associated with forcing adversaries to change tools or TTPs, not merely rotating IPs and domains.
Technical Deep Dive: In a Fortinet SOC, blocking phishing IPs/domains can be automated through FortiSOAR playbooks using FortiGate address objects, DNS filtering, FortiMail blocklists, or FortiGuard threat intelligence enrichment. That is good hygiene, but it is reactive. Higher-value hunting looks for reusable phishing tradecraft: lure themes, sender infrastructure patterns, attachment behaviors, command-and-control sequence, credential collection workflow, and post-compromise TTPs.
ASIC offloading is not the key issue here; the security value comes from intelligence quality and detection depth, not packet acceleration.
NEW QUESTION # 87
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