CompTIA CAS-005 Exam With Confidence Using Practice Dumps

The organization is most concerned about Generative AI improving phishing and social engineering attacks. Tools like ChatGPT can generate highly convincing phishing emails, fake websites, and human-like interactions that bypass traditional detection methods. Employees who were trained to spot poor grammar or obvious scams may now struggle to detect AI-crafted exploits.

Option A relates to compliance but not AI-driven threats. Option B (overreliance on AI bots) is operational risk, not phishing. Option D (differential analysis) applies to AI privacy issues, not phishing.

CAS-005 emphasizes adapting training to emerging threats, including AI-enabled social engineering. This ensures users remain resilient against modern attacks, making C the correct answer.

A Content Delivery Network (CDN) caches and distributes static and dynamic web content across multiple geographically distributed edge servers, reducing latency for global users. This directly addresses page-loading delays caused by distance from the primary data centers.

RASP is for runtime application security, not latency.

Remote journaling is for data replication, not performance optimization.

SASE can improve security and WAN routing, but a CDN is purpose-built for content delivery performance.

When dealing with false positives and false negatives reported by a Security Information and Event Management (SIEM) system, the goal is to enhance the accuracy of the alerts and ensure that actual threats are identified correctly. The following sources of information best support the analysis process:

A. Third-party reports and logs: Utilizing external sources of information such as threat intelligence reports, vendor logs, and other third-party data can provide a broader perspective on potential threats. These sources often contain valuable insights and context that can help correlate events more accurately, reducing the likelihood of false positives and false negatives.

B. Trends: Analyzing trends over time can help inunderstanding patterns and anomalies in the data. By observing trends, the security team can distinguish between normal and abnormal behavior, which aids in fine-tuning the SIEM configurations to better detect true positives and reduce false alerts.

Other options such as dashboards, alert failures, network traffic summaries, and manual review processes are also useful but are more operational rather than foundational for understanding the root causes of reporting errors in SIEM configurations.