Free Practice Questions for CompTIA CAS-005 Exam

Managing telemetry and differentiating it by office requires a way to categorize data. Let’s evaluate:

A. Sensor placement:Useful for data collection but doesn’t inherently differentiate by office.

B. Data labeling:Assigns metadata (e.g., office location) to telemetry, enabling differentiation. This aligns with CAS-005’s focus on data management for security operations.

C. Continuous monitoring:Ensures ongoing data collection but doesn’t address differentiation.

Regression testing is a software testingpractice that ensures that recent code changes have not adversely affected existing functionalities. In this scenario, the reintroduction of a previously fixed bug indicates that changes or integrations brought back the old issue. Implementing comprehensive regression testing would help detect such reintroductions by systematically retesting the existing functionalities whenever changes are made to the codebase. This practice is crucial in maintaining the integrity of the application, especially in complexsystems where multiple components interact.​

The hijacked administrator account was used across multiple ASNs (indicating different network locations) in a short time, despite MFA and SSO. This suggests a stolen session or token misuse. Let’s analyze:

A. Token theft detection with lockouts:Useful for detecting stolen SSO tokens, but it’s reactive and may not prevent initial misuse across networks.

B. Context-based authentication:This adds real-time checks (e.g., geolocation, IP changes) to verify login attempts. Given the rapid ASN changes, this proactively mitigates the issue by challenging suspicious logins, aligning with CAS-005’s focus on adaptive security.

C. Decentralize accounts:This removes SSO, increasing complexity and weakening MFA enforcement, which isn’t practical or secure.

Input sanitation is a critical process in cybersecurity that involvesvalidating and cleaning data provided by users to prevent malicious inputs from causing harm. In the context of AI concerns:

A. Model inversion involves an attacker inferring sensitive data from model outputs, typically requiring sophisticated methods beyond just manipulating input data.

B. Prompt Injection is a form of attack where an adversary provides malicious input to manipulate the behavior of AI models, particularly those dealing with natural language processing (NLP). Input sanitation directly addresses this by ensuring that inputs are cleaned andvalidated to remove potentially harmful commands or instructions that could alter the AI's behavior.

C. Data poisoning involves injecting malicious data into the training set to compromise the model. While input sanitation can help by filtering out bad data, data poisoning is typically addressed through robust data validation and monitoring during the model training phase, rather than real-time input sanitation.

D. Non-explainable model refers to the lack of transparency in how AI models make decisions. This concern is not addressed by input sanitation, as it relates more to model design and interpretability techniques.

Input sanitation is most relevant and effective for preventing Prompt Injection attacks, where the integrity of user inputs directly impacts the performance and security of AI models.

Step by Step Explanation:

Understanding the Scenario: The question focuses on the historical design assumptions behind older operational technology (OT)systems, particularly in the context of command, control, and telemetry.

Analyzing the Answer Choices:

A. operating in an isolated/disconnected system: This is the most accurate assumption for many legacy OT systems. Historically, these systems weredesigned to operate in air-gapped environments, completely isolated from external networks (including the internet).

The issue is tracing the original source of requests in a tiered architecture with a load balancer. The web server logs show internal IPs (192.168.1.10), not the external client IPs, because the load balancer forwards requests without preserving the source. Enabling theX-Forwarded-Forheader on the load balancer adds the client’s original IP to the HTTP request headers, allowing downstream servers to log it. This ensures traceability without altering the architecture significantly.

Option A:Correct—X-Forwarded-For is the standard solution for preserving client IPs through load balancers.

Option B:A Host-based Intrusion Detection System (HIDS) detects anomalies but doesn’t address IP traceability.

Option C:A trusted CA certificate fixes the self-signed warning but is unrelated to source tracking.

Option D:Stored procedures improve database security but don’t help with IP logging.

Option E:Storing $_SERVER['REMOTE_ADDR'] captures the loadbalancer’s IP, not the client’s, unless X-Forwarded-For is enabled.

To support email authenticity and enable analysis by a third-party platform, the protocols must verify the sender’s identity and provide metadata for inspection. According to the CompTIA SecurityX CAS-005 study guide (Domain 3: Cybersecurity Technology, 3.2):

DMARC (Domain-based Message Authentication, Reporting, and Conformance):DMARC builds on SPF and DKIM to enforce policies for email authenticity and provides reporting mechanisms to share authentication results with third parties for analysis.

DKIM (DomainKeys Identified Mail):DKIM adds a cryptographic signature to emails, allowing recipients to verify the sender’s domain and ensure the email’s integrity.

These two protocols are essential for authenticity and reporting.

Option C (TLS):TLS ensures encryption during transmission but does not address authenticity or reporting.

Option D (SPF):SPF verifies sender IP addresses but lacks reporting capabilities without DMARC.

Option E (DNSSEC):DNSSEC secures DNS queries but is not specific to email authenticity.

Option F (MX):MX records define mail servers, not authenticity or reporting.

Anacceptable use policy (AUP)defines what is considered appropriate use of corporate email and prevents unnecessary emails to personal accounts. This helps in reducing false DLP alerts while maintaining compliance.

Quarantining emails (A)is unnecessary since the content was not flagged as sensitive.

Encryption (C)secures emails but does not address overuse.

Phishing awareness training (D)is unrelated to policy enforcement for outgoing emails.

For a disaster recovery (DR) plan requiring immediate data availability, the first step is understanding what needs to be protected and recovered. Identifying critical business processes and their associated software and hardware requirements establishes the foundation for the DR plan. This ensures that backups and recovery mechanisms align with business priorities, meeting the "moment's notice" requirement.

Option A:A change management plan is important for system consistency but doesn’t directly address immediate data availability in a DR context.

Option B:Hiring staff supports execution but doesn’t define what needs to be recovered or how. It’s a later step.

Option C:A warm site (a partially operational backup site) is a good DR solution, but designing it comes after identifying critical processes and resources.

Option D:This is the first step in any DR planning process—knowing what’s critical ensures the plan meets availability goals efficiently.