The eradication phase in incident response involveseliminating the root cause of the incidentand strengthening defenses to prevent reoccurrence. In this case:

Intrusion Prevention System (D): Adding new rules to the IPS to detect and block malicious activity on TCP/135 is a direct eradication step to remove the threat’s entry point and prevent future attacks.

Centralized User Management (C): Hardening user accounts, removing unnecessary permissions, and applying tighter authentication/authorization measures helps eliminate the possibility that threat actors could exploit weak or mismanaged accounts to continue accessing the system.

Althoughanti-malware software (A)andenterprise block listing (E)are valuable, themost direct eradication stepshere specifically involve managing network access (via IPS) and strengthening user controls (via centralized user management), especially when TCP/135 (MSRPC endpoint mapper) can be used to enumerate services and potentially access vulnerable endpoints remotely.

This aligns with best practices outlined in incident response frameworks (such as the NIST SP 800-61 and referenced resources), which emphasizeclosing the exploited entry points(in this case, TCP/135) andremoving any lingering access pointsthrough user management and network control enhancements.

The Wireshark output shows SMB protocol transactions, including NT Create AndX Response and Write AndX Response, indicating the transfer of files or objects. SMB (Server Message Block) is a protocol used for file sharing and printer access in Windows networks. The log does not indicate phishing or redirection behavior but rather normal SMB communication such as accessing files or shared resources.

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Volatility is an open-source memory forensics tool specifically designed for memory analysis. It allows forensic investigators to inspect memory dumps for running processes, hidden processes, injected code, and malicious activity in memory.

As per the Cisco CyberOps Associate study guide, “Volatility helps security professionals with both incident response and malware analysis. It can identify processes, registry artifacts, network connections, and memory-resident malware”.

While Memoryze (D) is also a memory analysis tool, Volatility is the more recognized, command-line driven tool used widely in industry and is directly highlighted in the curriculum.

According to theCyberOps Technologies (CBRFIR) 300-215 study guidecurriculum, when analyzing suspicious behavior—especially when scripts or shell commands are executed from applications like Word (which is uncommon)—the encoded PowerShell payload must be decoded to determine if malicious intent is present. Deobfuscation is a critical step in identifying command-and-control behavior, persistence, or malware execution paths.

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The Cisco study material recommends integrating automation for log/event collection and contextual analysis to reduce detection delays and ensure rapid identification of anomalies. It also emphasizes the need for pre-defined roles and documented steps in anIncident Handling Playbook, following NIST SP 800-61 Rev.2 standards, to improve consistency and readiness during incidents.

Comprehensive and Detailed Explanation:

The log entries show repeated SSH login attempts for various invalid usernames (e.g., admin, phoenix, rainbow, test, user, etc.) from different source ports. These are clear signs of a brute-force attack—an automated process trying multiple usernames and passwords in hopes of gaining access.

Mitigating such attacks includes:

Implementing account lockout policies (e.g., locking an account after several failed login attempts).

Enabling Multi-Factor Authentication (MFA) to ensure that password guessing alone is insufficient for account access.

Therefore, the correct answer is:

D. Brute-force attack; implement account lockout policies and roll out MFA.

To prepare a post-incident report, thecauseof the incident (what enabled it) and theeffect(what damage was done) are the primary components analyzed first. This allows teams to understand vulnerabilities exploited and the consequences, forming the basis for corrective action.

The Cisco CyberOps guide recommends beginning withroot cause analysisfollowed by impact assessment to guide future prevention strategies.

Cisco Firepower Management Center (FMC), when configured with Snort rules, classifies attacks with signature categories such as FILE-OFFICE for Microsoft Office-based exploits. One of the critical threats involving Microsoft Office is a known vector involving Microsoft Graphics, which attackers exploit forremote code execution (RCE). RCE vulnerabilities enable attackers to execute arbitrary commands or code on the target machine—making this classification high-severity.

The alert "FILE-OFFICE Microsoft Graphics remote code execution attempt" is consistent with what Cisco and Snort define for such threats and appears in rulesets addressing vulnerabilities like CVE-2017-0001.

In VMware ESXi systems, the vmksummary.log file is responsible for capturing general system events, including uptime, reboot statistics, and key service-related issues. It serves as a valuable source for troubleshooting persistent or unexplained system behaviors.

The Cisco CyberOps study guide references log file paths used in system diagnostics and incident response, and for authentication-related issues on ESXi where standard logs don't yield insights, vmksummary.log is the recommended next source for identifying systemic service faults or anomalies.

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According to the Cisco Certified CyberOps Associate guide (Chapter 5 - Identifying Attack Methods), attachments in emails—especially with file extensions like.xlsm—are high-risk indicators when analyzing suspicious or phishing emails. Malicious actors often use macro-enabled Excel files (.xlsm) as a payload delivery mechanism for malware or other exploits. These attachments are typically disguised as legitimate content such as refunds or invoices to trick the recipient into opening them.

The presence of“Card_Refund_18_6913.xlsm”is a strongIndicator of Compromise (IoC), as.xlsmfiles can contain VBA macros capable of executing malicious code. This matches exactly with examples provided in the study material discussing how macro-based payloads are delivered and recognized.

Hence,option Cis the most direct indicator of attack in this email.

The Python code snippet:

Usessocket.socket(AF_INET, SOCK_STREAM), which indicatesTCP communication

Connects to a remote server (192.168.1.10on port 80)

Sends a manual HTTPGETrequest

Receives the response usings.recv()

This is a classic example ofTCP/IP socket programming, specifically creating asimple TCP clientto communicate with a web server. It does not monitor traffic or crawl websites — it sends a crafted request and prints the response.

Thus, this code best fits:

D. socket programming listener for TCP/IP communication.

In the provided Wireshark capture, we see multiple TCP SYN packets being sent from different source IP addresses to the same destination IP address(192.168.1.159:80)within a short time window. These SYN packets do not show a corresponding SYN-ACK or ACK response, indicating that these TCP connection requests are not being completed.

This pattern is indicative of aSYN flood attack, a type of Denial of Service (DoS) attack. In this attack, a malicious actor floods the target system with a high volume of TCP SYN requests, leaving the target's TCP connection queue (backlog) filled with half-open connections. This can exhaust system resources, causing legitimate connection requests to be denied or delayed.

Thecountermeasurefor this scenario, as highlighted in theCyberOps Technologies (CBRFIR) 300-215 study guideunderNetwork-Based Attacks and TCP SYN Flood Attacks, involves:

Increasing the backlog queue: This allows the server to hold more half-open connections.

Recycling the oldest half-open connections: This ensures that legitimate connections have a chance to be established if the backlog fills up.

According to theCyberOps Technologies (CBRFIR) 300-215 study guide, during thepost-incident activityphase, it is critical to analyze lessons learned and update processes to ensure quicker and more efficient response in the future. Specifically:

Introducing a priority rating for incident response workloads(A) helps address the issue of team members being occupied with other tasks and unable to prioritize abnormal system activity. This ensures incidents are handled based on severity, not just workload.

Creating an executive team delegation plan(D) addresses the issue of delays due to unavailability of management for approvals. It ensures alternative decision-makers are available for swift action.

These strategies are based on the NIST SP 800-61 Rev. 2 recommendations and are highlighted in the Cisco guide’s post-incident activity phase (page 418), which emphasizeslessons learnedand how to reduce detection and response times for future incidents.

Fileless malware resides in memory and does not leave traditional file artifacts, making it difficult for antivirus solutions to detect. The most effective next step is to isolate the endpoints to prevent lateral movement and perform memory forensics to capture volatile data and identify any running malicious processes.

The error logs indicate multiplePKCS12andASN.1 decodingerrors, such as:

PKCS12 routines:PKCS12_parse:mac verify failure

rsa routines:old_rsa_priv_decode:RSA lib

PKCS12 routines:PKCS12_key_gen_uni:malloc

These specific errors most commonly occur when:

Theprivate key does not correspondto the certificate being used.

There is amismatchbetween the public and private key pair required for SSL handshakes.

This is a well-documented condition in Apache SSL configuration issues and explicitly covered under TLS/SSL troubleshooting sections in cybersecurity operations contexts. The Cisco CyberOps guide also notes that SSL errors with key verification usually result from "improper key/certificate pairing" rather than file corruption or missing modules.

Thus, the correct answer is:

B. The private key does not match with the SSL certificate.

The described scenario includes both internal alerts (unusual network traffic, failed logins, suspicious file access) and external intelligence indicating active ransomware campaigns in the same industry. This constitutes a strong combination of precursors and indicators, as defined in the NIST SP 800-61 incident handling model and reinforced in the Cisco CyberOps Associate curriculum.

According to the Cisco guide:

“Once an incident has occurred, the IR team needs to contain it quickly before it affects other systems and networks within the organization.”

“The containment phase is crucial in stopping the threat from spreading and compromising more systems”.

Given these indicators and the high-value nature of the data involved, it is essential to proactively isolate suspected systems and activate the incident response plan to prevent damage from potential ransomware.

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The exhibit shows a series of process executions that form a suspicious chain involving scripting engines and obfuscated commands:

One critical indicator iscmd.exe executing PowerShell with obfuscated (Base64-encoded) arguments. The use of Base64 is a known method used by attackers to mask malicious commands. This aligns with attack techniques defined under MITRE ATT&CK T1059 (Command and Scripting Interpreter) and T1086 (PowerShell abuse). Therefore, option D is valid.

Another important IOC isWScript.exe acting as a parent of cmd.exe, which is abnormal in typical business environments. This indicates potential misuse of Windows Script Host (WSH) to launch commands, often seen in phishing or malware dropper scenarios. Thus, option E is also valid.

Options A and B by themselves are not definitive IOCs—PowerShell and cmd.exe are legitimate administrative tools and frequently used in Windows environments.

Option C is not supported by the exhibit—the reverse (powershell.exe initiated by WScript.exe) is what's seen, not the other way around.

These patterns align with theCyberOps Technologies (CBRFIR) 300-215 study guide, which specifies that chaining of interpreters (e.g., WScript → cmd → PowerShell) with encoded commands is a key indicator of compromise during forensic analysis.

In cloud environments, investigators typically do not have access to the physical storage devices where the data resides. This restricts traditional forensic processes, such as imaging or direct disk access, which are commonly used in on-premises investigations.

The PowerShell cmdlet Get-Content reads content line-by-line from a file and is commonly used for processing logs or large text files. When combined with Select-String, it can search for specific patterns (such as "ERROR" or "SUCCESS") within those lines and return a collection of matching objects, including metadata like line number and line content.

Option D uses:

Get-Content –Path: Correct syntax to read the log file from a UNC path.

Select-String “ERROR”, “SUCCESS”: Searches for these terms in each line and returns matching lines as structured output.

The other options (A, B, C) use non-existent or incorrect cmdlets/parameters such as Get-Content-Folder, –ifmatch, –Directory, which are invalid in PowerShell.

Since the phishing email originates from a known compromised cloud provider (XYZCloud), the correct immediate action for the security analyst is to determine the broader scope of exposure. This involves checking whether other users in the organization received similar emails from the same potentially malicious source. Therefore, querying for emails from theIP address rangesorSMTP domainslinked to XYZCloud is essential for identifying other possible attack vectors.

This step aligns with the containment phase of the incident response lifecycle, as outlined in theCyberOps Technologies (CBRFIR) 300-215 study guide, where threat hunting and log analysis are used to determine the extent of compromise and prevent lateral movement or further exposure. Only after the scope is understood should remediation or reporting actions follow.

TCPdumpis a CLI-based packet capture tool that is widely used for real-time traffic inspection and analysis on Unix/Linux systems.

TCPsharkis a variant CLI tool used similarly for packet analysis.

AlthoughWiresharkis a powerful network protocol analyzer, it requires a GUI. Therefore, it is not suitable for environments without a graphical interface.

The alert shown is based on aSnort rulefor aUnicode directory traversal attack against IIS web servers(Microsoft platform). The key detail here is the payload content"../..%c0%af../"which is a classic IIS-specific exploit related toCVE-2000-0884.

Since the company only usesUnix systems, they arenot vulnerableto this IIS-specific attack. Therefore, these alerts are triggered by irrelevant traffic or misapplied signatures, resulting inFalse Positives.

As defined in the Cisco CyberOps guide:

“False Positive: an alert is generated for traffic that is not actually malicious or relevant to the protected environment”.

YARA rulesare primarily used for malware classification and detection based onbinary pattern matchingwithin files. They describe sequences of bytes, strings, and other file characteristics found in malicious binaries.

The Cisco CyberOps Associate guide explains:"YARA rules operate by inspecting binary data using conditions and string matches to identify specific patterns that indicate known malware samples.".

From the exhibit, the first artifact (PE32 executable fromsyracusecoffee.com) and the second artifact (HTML fromqstride.com) suggest astaged malware deliverymethod. The executable and the HTML file are linked to different domains, often indicating redirection or multi-stage infection strategies, which is common in phishing or malvertising campaigns.

The Cisco guide explains this tactic as:“One file may appear benign but can initiate downloads or connections to external resources to fetch additional payloads or redirect users”. This pattern of domain redirection strongly supportsOption B.

YARA rulesare designed to identifyfilesthat match specific patterns, strings, or binary characteristics.

The Cisco CyberOps guide states:

“YARA helps researchers and analysts identify and classify malware samples based on textual or binary patterns”.

The string shown is long, alphanumeric, and includes both uppercase and lowercase letters with numbers—characteristics of Base64 encoding. This format is widely used to obfuscate payloads in malicious scripts, particularly in phishing or malware campaigns. Base64 encoding is also supported by Python and other platforms for data transformation.

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Input validation (A) is a critical countermeasure to defend against command injection and related vulnerabilities, as discussed in the Cisco guide. Proper validation ensures that malicious commands or payloads are not accepted or executed by the web application.

File integrity monitoring (E) helps detect unauthorized changes such as log deletion or binary modification, making it a crucial tool in recognizing and investigating tampering attempts.Blocking port 443 (B) would disable HTTPS and is not a practical solution. Antivirus (C) does not prevent form-based application attacks, and merely updating the application (D) may not be sufficient without addressing the underlying input validation flaw.

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One of the primary concerns when gathering forensic evidence in public cloud environments is the issue of multitenancy. In a shared cloud infrastructure, multiple tenants (organizations or users) operate on the same physical hardware, using virtualization to logically separate resources. This architecture poses a significant challenge for forensic investigations because:

Forensic investigators must ensure that they do not inadvertently access or expose data belonging to other tenants while collecting evidence.

This can limit access to low-level system data or hardware-level logs that might be essential for a thorough forensic analysis, since providers must enforce strict data isolation policies.

This concern is recognized in industry practices and guidelines, including NIST SP 800-86, which underscores the need to collect data in a forensically sound and legally defensible manner—something made more complex in shared environments.

The Cisco CyberOps Associate guide emphasizes the challenges of evidence handling in cloud environments, stating that "gathering evidence in the cloud must be carefully performed to ensure compliance with legal standards and to respect the boundaries of other tenants' data".

The XML (STIX/CybOX format) details anemail-based threatindicator. Specifically:

Theemail addresscontains “@state.gov” (not exact match, so blocking all @state.gov would be overbroad).

Theattachment is a PDFfile with a specifiedMD5 hash: cf2b3ad32a8a4cfb05e9dfc45875bd70.

Theattachment sizeis 87022 bytes.

From a threat mitigation perspective:

Ais correct: Updating AV to block or flag files matching the malicious hash is a standard response.

Dis correct: The email address context and hash together provide a precise rule for blocking—this prevents false positives.

Incorrect options:

Boverreaches by blocking an entire domain without confirming threat context.

Cwould stop all PDFs, which is impractical.

Eis incorrect; there is no indication that the hash appears in the subject line.