CompTIA Updated CY0-001 Exam Questions and Answers by evalyn

Basic Concept: A replay attack occurs when an attacker captures a valid authentication token or credential and reuses it to impersonate a legitimate user. Preventing replay attacks requires ensuring that captured credentials cannot be successfully reused after a defined period or after their intended single use. CompTIA SecAI+ Study Guide covers replay attack prevention under AI system authentication.

Why C is Correct: Expiring session tokens have a limited validity window, typically a few minutes to hours. If an attacker captures a token, they can only use it until it expires. Short expiration times dramatically reduce the window of opportunity for replay attacks. This is the most direct and effective control specifically targeting replay attack prevention, as expired tokens are rejected even if intercepted.

Why A is Wrong: IdP federation enables single sign-on across multiple systems using federated identity providers. While it standardizes authentication, it does not inherently prevent replay attacks on captured tokens unless combined with short token expiration and proper validation.

Why B is Wrong: SSH certificate authentication uses cryptographic certificates for strong authentication. While more secure than password-based SSH, certificates alone do not prevent replay attacks unless they include timestamps, nonces, or other anti-replay mechanisms that invalidate captured credentials.

Why D is Wrong: IAM access keys are long-lived credentials that provide programmatic access to services. They are typically static and do not expire automatically, making them vulnerable to replay attacks if intercepted. They are less suitable for replay attack prevention than expiring session tokens.

Basic Concept: An on-path (formerly man-in-the-middle) attack intercepts communication between two parties, allowing the attacker to read, modify, or inject content. In the context of a generative AI application, an on-path attack on the session between user and AI service can manipulate prompts being sent to the model or responses being returned to users. CompTIA SecAI+ covers AI-specific attack vectors under securing AI systems.

Why B is Correct: Session hijacking involves an attacker taking control of an active user session by capturing or forging session tokens. In this attack, the attacker intercepts the communication channel between users and the AI application, allowing them to modify prompts sent to the model or replace legitimate model responses with offensive content. This explains why outputs seem unrelated to prompts and contain offensive material.

Why A is Wrong: Application server hijacking involves gaining unauthorized control of the server hosting the application. While severe, this would typically manifest as complete service disruption or data exfiltration rather than targeted modification of individual user session content.

Why C is Wrong: Domain hijacking involves unauthorized transfer of a domain name registration, redirecting all users to a different IP address. This would affect all users simultaneously and typically redirect to a completely different site rather than manipulating individual AI responses.

Why D is Wrong: Model hijacking refers to attacks that steal or replicate an AI model, not to intercepting and modifying the communication between users and an existing model during active sessions.

Basic Concept: A denial-of-wallet (DoW) attack deliberately generates excessive API calls or token consumption to exhaust an organization ' s AI budget. Since LLM providers charge based on tokens processed, attackers can cause significant financial damage by driving massive usage. CompTIA SecAI+ Study Guide addresses financial abuse vectors in AI systems.

Why E is Correct: API rate controls limit the number of requests a user or application can make within a defined time period. By capping request frequency, rate controls directly prevent attackers from generating the massive API call volume needed to execute a denial-of-wallet attack.

Why F is Correct: Output token controls cap the maximum number of tokens the model can generate per response. Since billing is based on tokens consumed including outputs, limiting output tokens directly caps the cost per request, preventing attackers from triggering extremely long, expensive responses.

Why A is Wrong: Endpoint access controls manage device or network access. They do not directly limit token consumption or API call volume that drives denial-of-wallet costs.

Why B is Wrong: A CDN distributes content geographically to improve performance and absorb traffic. It does not control LLM API billing or token consumption.

Why C is Wrong: Model fine-tuning adjusts model parameters for improved performance on specific tasks. It is a training process that does not address active cost-exhaustion attacks.

Why D is Wrong: Modality controls restrict which input types such as text, images, or audio a model accepts. While useful for reducing attack surface, they do not directly address the rate or volume of API calls in a DoW attack.

Option A is correct because a system prompt contains the developer- or platform-defined instructions that establish how the AI should behave throughout an interaction. It can define the model’s role, objectives, prohibited actions, response style, tool-use boundaries, and security constraints before the user submits a request. That description matches an input supplied by a developer to govern later AI interactions. Option B is the end user’s prompt or request; it expresses what the user wants in a particular turn and normally has lower authority than system-level instructions. Option C, zero-shot prompting, describes asking the model to perform a task without providing an example. Option D, multi-shot prompting, supplies multiple examples to demonstrate the desired input or output pattern. Neither zero-shot nor multi-shot identifies the authority or source of the instruction. In a secure AI application, system instructions should be protected from unauthorized modification, tested for conflicts, and reinforced with technical controls rather than treated as the sole security boundary. The essential distinction is prompt hierarchy: system instructions configure persistent behavior, while user prompts request individual tasks.

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