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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Operations and Incident Response | 16% | - Given a scenario, apply mitigation techniques or controls to secure an environment - Explain key aspects of digital forensics - Given a scenario, use data sources to support an investigation - Given a scenario, use appropriate tool to assess organizational security - Summarize the importance of policies, processes, and procedures for incident response |
| Topic 2: Governance, Risk, and Compliance | 14% | - Explain privacy and sensitive data concepts in relation to security - Summarize regulations, standards, and frameworks that impact organizations - Compare and contrast various types of security controls - Explain risk management processes and concepts - Given a scenario, follow organizational security policies and procedures |
| Topic 3: Attacks, Threats, and Vulnerabilities | 24% | - Given a scenario, analyze potential indicators associated with network attacks - Explain vulnerability scanning concepts - Explain penetration testing concepts - Given a scenario, analyze potential indicators to determine the type of attack - Given a scenario, analyze potential indicators associated with application attacks - Compare and contrast types of social engineering attacks - Explain threat actor types and attributes |
| Topic 4: Architecture and Design | 21% | - Explain secure application development, deployment, and automation concepts - Explain the security implications of embedded and specialized systems - Explain the importance of security concepts in an enterprise environment - Given a scenario, implement cybersecurity resilience - Explain the importance of physical security controls - Summarize virtualization and cloud security concepts - Summarize authentication and authorization design concepts - Summarize basics of cryptographic concepts |
| Topic 5: Implementation | 25% | - Given a scenario, implement identity and account management controls - Given a scenario, implement secure network architecture concepts - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement authentication and authorization solutions - Given a scenario, implement secure systems design - Given a scenario, implement secure host settings - Given a scenario, apply cybersecurity solutions to the cloud - Given a scenario, implement secure mobile device policies |
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問題 #68
Which of the following is the most appropriate reason for model validation?
答案：A
解題說明：
Model validation is intended to determine systematically whether an AI or machine learning model performs according to its defined objectives and produces acceptable results. This requires a formal methodology, appropriate validation data, measurable criteria, and comparison of actual model behavior against expected outcomes. CompTIA SecAI+ explicitly includes model validation among model-training techniques and also places validation, model evaluation, monitoring, and feedback within the AI lifecycle. Option C therefore represents the actual purpose of validation: objectively establishing whether the model satisfies predetermined performance and quality requirements. Providing feedback between interactions is closer to feedback and iteration or model adaptation rather than validation itself. Checking an exported file is merely an output or serialization check and does not evaluate model quality comprehensively. CI/CD integration checks establish whether software components build, integrate, or deploy correctly; a model could successfully pass those technical checks while still producing inaccurate, biased, unsafe, or otherwise unacceptable predictions.
Formal measurement against expected outcomes is therefore the distinguishing characteristic of proper model validation.
問題 #69
A detection engineering team wants to use AI to automatically prevent vulnerable code from reaching production.
Which of the following is the most effective way to accomplish this task?
答案：D
解題說明：
Basic Concept: Preventing vulnerable code from reaching production requires an automated, mandatory gate in the software delivery pipeline. The CI/CD pipeline is the enforcement point where all code must pass before deployment. CompTIA SecAI+ Study Guide covers AI integration in secure development pipelines under AI-assisted security.
Why C is Correct: Implementing an LLM in the CI/CD runner creates a mandatory automated security gate that every code change must pass. The LLM can analyze code for vulnerabilities, insecure patterns, and policy violations, then automatically fail the build if issues are found. This prevents vulnerable code from progressing toward production without human bypass capability, making it the most effective enforcement mechanism.
Why A is Wrong: IDE plug-ins provide warnings to developers during coding, but developers can choose to ignore them and proceed with compilation and commits. Warnings are advisory, not preventive, and cannot guarantee vulnerable code is blocked from the pipeline.
Why B is Wrong: SOAR platforms with ML models are excellent for incident response and security operations automation. However, they are not positioned in the code delivery pipeline and do not gate code from progressing to production.
Why D is Wrong: An agentic penetration testing tool validates vulnerabilities reactively after code is written or deployed. This approach does not intercept code before production deployment and is typically used for post-deployment assessment rather than prevention.
問題 #70
Which of the following is used to train an AI model with unstructured data?
答案：B
解題說明：
Fine-tuning allows an AI model to adapt to unstructured data (such as text, audio, or images) by retraining it on domain-specific datasets. This process improves the model's ability to handle and generate outputs aligned with the unstructured data context.
問題 #71
An automobile manufacturer implements a chatbot to assist with configuration options for customer automobiles. Given a customer ' s prompt, the chatbot gives offensive responses.
Which of the following describes this behavior?
答案：C
解題說明：
Basic Concept: AI chatbots are designed with safety guidelines and content policies that prevent them from generating harmful, offensive, or inappropriate content. When users find ways to bypass these restrictions through crafted prompts, they have " jailbroken " the model. CompTIA SecAI+ Study Guide covers jailbreaking as a key AI vulnerability category.
Why C is Correct: Jailbreaking is the process of using cleverly crafted prompts to bypass an AI model ' s built- in safety restrictions, content policies, and behavioral guardrails, causing it to produce outputs it was designed to refuse. The scenario describes a chatbot that was designed for automobile configuration assistance but is producing offensive responses following customer prompts, indicating that customers have successfully prompted the model to bypass its safety constraints and generate prohibited content.
Why A is Wrong: Model skewing refers to attacks or biases that cause a model to favor certain outputs or perspectives systematically over time, often through data manipulation. It describes a gradual distortion of model behavior, not a direct user-prompted bypass of safety restrictions in a single interaction.
Why B is Wrong: Model theft involves extracting or replicating a proprietary model ' s functionality or architecture through repeated queries. It is an intellectual property attack aimed at stealing the model ' s knowledge, not an attack that causes the model to produce offensive content.
Why D is Wrong: Insecure output handling occurs when an application fails to properly validate or sanitize AI-generated outputs before using them in ways that could cause harm such as passing AI output directly to a system command or database query. It describes a developer implementation vulnerability, not the act of a user prompting a model to bypass its safety constraints.
問題 #72
Which log type is MOST useful for detecting DNS tunneling?
答案：A
解題說明：
DNS logs reveal abnormal query lengths and frequencies typical of tunneling.
問題 #73
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