Cisco 300-215 - Conducting Forensic Analysis and Incident Response Using Cisco CyberOps Technologies (CBRFIR)

The alert shown is based on a Snort rule for a Unicode 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 to CVE-2000-0884.

Since the company only uses Unix systems, they are not vulnerable to this IIS-specific attack. Therefore, these alerts are triggered by irrelevant traffic or misapplied signatures, resulting in False 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”.

The root cause analysis in incident response focuses on identifying the initial trigger or root cause of the incident to understand how it started and how to prevent recurrence. In this scenario, the phishing email sent to the victim (A) is the initial trigger that led to the employee’s action of clicking the malvertising link, resulting in the malware download.

The other options represent later stages in the incident response cycle, such as detection (SIEM alert, cybersecurity team’s alert) or supporting evidence (email header information), but they do not address the root cause, which is the phishing email itself.

This aligns with the CyberOps Technologies (CBRFIR) 300-215 study guide, which states that identifying the initial vector of compromise is critical to the root cause analysis phase of incident response (Chapter: Incident Response Techniques, page 410-412).

When dealing with suspected malicious activity involving obfuscated PowerShell scripts—especially when launched from Microsoft Word documents—behavioral analysis is the most critical next step. This approach helps in determining if the process chain is part of a known attack pattern, such as a phishing attempt using malicious macros that launch PowerShell for data exfiltration or payload download.

As highlighted in the CyberOps Technologies (CBRFIR) 300-215 study guide, understanding behavior and deobfuscating PowerShell scripts is an essential part of the forensic and incident response process. Specifically:

During the detection and analysis phase, if PowerShell is used with obfuscated or encoded commands, responders should investigate the intent and behavior of the command.

Deobfuscation allows analysts to see what the script is doing (e.g., downloading files, creating persistence mechanisms, or opening a reverse shell).

The guide states:

“For example, if the threat is malware, the compromised system should be immediately isolated and the malware should be placed in a sandbox or a detonation chamber to understand what it is trying to do”.

This confirms that understanding execution behavior (such as what the PowerShell script intends to perform) is key to uncovering indicators of compromise (IoCs).

Thus, option C—conducting a behavioral analysis and deobfuscating PowerShell—is the most critical and effective response at this stage.

The safest and most effective approach is to isolate the files and subject them to heuristic and behavioral analysis. This can reveal obfuscated malware or unauthorized data storage techniques, even if signature-based antivirus fails to flag them.

To determine the correct script, we evaluate the following requirements:

The script must search for the IP address 192.168.100.100.

The output should be written to a file named parsed_host.log.

The matching lines should be printed to the console.

Analysis of the options:

Option A: Correct IP regex used and correct output filename, but reads from parsed_host.log instead of a source log file like test_log.log (not ideal for initial parsing).

Option C: The IP address used is 192.168.100.101 instead of 192.168.100.100 — incorrect.

Option D: Same IP address and logic as Option B, but uses print statement without parentheses, which is not valid in Python 3 unless using Python 2 — not ideal.

✅ Option B:

Uses correct IP: "192.168.100.100"

Reads from test_log.log (presumably the source log file).

Writes to output/parsed_host.log.

Prints each matching line and writes to output file — satisfying all conditions.

Comprehensive and Detailed Explanation:

Endpoint Detection and Response (EDR) tools provide behavioral analytics and continuous monitoring to detect malware such as backdoors, which is especially critical on endpoints like macOS devices. These tools are essential to detect post-compromise activities and contain threats before they spread.

Secure Email Gateway (e.g., Cisco ESA) plays a key role in blocking phishing emails—the initial vector in this attack. It uses filters and reputation analysis to prevent malicious links or attachments from reaching end users.

Incorrect Options:

C. DLP focuses on preventing data exfiltration, not phishing prevention or backdoor detection.

D. IPS is effective for known signature-based threats but less effective against phishing links and endpoint-level backdoors.

E. WAF protects web servers, not end-user devices from phishing or backdoor infections.

Therefore, the correct answers are: A and B.

The log entry shows a failed SSH login attempt for an invalid user “admin” from IP 192.168.1.100. As the system has just gone live and no legitimate use is expected, this could be an early reconnaissance or brute-force attempt. However, blocking IPs or resetting passwords without fully understanding the context could lead to incomplete remediation or false positives.

According to Cisco CyberOps best practices, the first step is to thoroughly investigate the alert by correlating it with other logs (e.g., authentication logs, IDS/IPS logs) to determine the intent and scope of activity.

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The Wireshark capture shows a series of HTTP requests and responses:

The client (10.1.21.101) sends a GET request for /Lk9tdZ.

The server (209.141.51.196) responds with HTTP/1.1 302 Found, which is a standard HTTP status code indicating a redirection.

The subsequent GET request from the client is for /files/1.bin, which indicates it followed the redirect.

This behavior confirms that the server is issuing an HTTP 302 redirect from the initial request path /Lk9tdZ to /files/1.bin. This is often observed in malware command-and-control behavior or file download staging.

Option A is incorrect: 302 is a status code, not a data size.

Option C is incorrect: port 49723 is a source/destination ephemeral port, not a redirect target.

Option D is incorrect: communication is over HTTP, not HTTPS (which would indicate encryption).

The goal of the given Python code is to parse an Apache access log and extract IP addresses using regular expressions (regex). In this context, the most appropriate regex pattern to extract IPv4 addresses from log data is:

r'\d{1,3}.\d{1,3}.\d{1,3}.\d{1,3}'

This pattern matches typical IPv4 addresses, where each octet consists of 1 to 3 digits separated by periods. For example, it matches addresses like 192.168.1.1 or 10.0.0.123. The pattern uses:

\d{1,3} to capture between 1 and 3 digits,

\. to match the dot (escaped since . is a special character in regex),

repeated 4 times with proper separation to form the full IPv4 structure.

Options A, B, and C either include incorrect syntax, improper escape sequences, or do not represent a valid IP address pattern.

This type of log analysis and pattern extraction is described in the Cisco CyberOps Associate curriculum under basic scripting and automation techniques used in log and artifact analysis.