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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Architecture and Design | 21% | - Summarize authentication and authorization design concepts - Explain the security implications of embedded and specialized systems - Explain the importance of security concepts in an enterprise environment - Summarize virtualization and cloud security concepts - Explain the importance of physical security controls - Explain secure application development, deployment, and automation concepts - Given a scenario, implement cybersecurity resilience - Summarize basics of cryptographic concepts |
| Topic 2: Implementation | 25% | - Given a scenario, implement authentication and authorization solutions - Given a scenario, implement secure systems design - Given a scenario, implement identity and account management controls - Given a scenario, implement secure network architecture concepts - Given a scenario, implement secure host settings - Given a scenario, implement public key infrastructure (PKI) - Given a scenario, implement secure mobile device policies - Given a scenario, apply cybersecurity solutions to the cloud |
| Topic 3: Governance, Risk, and Compliance | 14% | - Explain privacy and sensitive data concepts in relation to security - Given a scenario, follow organizational security policies and procedures - Compare and contrast various types of security controls - Summarize regulations, standards, and frameworks that impact organizations - Explain risk management processes and concepts |
| Topic 4: Attacks, Threats, and Vulnerabilities | 24% | - Compare and contrast types of social engineering attacks - Given a scenario, analyze potential indicators to determine the type of attack - Explain penetration testing concepts - Given a scenario, analyze potential indicators associated with application attacks - Explain threat actor types and attributes - Explain vulnerability scanning concepts - Given a scenario, analyze potential indicators associated with network attacks |
| Topic 5: Operations and Incident Response | 16% | - Given a scenario, use appropriate tool to assess organizational security - Given a scenario, apply mitigation techniques or controls to secure an environment - Given a scenario, use data sources to support an investigation - Summarize the importance of policies, processes, and procedures for incident response - Explain key aspects of digital forensics |
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NEW QUESTION # 16
Which IR document defines who must be contacted during a breach and within what timeframe?
Answer: C
Explanation:
The communications plan specifies notification roles and timelines.
NEW QUESTION # 17
A cybersecurity analyst must use pattern recognition on a data set containing unstructured data.
Which of the following models is the best for this task?
Answer: C
Explanation:
Convolutional neural networks (CNNs) are highly effective at detecting patterns in unstructured data such as images, audio, or text embeddings. Their ability to automatically learn spatial or hierarchical features makes them the best choice for pattern recognition on unstructured datasets.
NEW QUESTION # 18
A security administrator sees suspicious queries on AI logs.
Which of the following should the administrator implement to address this issue?
Answer: D
Explanation:
Basic Concept: Suspicious queries in AI system logs indicate that potentially malicious or policy-violating prompts are reaching the AI model. Proactively intercepting and filtering suspicious prompts before they are processed requires a prompt-level security control. CompTIA SecAI+ Study Guide identifies prompt firewalls as the appropriate control for blocking suspicious AI queries.
Why A is Correct: A prompt firewall analyzes incoming queries using a combination of pattern matching, semantic analysis, and policy rules to identify and block suspicious prompts before they reach the AI model.
It can detect prompt injection attempts, jailbreaking patterns, sensitive data extraction queries, and other suspicious prompt characteristics. By intercepting malicious prompts at the perimeter, it prevents them from influencing model behavior or extracting sensitive information.
Why B is Wrong: Data size controls limit the volume or size of data in requests. While controlling input size can prevent some attacks, it does not analyze the content or semantics of queries to detect suspicious patterns.
A small suspicious prompt can be just as harmful as a large one.
Why C is Wrong: Rate limiting controls the frequency of requests from a source. While it can slow down automated attack campaigns, it does not inspect query content for suspicious patterns and allows suspicious queries through as long as they are submitted below the rate threshold.
Why D is Wrong: Agentic AI is an AI architecture for autonomous multi-step task execution. It is a type of AI system, not a security control for filtering suspicious queries from an existing AI system ' s logs.
NEW QUESTION # 19
Which of the following should an auditor reference when reviewing a company's human resources AI systems for legal non-compliance?
Answer: A
Explanation:
The EU AI Act is legally binding legislation that specifically governs the use of AI systems, including those used in human resources for hiring, promotion, and evaluation. An auditor reviewing AI systems for legal non-compliance must reference this act because it establishes enforceable requirements related to transparency, bias, risk classification, and prohibited practices.
NEW QUESTION # 20
A security architect performs threat modeling of an AI system. The architect needs to determine which attacks can be performed against the system.
Which of the following actions should the architect take next?
Answer: A
Explanation:
Basic Concept: AI-specific threat modeling requires consulting resources that catalogue adversarial attacks specifically developed for AI and ML systems. General cybersecurity frameworks may miss AI-unique attack vectors such as model inversion, data poisoning, and adversarial examples. CompTIA SecAI+ Study Guide identifies MITRE ATLAS as the authoritative source for AI system TTPs.
Why D is Correct: MITRE ATLAS provides a comprehensive, curated knowledge base of adversarial tactics, techniques, and procedures specifically targeting AI and ML systems, derived from real-world attack case studies. Analyzing ATLAS enables the architect to enumerate realistic AI-specific attacks applicable to the system being threat-modeled, which directly answers the question of which attacks can be performed.
Why A is Wrong: Using an LLM to map attack paths introduces uncertainty and potential hallucination risk.
LLMs may generate plausible-sounding but inaccurate attack paths and cannot guarantee comprehensive coverage of AI-specific attack techniques.
Why B is Wrong: Quantifying risk of known vulnerabilities is a risk assessment step that occurs after identifying which attacks are possible. The architect must first identify attack possibilities before quantifying their risk impact.
Why C is Wrong: OWASP Top 10 covers web application vulnerabilities and, in its LLM edition, certain LLM-specific risks. However, MITRE ATLAS provides a more comprehensive and structured catalog of AI and ML-specific adversarial TTPs for systematic threat modeling.
NEW QUESTION # 21
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