CAS-004 Exam Dumps - CompTIA CASP Questions and Answers

Modeling user behavior and monitoring for deviations from normal and continuously monitoring code commits to repositories and generating summary logs are actions that will enable the data feeds needed to detect unauthorized insertions into application development environments and authorized insiders making unauthorized changes to environment configurations. Modeling user behavior and monitoring for deviations from normal is a technique that uses baselines, analytics, machine learning, or other methods to establish normal patterns of user activity and identify anomalies or outliers that could indicate malicious or suspicious behavior. Modeling user behavior and monitoring for deviations from normal can help detect unauthorized insertions into application development environments, as it can alert on unusual or unauthorized access attempts, commands, actions, or transactions by users. Continuously monitoring code commits to repositories and generating summary logs is a technique that uses tools, scripts, automation, or other methods to track and record changes made to code repositories by developers, testers, reviewers, or other parties involved in the software development process. Continuously monitoring code commits to repositories and generating summary logs can help detect authorized insiders making unauthorized changes to environment configurations, as it can audit and verify the source, time, reason, and impact of code changes made by authorized users. Performing static code analysis of committed code and generate summary reports is not an action that will enable the data feeds needed to detect unauthorized insertions into application development environments and authorized insiders making unauthorized changes to environment configurations, but an action that will enable the data feeds needed to detect vulnerabilities, errors, bugs, or quality issues in committed code. Implementing an XML gateway and monitor for policy violations is not an action that will enable the data feeds needed to detect unauthorized insertions into application development environments and authorized insiders makingunauthorized changes to environment configurations, but an action that will enable the data feeds needed to protect XML-based web services from threats or attacks by validating XML messages against predefined policies. Monitoring dependency management tools and report on susceptible third-party libraries is not an action that will enable the data feeds needed to detect unauthorized insertions into application development environments and authorized insiders making unauthorized changes to environment configurations, but an action that will enable the data feeds needed to identify outdated or vulnerable third-party libraries used in software development projects. Installing an IDS (intrusion detection system) on the development subnet and passively monitor for vulnerable services is not an action that will enable the data feeds needed to detect unauthorized insertions into application development environments and authorized insiders making unauthorized changes

The process ID 87 can be the starting point for an investigation of a possible buffer overflow attack, as it shows a high percentage of CPU utilization (99.7%) and a suspicious command name (graphic.linux_randomization.prg). A buffer overflow attack is a type of attack that exploits a vulnerability in an application or system that allows an attacker to write data beyond the allocated buffer size, potentially overwriting memory segments and executing malicious code. A high CPU utilization could indicate that the process is performing intensive or abnormal operations, such as a buffer overflow attack. A suspicious command name could indicate that the process is trying to disguise itself or evade detection, such as by mimicking a legitimate program or using random characters. The other process IDs do not show signs of a buffer overflow attack, as they have low CPU utilization and normal command names. Verified References: https://www.comptia.org/blog/what-is-buffer-overflow https://partners.comptia.org/docs/default-source/resources/casp-content-guide

Perfect Forward Secrecy (PFS) is a feature of certain key agreement protocols that ensures a session key derived from a set of long-term keys cannot be compromised if one of the long-term keys is compromised in the future. In the context of a VPN, PFS ensures that each session has a unique encryption key, and even if a key is compromised, it will not compromise past or future VPN sessions.

Step by Step Explanation:

Data labeling enables metadata tagging for data classification, which allows systems to filter, act, and enforce policies based on the labels.

Data mapping is used for understanding data flows but does not support automation.

Log scraping and resource tagging are unrelated to enabling system actions based on data classification.

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.

Comprehensive and Detailed Step by Step Explanation:

Due diligenceinvolves researching and understanding regulatory requirements (e.g., HIPAA) to ensure compliance for handling sensitive data like personal health information.

Data retentionrefers to how long data is stored, not compliance research.

Data classificationorganizes data by sensitivity but is not specific to compliance research.

Reference frameworksprovide guidelines for implementation but are not directly about research.

Risk acceptance is the decision to accept the potential risk and continue operating without engaging in extraordinary measures to mitigate it. If the cost of anti-malware exceeds the potential loss from a malware threat, it would be more cost-effective to accept the risk rather than spend more on mitigations that don't provide proportional value. This is part of a cost-benefit analysis in risk management.

Restricting HTTP methods can mitigate the risk of network-based attacks against an online store by limiting the types of HTTP requests that the server will accept, thus reducing the attack surface. This is a common method to prevent web-based attacks such as Cross-Site Scripting (XSS) and SQL Injection.

A digital signature is a cryptographic technique that allows the sender of a file to sign it with their private key and the receiver to verify it with the sender’s public key. This ensures the integrity and authenticity of the file, as well as the non-repudiation of the sender. A message hash or a message digest is a one-way function that produces a fixed-length output from an input, but it does not provide any information about the sender. A message authentication code (MAC) is a symmetric-key technique that allows both the sender and the receiver to generate and verify a code using a shared secret key, but it does not provide non-repudiation. References: [CompTIA Advanced Security Practitioner (CASP+) Certification Exam Objectives], Domain 2: Enterprise Security Architecture, Objective 2.1: Apply cryptographic techniques

Comprehensive and Detailed in-Depth Explanation:

Why the Correct Answer is C (A CDN with the origin set to its data center):

AContent Delivery Network (CDN)is specifically designed to address the requirements presented:

Low Latency for Global Users:

A CDN caches static and dynamic content onedge serversdistributed across the globe.

This minimizes latency forremote geographic locationsas content is served from thenearest edge serverrather than the centralized New York data center.

SSL Offloading:

Many CDNs offerSSL terminationat the edge, offloading theSSL/TLS handshake processfrom the origin server.

This improvesweb server performanceby reducing the computational load.

Protection Against DoS and DDoS Attacks:

CDNs are equipped withbuilt-in DDoS protection, absorbing andmitigating attacksat the edge rather than letting them hit the origin server.

This capability ensures that the application remainsavailableeven during attack attempts.

High Availability:

CDNs are designed forresiliency and redundancy.

Even if the origin data center goes down, cached content can still be served frommultiple edge locations, enhancing availability.

Why the Other Options Are Incorrect:

A. A cache server farm in its data center:

While it improves performancelocally, it does not reducelatency for global users.

It lacksDDoS protectionand high availability across regions.

B. A load-balanced group of reverse proxy servers with SSL acceleration:

This approach improvesSSL performanceandavailabilitywithin the data center but does not addressglobal latency.

It also does not inherently provideDDoS mitigation.

D. Dual gigabit-speed internet connections with managed DDoS prevention:

This solution addressesDDoS protection and availabilitybut notlow latency for remote users.

Thebottleneck remainsat the single data center location, leading tohigh latencyfor global users.

Real-World Scenario:

A social media application similar toInstagram or TikTokmust ensurefast content deliveryandresilient performanceworldwide. ACDNenables content to be deliveredcloser to the user, significantly reducingloading times. Furthermore, theSSL offloading and DDoS mitigationcapabilities protect both user data and service availability.

Extract from CompTIA SecurityX CAS-005 Study Guide:

TheCompTIA SecurityX CAS-005 Official Study Guidehighlights thatCDNsare essential for applications with aglobal user base. CDNs providelow latency, enhanced security (including DDoS protection), and increased availabilityby distributing content throughedge locations. This aligns perfectly with the organizational requirements outlined.

Steganalysis is the process of detecting hidden data in files or media, such as images, audio, or video. One technique of steganalysis is to identify least significant bit encoding, which is a method of hiding data by altering the least significant bits of each byte in a file. For example, a .wav file could contain hidden data encoded in the least significant bits of each audio sample. Steganalysis techniques can helpforensic responders to discover hidden evidence or malicious payloads. Breaking a symmetric cipher, determining the frequency of attacks, or maintaining chain of custody are not related to steganalysis. Verified References: https://www.comptia.org/blog/what-is-steganography https://partners.comptia.org/docs/default-source/resources/casp-content-guide

A WAF protects your web apps by filtering, monitoring, and blocking any malicious HTTP/S traffic traveling to the web application, and prevents any unauthorized data from leaving the app. It does this by adhering to a set of policies that help determine what traffic is malicious and what traffic is safe.

According to OWASP, LDAP injection is an attack that exploits web applications that construct LDAP statements based on user input without proper validation or sanitization. LDAP injection can result in unauthorized access, data modification, or denial of service. To prevent LDAP injection, OWASP recommends conducting input sanitization by escaping special characters in user input and deploying a web application firewall (WAF) that can detect and block malicious LDAP queries.45

This solution would address the three issues as follows:

Serving static content via distributed CDNs would reduce the latency for international users by delivering images from the nearest edge location to the user’s request.

Creating a read replica of the central database and pulling reports from there would offload the read-intensive workload from the primary database and avoid affecting the inventory data for order placement.

Auto-scaling API servers based on performance would dynamically adjust the number of servers to match the demand and balance the load across them at peak times.