300-220 Exam Dumps : Conducting Threat Hunting and Defending using Cisco Technologies for Cybersecurity 300-220 CBRTHD

The correct answers areA. Service and version of the web serverandC. Technology used by the application. The error message shown in the exhibit is a classic example ofverbose error handling, which unintentionally discloses sensitive internal details about the web application stack.

First, the error page explicitly referencesApache Tomcat/6.0.16at the bottom. This directly exposes theweb server/service and its exact version, makingOption Acorrect. From an attacker’s perspective, this is valuable intelligence because it allows them to search forknown vulnerabilities, exploits, or misconfigurationsspecific to that version of Tomcat. Older versions of Tomcat, in particular, have a long history of publicly documented security flaws.

Second, the stack trace references components such as:

org.apache.jasper.compiler.*

.jsp files (e.g., /user/left.jsp)

javax.servlet.http.HttpServlet

These details clearly reveal thetechnology stack used by the application, namelyJava Server Pages (JSP)running onApache Tomcat with Apache Jasper. This confirmsOption Cas correct. Exposing application technology helps attackers tailor attacks such as deserialization exploits, JSP injection attempts, or framework-specific vulnerabilities.

Option B is incorrect because the error message doesnotstate or imply that Apache Jasper is vulnerable to path injection; it merely shows a compilation/runtime error. Option D is incorrect because the error page provides no information about theclient-side browser version—all disclosed details relate to server-side processing.

From a professional security and threat hunting perspective, verbose error messages significantlyincrease attack surface visibility. Best practices dictate that production systems should returngeneric error messagesto users while logging detailed stack traces internally. This scenario reinforces why proper error handling and information disclosure controls are critical defensive measures.

In summary, the penetration test error message exposes:

Theweb server service and version

Theapplication technology stack

Therefore, the correct answers areA and C.

The correct answer isMonitoring failed AWS console login attempts. The Bash script shown in the exhibit is clearly designed toparse AWS CloudTrail logsand extract specific authentication-related events.

Breaking down the script behavior from a professional cloud security perspective:

gunzip -c *.json.gz indicates the script is processingcompressed CloudTrail log files, which are typically stored in .json.gz format.

jq -c '.Records[]' parses individual CloudTrail records, a common approach when analyzing AWS activity logs.

The filter conditions explicitly check for:

eventSource == "signin.amazonaws.com"

eventName == "ConsoleLogin"

responseElements.ConsoleLogin == "Failure"

These fields are definitive indicators offailed AWS Management Console login attempts. Additionally, the script extracts contextual fields such as:

Event time

Source IP address

Error message

AWS region

Username

MFA usage status

This data is exactly what security teams use to detectcredential abuse, password spraying, brute-force attempts, and compromised IAM accounts. Monitoring failed console logins is a foundational cloud threat hunting activity, especially for identifying early stages of account takeover.

Option B is incorrect because the script does not establish AWS CLI sessions or authenticate to accounts. Option C is incorrect because instance errors would involve services like ec2.amazonaws.com and different event names. Option D is incorrect because the script is analyzing—not archiving—records, and it applies filtering logic rather than storage or lifecycle management.

From a threat hunting and cloud security standpoint, this script supportsidentity-focused detection, which is critical in AWS environments where IAM misuse is one of the most common initial access vectors. It aligns withMITRE ATT&CK – Credential Access and Initial Access, particularly techniques involving valid account abuse.

In summary, the script’s clear purpose is tomonitor failed AWS console login attempts, makingOption Athe correct and professionally validated answer.

The correct next action is tosubmit the file for sandboxing. In professional security operations and threat hunting workflows, sandboxing is the most appropriate step when a file originates from an untrusted source and hash-based reputation checks return anunknownresult. An unknown hash means the file has not yet been classified as benign or malicious by threat intelligence databases, which is common with newly created malware or targeted attacks.

Sandboxing allows the security team to performdynamic analysisby executing the file in an isolated, controlled environment. This process observes runtime behaviors such as process creation, registry modification, network communications, command-and-control callbacks, file system changes, and exploit attempts. These behaviors provide high-fidelity indicators that static analysis or hash lookups cannot reveal.

Option B, reviewing the directory path, is useful for contextual awareness but does not determine whether the file is malicious. Option C, running a full malware scan, is premature; modern malware often evades signature-based scans, especially when the file is previously unknown. Option D, investigating the reputation of the website, is a supporting activity but does not assess the actual behavior or payload of the downloaded file.

From a threat hunting and incident response standpoint, sandboxing bridges the gap betweendetection and confirmation. If the sandbox analysis confirms malicious behavior, the team can escalate to containment actions such as isolating the endpoint, blocking hashes and domains, and performing scope analysis to identify other affected systems. Additionally, sandbox results can be used to create new SIEM detections and EDR behavioral rules, strengthening future defenses.

This approach aligns with professional best practices:unknown file + untrusted source = dynamic analysis first. It ensures accurate classification while minimizing unnecessary disruption to the user or environment.