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| Section | Weight | Objectives |
|---|---|---|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI and Machine Learning Fundamentals
|
| AI Governance, Risk, and Compliance | 19% | - AI Governance Frameworks
|
| Securing AI Systems | 40% | - Adversarial Defense
|
| AI-Assisted Security | 24% | - Security Operations Enhancement
|
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問題 #125
Which of the following attacks would be the best to automate with AI during dynamic application software testing (DAST)?
答案：D
解題說明：
Basic Concept: Dynamic Application Security Testing (DAST) tests running applications by sending various inputs to discover vulnerabilities. AI can significantly enhance DAST by intelligently generating diverse, targeted test payloads that traditional tools might miss. CompTIA SecAI+ covers AI augmentation of security testing methodologies.
Why C is Correct: Payload creation is highly suitable for AI automation during DAST. AI can generate diverse, contextually appropriate attack payloads such as SQL injection strings, XSS vectors, command injection attempts, and format string exploits tailored to the specific application ' s behavior observed during testing. AI can learn from the application ' s responses to previous payloads and generate increasingly targeted inputs, discovering vulnerabilities more efficiently than static payload databases.
Why A is Wrong: DDoS attacks are volume-based attacks designed to overwhelm network or application infrastructure. Automating DDoS during DAST is inappropriate as it would disrupt service availability rather than discover application security vulnerabilities, and it is harmful to legitimate operations.
Why B is Wrong: Data poisoning is an attack targeting AI/ML model training data integrity. It is relevant to securing AI systems but is not a DAST technique for testing web or software application security vulnerabilities during dynamic testing.
Why D is Wrong: Threat modeling is a structured analysis process performed before development or testing to identify potential threats and design appropriate countermeasures. It is a planning activity, not an attack technique that can be automated during dynamic application security testing.
問題 #126
Which of the following attacks is most enabled by AI-generated content?
答案：A
解題說明：
Basic Concept: AI-generated content including personalized text, synthetic voice, and deepfake video has dramatically enhanced the effectiveness and scalability of social engineering attacks. Understanding how AI amplifies specific attack types is key to CompTIA SecAI+ basic AI concepts in the cybersecurity context.
Why B is Correct: Phishing attacks are most dramatically enabled by AI-generated content. AI can generate highly personalized, grammatically perfect phishing emails tailored to individual targets using publicly available information. It can create convincing deepfake audio and video for voice phishing (vishing) and video phishing, replicate executive communication styles for business email compromise, and generate phishing campaigns at massive scale. The quality and personalization that previously required skilled human social engineers can now be automated with AI.
Why A is Wrong: Model poisoning is a specific attack against AI systems that corrupts training data to manipulate model behavior. While sophisticated, it is a targeted AI security attack rather than a broad cybercrime enabled by AI-generated content at scale.
Why C is Wrong: Ransomware is malware that encrypts victim data and demands payment for decryption keys. While AI can assist in ransomware development, ransomware deployment relies on code execution and network propagation techniques more than AI-generated content.
Why D is Wrong: Remote code execution involves exploiting vulnerabilities to run arbitrary code on a target system. It relies on technical vulnerability exploitation rather than AI-generated content. AI might assist in finding vulnerabilities, but RCE is not primarily enabled by content generation.
問題 #127
A security team is using an AI-based tool to try to bypass organizational boundaries. The team uses AI to look at the current state and suggest different attack vectors based on the outcome of the previous ones.
Which of the following techniques is the team most likely using?
答案：A
解題說明：
Basic Concept: Modern penetration testing increasingly leverages AI to automate the reconnaissance, exploitation, and pivoting process. AI-assisted automated penetration testing can adapt its strategy based on previous results, simulating intelligent adversary behavior more realistically than static scripts. CompTIA SecAI+ covers AI-assisted offensive security techniques.
Why D is Correct: Automated penetration testing uses AI to systematically discover and attempt to exploit vulnerabilities while adapting tactics based on the results of previous attempts. The described behavior - looking at the current state, suggesting attack vectors, and adjusting based on outcomes - precisely describes an adaptive AI-driven penetration testing tool that iteratively explores the attack surface, mimicking how an advanced persistent threat would operate.
Why A is Wrong: Manual signature matching compares network traffic or files against a database of known threat signatures. It is a passive detection technique used by defensive tools like IDS/IPS, not an adaptive offensive technique for bypassing organizational boundaries.
Why B is Wrong: Code quality testing analyzes source code for bugs, vulnerabilities, and adherence to coding standards. It is a development quality assurance activity, not an offensive security technique for testing organizational security boundaries.
Why C is Wrong: Fraud detection uses ML to identify suspicious patterns in transactions or user behavior for defensive purposes. It is a preventive security measure, not an offensive technique for penetration testing.
問題 #128
An organization develops a chatbot with the following requirements:
- Does not provide harmful or explicit responses
- Must use clean and professional language
- Ensures that responses are accurate
Which of the following should the organization conduct after the chatbot is fully developed but before a customer-facing deployment?
答案：A
解題說明：
Guardrail testing and validation ensure the chatbot adheres to safety, language, and accuracy requirements before deployment. This step verifies the model will not generate harmful, explicit, or unprofessional responses in a customer-facing environment.
問題 #129
A user interface engineer adds new graphics to the latest release of an AI-integrated application.
During the update, the engineer accidentally causes the model to retain on unverified data. After the update, the model begins to return many errors. Which of the following is the best way to mitigate future errors?
答案：C
解題說明：
Following a secure and structured model development life cycle (MDLC) ensures controls such as data validation, verification, and testing are in place. This prevents issues like retraining on unverified data and reduces the likelihood of future model errors.
問題 #130
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