Pass the CompTIA CASP CAS-005 Questions and answers with ExamsMirror

User behavior analytics (UBA)detectsanomalousactivityby analyzing historical patterns and comparing them to recent behavior. The time shift in account activity suggestspotential compromise or misuse.

TTP-based inquiries (A)focus on known attack tactics, techniques, and procedures but do not involve behavior tracking.

Adversary emulation (C)simulates attacks but does not analyze real data trends.

OSINT analysis (D)gathers intelligence from public sources, which is unrelated to internal account behavior analysis.

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.

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 and validated 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.

In serverless computing, organizations rely heavily on CSPs to manage the infrastructure, runtime, and scaling. A key risk is thelevel of control and influence governments have over CSPs, potentially affecting availability, access, or confidentiality of hosted services due to legal orders or government actions. Concerns about virtualization technologies, scalability, or third-party monitoring are valid but less critical compared to the overarching legal and control risks tied to CSP reliance.

The best solution to reduce the likelihood of firmware-level attacks and rootkits is to implement measured boot. Measured boot is a hardware-assisted security mechanism that leverages Trusted Platform Module (TPM) and Secure Boot processes. It records cryptographic measurements of each stage of the boot process—from firmware to operating system loaders—and stores them in the TPM. Security software, such as attestation services, can then verify that the system booted into a known, trusted state. If firmware or boot-level code has been tampered with, the measurements will not match expected values, alerting administrators to compromise.

Option A (software integrity checks) validates application-level integrity but does not address firmware rootkits that load before the operating system. Option B (self-encrypting drives) protects data at rest but does not prevent rootkits. Option D (host-based encryption) ensures confidentiality but does not detect or mitigate firmware-level persistence.

Measured boot specifically targets low-level tampering, making it the most relevant control to defend against rootkits and firmware exploits.

To improve the quality of code scanning results and reduce false positives, the best solution is to limit the tool to a specific coding language and fine-tune the rule set. By configuring the code scanning tool to focus on the specific language used in the application, the tool can more accurately identify relevant issues and reduce the number of false positives. Additionally, tuning the rule set ensures that the tool's checks are appropriate for the application's context, further improving the accuracy ofthe scan results.

SecurityX CAS-005 network architecture objectives emphasize limiting exposure of vulnerable systems by using application-aware firewalls with strict rule sets.

This approach directly reduces the attack surface by allowing only approved application traffic to and from the vulnerable systems, mitigating risk until systems are patched or replaced.

EDR (A) enhances detection but doesn’t inherently reduce the exposed services.

Network segmentation in monitor mode (B) doesn’t block threats.

IDS (C) detects activity but does not block it.

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 error message"NET::ERR_CERT_WEAK_SIGNATURE_ALGORITHM" indicates that the web browser is rejecting the certificate because it uses a weak signature algorithm. This commonly happens with self-signed certificates, which often use outdated or insecure algorithms.

Why Discontinue Self-Signed Certificates?

Security Compliance: Modern browsers enforce strict security standards and may reject certificates that do not comply with these standards.

Trusted Certificates: Using certificates from a trusted Certificate Authority (CA) ensures compliance with security standards and is less likely to be flagged as insecure.

Weak Signature Algorithm: Self-signed certificates might use weak algorithms like MD5 or SHA-1, which are considered insecure.

Other options do not address the specific cause of the certificate error:

A. Rewriting legacy web functions: Does not address the certificate issue.

B. Disabling deprecated ciphers: Useful for improving security but not related to the certificate error.

C. Blocking non-essential ports: This is unrelated to the issue of certificate validation.

OWIN23 is running Windows 7, which is a legacy operating system. Many EDR solutions no longer provide full support for outdated operating systems like Windows 7, which has reached its end of life and is no longer receiving security updates from Microsoft. This makes such systems more vulnerable to infections and attacks, including remote access Trojans (RATs).

A. OWIN23 uses a legacy version of Windows that is not supported by the EDR: This is the most probable cause because the lack of support means that the EDR solution may not fully protect or monitor this system, making it an easy target for infections.

B. LN002 was not supported by the EDR solution and propagates the RAT: While LN002 is unmanaged, it is less likely to propagate the RAT to OWIN23 directly without an established vector.

C. The EDR has an unknown vulnerability that was exploited by the attacker: This is possible but less likely than the lack of support for an outdated OS.

D. OWIN29 spreads the malware through other hosts in the network: While this could happen, the status indicates OWIN29 is in a bypass mode, which might limit its interactions but does not directly explain the infection on OWIN23.