The threat was detected from the time the emails were sent at 8:30 a.m. to when the recipients started alerting the organization's help desk about the email at 8:45 a.m., taking a total of 15 minutes. The detection time is the time elapsed between the occurrence of an incident and its discovery by the security team . The other options are either too short or too long based on the given information.

Potential precursor to an attack: Unauthorized network scans are often used by attackers to gather information about the network, such as identifying open ports, services, and vulnerabilities.
This information can then be used to plan and execute an attack.
The detection of an unauthorized scan is indicative of A. Potential precursor to an attack, as such scans are typically part of the reconnaissance phase in the cyber kill chain, used by attackers to identify potential targets and vulnerabilities within the network.

This log shows multiple 404 errors being triggered from requests to different directories or paths, which strongly suggests adirectory brute-force attack. In this type of attack, an adversary uses automated tools to enumerate directory or file paths in an attempt to find hidden or misconfigured resources. The frequent 404
"Not Found" HTTP responses from a single IP address attempting to access different URL paths is the signature pattern for directory brute-forcing. This behavior is not consistent with XSS, SQLi, or RCE, which would involve payloads or specific encoded commands, not merely probing paths.
Reference:
Chapple & Seidl,CompTIA CySA+ Practice Tests(Sybex, 2023), Question 149, p. 297 Objective 1.2 of CySA+ CS0-003 Exam Objectives: Analyze indicators of malicious activity such as scans
/sweeps, unusual traffic spikes, activity on unexpected ports

Explanation
High GPU utilization is the most likely indicator that cryptomining is occurring, as it reflects the intensive computational work that is required to solve the complex mathematical problems involved in mining cryptocurrencies. Cryptomining is the process of generating new units of a cryptocurrency by using computing power to verify transactions and create new blocks on the blockchain. Cryptomining can be done legitimately by individuals or groups who participate in a mining pool and share the rewards, or illegitimately by threat actors who use malware or scripts to hijack the computing resources of unsuspecting victims and use them for their own benefit. This practice is called cryptojacking, and it can cause performance degradation, increased power consumption, and security risks for the affected systems. Cryptomining typically relies on the GPU (graphics processing unit) rather than the CPU (central processing unit), as the GPU is better suited for parallel processing and can handle more calculations per second. Therefore, a high GPU utilization rate can be a sign that cryptomining is taking place on a system, especially if there is no other explanation for the increased workload. The other options are not as indicative of cryptomining as high GPU utilization, as they can have other causes or explanations. Bandwidth consumption can be affected by many factors, such as network traffic, streaming services, downloads, or updates. It is not directly related to cryptomining, which does not require a lot of bandwidth to communicate with the mining pool or the blockchain network. Unauthorized changes can be a result of many types of malware or cyberattacks, such as ransomware, spyware, or trojans.
They are not specific to cryptomining, which does not necessarily alter any files or settings on the system, but rather uses its processing power. Unusual traffic spikes can also be caused by various factors, such as legitimate surges in demand, distributed denial-of-service attacks, or botnets. They are not indicative of cryptomining, which does not generate a lot of traffic or requests to or from the system.

Data loss prevention (DLP) is a set of policies and tools that aim to prevent unauthorized disclosure of sensitive data. DLP transport rules are rules that apply to email messages that are sent or received by an organization's mail server. These rules can provide deep content analysis, which means they can scan the content of email messages and attachments for sensitive data patterns, such as client lists or contact information. If a rule detects a violation of the DLP policy, it can take actions such as blocking, quarantining, or notifying the sender or recipient. This would improve security and help prevent sales team members from sending sensitive client lists to their personal accounts. Reference: CompTIA Cybersecurity Analyst (CySA+) Certification Exam Objectives (CS0-002), page 14; https://docs.microsoft.com/en-us/exchange/security-and-compliance/mail-flow-rules/data-loss-prevention