CAS-005 Exam Dumps - CompTIA SecurityX Certification Exam

VPN Concentrator:

A screenshot of a computer Description automatically generated

AAA Server:

A screenshot of a computer Description automatically generated

User and Entity Behavior Analytics (UEBA) is the best solution to help the company overcome challenges associated with suspicious activity that cannot be categorized by traditional detection tools. UEBA uses advanced analytics to establish baselines of normal behavior for users and entities within the network. It then identifies deviations from these baselines, which may indicate malicious activity. This approach is particularly effective for detecting unknown threats and sophisticated attacks that do not match known indicators of compromise (IoCs).

The logs indicate unauthorized access from104.18.16.29, an external IP, to the building camera’s administrative console during off-hours.Restricting access only to approved IPsensures that only authorized personnel can remotely control the cameras, reducing the risk of unauthorized access and manipulation.

Implementing WAF protection (A)secures against web application attacks but does not restrict unauthorized administrative access.

Upgrading the firmware (B)is good security hygiene but does not immediately mitigate the active threat.

Blocking IP 104.18.16.29 (D)is a temporary measure, as an attacker can switch to another IP. A better long-term solution is whitelisting trusted IPs.

Collecting a large pool of behavioral observations requires handling vast datasets, which is the domain ofBig Data. Big Data technologies enable the storage, processing, and analysis of large-scale data (e.g., user behavior logs) to inform decisions, a key capability in security analytics.

Option A:Linear regression is a statistical method for modeling relationships, not collecting data.

Option B:Distributed consensus relates to agreement in distributed systems (e.g., blockchain), not data collection.

Option C:Big Data directly supports collecting and analyzing large datasets for insights, fitting the question perfectly.

Option D:Machine learning uses data to train models but relies on data being collected first, often via Big Data.

To meet the requirements of having allendpoints establish telemetry with a SIEM, integrate into an XDR platform, and allow SOC services to monitor the XDR platform, the best approach is to implement Host Intrusion Prevention Systems (HIPS) and a host-based firewall. HIPS can provide detailed telemetry data to the SIEM and can be integrated into the XDR platform for comprehensive monitoring and response. The host-based firewall ensures that only authorized traffic is allowed, providing an additional layer of security.

The technique that best addresses the issue of insider threats from employees who have individual access to encrypted material is key splitting. Here’s why:

Key Splitting: Key splitting involves dividing a cryptographic key into multiple parts anddistributing these parts among different individuals or systems. This ensures that no single individual has complete access to the key, thereby mitigating the risk of insider threats.

Increased Security: By requiring multiple parties to combine their key parts to access encrypted material, key splitting provides an additional layer of security. This approach is particularly useful in environments where sensitive data needs to be protected from unauthorized access by insiders.

Compliance and Best Practices: Key splitting aligns with best practices and regulatory requirements for handling sensitive information, ensuring that access is tightly controlled and monitored.

Malware that does not execute in a sandbox environment often contains anti-analysis techniques, such as anti-virtualization code. This code detects when the malware is running in a virtualized environment and alters its behavior to avoid detection. Checking for anti-virtualization code is a logical next step because:

It helps determine if the malware is designed to evade analysis tools.

Identifying such code can provide insights into themalware's behavior and intent.

This step can also inform further analysis methods, such as running the malware on physical hardware.

Useruser-cis showinganomalous behavior across multiple machines, attempting to run administrative tools such as cmd.exe and appwiz.CPL, which are commonly used by attackers for system modification. The activity pattern suggests a lateral movement attempt, potentially indicating a compromised account.

user-a (A)anduser-b (B)attempted to run applications but only on one machine, suggesting less likelihood of compromise.

user-d (D)was blocked running cmd.com, but user-c’s pattern is more consistent with an attack technique.