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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Application Delivery and Additional Configuration | 20% | - Protection and integration
|
| Topic 2: Deployment and Configuration | 30% | - Server objects and security policies
|
| Topic 3: Web Application and API Security with Bot Mitigation | 35% | - Web application security measures
|
| Topic 4: Compliance and Troubleshooting | 15% | - Compliance and audit
|
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NEW QUESTION # 40
A FortiWeb administrator is hardening a customer checkout website.
The site contains sensitive links such as Login, Payment, and Admin, which are embedded in the HTML content of several pages.
A vulnerability scan shows that automated bots can crawl the web pages and easily enumerate these links by parsing the HTML source, even though users access them normally, through the site navigation.
Which FortiWeb feature should the administrator enable to prevent automated scanners from discovering these links?
Answer: C
NEW QUESTION # 41
A third-party penetration test reveals that users can bypass login controls through a mobile API.
Your current FortiWeb configuration includes zero trust network access (ZTNA) profiles and cookie security, but API protection and client management are not enabled. The security team asks you to recommend the most effective way to close this gap. Which FortiWeb adjustment would best prevent future unauthorized API access?
Answer: A
Explanation:
API protection and client management are designed to control and validate access to API endpoints, including mobile API traffic. Enabling them allows FortiWeb to apply identity-aware checks, manage API clients, and prevent unauthorized access paths that are not adequately protected by cookie security alone.
NEW QUESTION # 42
Refer to the exhibit.
A FortiWeb administrator tests a new form input value after training the machine learning (ML) anomaly detection system.
The hidden Markov model (HMM) flags the input as abnormal, while the support vector machine (SVM) model classifies it as normal. FortiWeb allows the request.
What does this result indicate about the FortiWeb ML anomaly detection behavior?
Answer: C
Explanation:
FortiWeb machine learning uses layered detection rather than treating every unusual value as malicious. The HMM layer models normal parameter behavior and can flag a value as abnormal when it falls outside the learned distribution. However, abnormal does not automatically mean hostile. FortiWeb then uses additional ML classification logic, including SVM-based evaluation, to determine whether the anomaly resembles an actual attack or simply a legitimate unusual input. In this case, HMM noticed that the value was uncommon, but SVM classified it as normal, so FortiWeb allowed the request. That is expected behavior. Raising thresholds, disabling models, or assuming FortiWeb failed would misunderstand the two-stage ML decision process.
NEW QUESTION # 43
Drag and Drop Question
A FortiWeb administrator is reviewing protection effectiveness after a surge in malicious traffic exposed design flaws and misconfigurations in several web applications.
For each Open Web Application Security Project (OWASP) risk listed, choose the FortiWeb feature that offers the most strategic protection, considering both coverage depth and operational effectiveness.
Match the most appropriate FortiWeb feature to each OWASP issue.
Select each FortiWeb feature in the left column, hold and drag it to the blank space next to the OWASP issue in the column on the right. Once you match a FortiWeb feature to the OWASP issue, you can move it again if you want to change your answer by clicking on the FortiWeb feature. You need to match five FortiWeb features to the OWASP issue in the work area.
Answer:
Explanation:
Explanation:
A01: Broken Access Control → Site publish
A03: Injection → Parameter validation
A04: Insecure Design → Web vulnerability scan
A05: Security Misconfiguration → HSTS header
Site publish helps enforce controlled access to protected applications. Parameter validation restricts unsafe or unexpected input that could be used in injection attacks. Web vulnerability scanning helps identify application weaknesses and design-related exposure before attackers exploit them. HSTS reduces security misconfiguration risk by forcing browsers to use HTTPS for the protected site.
NEW QUESTION # 44
A FortiWeb administrator wants to stop coordinated scraping traffic coming from several IP addresses, each making only a few requests so thresholds never trigger.
Which tactic should the administrator deploy to identify botnets using shared behavioral signals instead of volume?
Answer: C
Explanation:
The scenario describes distributed scraping where each individual IP stays below request-rate thresholds. A simple DoS threshold is weak here because the attacker avoids volume-based detection per source. Static blocklists are also ineffective because many botnet IPs may appear only once or rotate frequently. Blocking every non-allowlisted user agent would cause severe false positives and is easy for bots to evade by spoofing headers. FortiWeb bot mitigation is the correct control because it can evaluate behavior beyond source IP volume. Device fingerprinting, browser behavior, headers, JavaScript challenges, and client characteristics help correlate suspicious automation even when requests are spread across many addresses. Therefore, bot mitigation with behavioral/device fingerprinting is the strongest answer.
NEW QUESTION # 45
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