Changed CAS-004 Exam Questions

Agent-based scanning is best suited for environments with multiple subnets, VLANs, and branch offices, as described. It allows for fast scanning with fewer false positives, and since the agents are installed on the servers, they tend to have a lower impact on performance. This type of scanning also facilitates signature-based scanning, which is one of the customer's requirements.

While the company has implemented Single Sign-On (SSO) with strong passwords, additional security controls are required to mitigate attacks such as LDAP injections, brute-force, whaling, and spear-phishing. Two-factor authentication (2FA) provides an additional layer of security by requiring users to provide two different forms of authentication (e.g., a password and a security token or a biometric factor), reducing the likelihood of unauthorized access even if passwords are compromised. CASP+ emphasizes the importance of using multi-factor authentication mechanisms to strengthen access control and protect against such attacks.

References:

CASP+ CAS-004 Exam Objectives: Domain 2.0 – Enterprise Security Operations (Access Control and Multi-factor Authentication)

CompTIA CASP+ Study Guide: Implementing Two-Factor Authentication for System Access

OAuth, which stands for Open Authorization, is a standard for authorization that enables secure token-based access. It allows users to grant a web application access to their information on another web application without giving them the credentials for their account. OAuth is particularly useful for rapid authentication, flexible authorization, ease of deployment, and offers high functionality at a low cost, making it an ideal choice for new web-based applications. This approach is well-suited for situations where web applications need to interact with each other on behalf of the user, without sharing user's password, such as integrating a geolocation application with Facebook. OAuth uses tokens issued by an authorization server, providing restricted access to a user's data, which aligns with the objectives of rapid authentication, flexible authorization, ease of deployment, and cost-effectiveness​​.

The most significant risk to the development of a machine-learning-based threat detection tool is the Big Data processing required for maturity. Machine learning models often require large datasets to train effectively, and processing and analyzing this data can be time-consuming and resource-intensive. This can delay the development timeline, especially in a rapid CI/CD pipeline environment where timely delivery is crucial. CASP+ highlights the challenges associated with machine learning and Big Data in security tool development, particularly the resource demands and the need for extensive data to ensure accuracy and maturity.

References:

CASP+ CAS-004 Exam Objectives: Domain 2.0 – Enterprise Security Operations (Big Data and Machine Learning Challenges)

CompTIA CASP+ Study Guide: Implementing and Managing Machine Learning in Security Environments