CCOA Exam Dumps : ISACA Certified Cybersecurity Operations Analyst

A poorly enforcedBring Your Own Device (BYOD)policy can lead to the rise ofShadow IT, where employees use unauthorized devices, software, or cloud services without IT department approval. This often occurs because:

Lack of Policy Clarity:Employees may not be aware of which devices or applications are approved.

Absence of Monitoring:If the organization does not track personal device usage, employees may introduce unvetted apps or tools.

Security Gaps:Personal devices may not meet corporate security standards, leading to data leaks and vulnerabilities.

Data Governance Issues:IT departments lose control over data accessed or stored on unauthorized devices, increasing the risk of data loss or exposure.

Other options analysis:

A. Weak passwords:While BYOD policies might influence password practices, weak passwords are not directly caused by poor BYOD enforcement.

B. Network congestion:Increased device usage might cause congestion, but this is more of a performance issue than a security risk.

D. Unapproved social media posts:While possible, this issue is less directly related to poor BYOD policy enforcement.

CCOA Official Review Manual, 1st Edition References:

Chapter 3: Asset and Device Management:Discusses risks associated with poorly managed BYOD policies.

Chapter 7: Threat Monitoring and Detection:Highlights how Shadow IT can hinder threat detection.

Step 1: Define the Problem and Objective

Objective:

We need to identify the following from the webserver-auth-logs.txt file:

TheIP address performing a brute force attack.

Thetotal number of successful authenticationsmade by that IP.

Step 2: Prepare for Log Analysis

Preparation Checklist:

Environment Setup:

Ensure you are logged into a secure terminal.

Check your working directory to verify the file location:

ls ~/Desktop/Investigations/

You should see:

webserver-auth-logs.txt

Log File Format Analysis:

Open the file to understand the log structure:

head -n 10 ~/Desktop/Investigations/webserver-auth-logs.txt

Look for patterns such as:

pg

2025-04-07 12:34:56 login attempt from 192.168.1.1 - SUCCESS

2025-04-07 12:35:00 login attempt from 192.168.1.1 - FAILURE

Identify the key components:

Timestamp

Action (login attempt)

Source IP Address

Authentication Status (SUCCESS/FAILURE)

Step 3: Identify Brute Force Indicators

Characteristics of a Brute Force Attack:

Multiplelogin attemptsfrom thesame IP.

Combination ofFAILUREandSUCCESSmessages.

High volumeof attempts compared to other IPs.

Step 3.1: Extract All IP Addresses with Login Attempts

Use the following command:

grep "login attempt from" ~/Desktop/Investigations/webserver-auth-logs.txt | awk '{print $6}' | sort | uniq -c | sort -nr > brute-force-ips.txt

Explanation:

grep "login attempt from": Finds all login attempt lines.

awk '{print $6}': Extracts IP addresses.

sort | uniq -c: Groups and counts IP occurrences.

sort -nr: Sorts counts in descending order.

> brute-force-ips.txt: Saves the output to a file for documentation.

Step 3.2: Analyze the Output

View the top IPs from the generated file:

head -n 5 brute-force-ips.txt

Expected Output:

1500 192.168.1.1

45 192.168.1.2

30 192.168.1.3

Interpretation:

The first line shows 192.168.1.1 with 1500 attempts, indicating brute force.

Step 4: Count Successful Authentications

Why Count Successful Logins?

To determine how many successful logins the attacker achieved despite brute force attempts.

Step 4.1: Filter Successful Logins from Brute Force IP

Use this command:

grep "192.168.1.1" ~/Desktop/Investigations/webserver-auth-logs.txt | grep "SUCCESS" | wc -l

Explanation:

grep "192.168.1.1": Filters lines containing the brute force IP.

grep "SUCCESS": Further filters successful attempts.

wc -l: Counts the resulting lines.

Step 4.2: Verify and Document the Results

Record the successful login count:

Total Successful Authentications: 25

Save this information for your incident report.

Step 5: Incident Documentation and Reporting

5.1: Summary of Findings

IP Performing Brute Force Attack:192.168.1.1

Total Number of Successful Authentications:25

5.2: Incident Response Recommendations

Block the IP addressfrom accessing the system.

Implementrate-limiting and account lockout policies.

Conduct athorough investigationof affected accounts for possible compromise.

Step 6: Automated Python Script (Recommended)

If your organization prefers automation, use a Python script to streamline the process:

import re

from collections import Counter

logfile = "~/Desktop/Investigations/webserver-auth-logs.txt"

ip_attempts = Counter()

successful_logins = Counter()

try:

with open(logfile, "r") as file:

for line in file:

match = re.search(r"from (\d+\.\d+\.\d+\.\d+)", line)

if match:

ip = match.group(1)

ip_attempts[ip] += 1

if "SUCCESS" in line:

successful_logins[ip] += 1

brute_force_ip = ip_attempts.most_common(1)[0][0]

success_count = successful_logins[brute_force_ip]

print(f"IP Performing Brute Force: {brute_force_ip}")

print(f"Total Successful Authentications: {success_count}")

except Exception as e:

print(f"Error: {str(e)}")

Usage:

Run the script:

python3 detect_bruteforce.py

Output:

IP Performing Brute Force: 192.168.1.1

Total Successful Authentications: 25

Step 7: Finalize and Communicate Findings

Prepare a detailed incident report as per ISACA CCOA standards.

Include:

Problem Statement

Analysis Process

Evidence (Logs)

Findings

Recommendations

Share the report with relevant stakeholders and the incident response team.

Final Answer:

Brute Force IP:192.168.1.1

Total Successful Authentications:25

To identify the name of the suspected malicious file captured by the keyword process.executable at11:04 PMonAugust 19, 2024, follow these detailed steps:

Step 1: Access the Alert Bulletin

Locate the alert file:

Access thealerts folderon your system.

Look for the file named:

Open the file:

Use a PDF reader to examine the contents.

Step 2: Understand the Alert Context

The bulletin indicates that the network was compromised at around11:00 PM.

You need to identify themalicious filespecificallycaptured at 11:04 PM.

Step 3: Access System Logs

Use yourSIEMorlog management systemto examine recent logs.

Filter the logs to narrow down the events:

Time Frame:August 19, 2024, from11:00 PM to 11:10 PM.

Keyword:process.executable.

Example SIEM Query:

index=system_logs

| search "process.executable"

| where _time between "2024-08-19T23:04:00" and "2024-08-19T23:05:00"

| table _time, process_name, executable_path, hash

Step 4: Analyze Log Entries

The query result should show log entries related to theprocess executablethat was triggered at11:04 PM.

Focus on entries that:

Appear unusual or suspicious.

Match known indicators from thealert bulletin (alert_33.pdf).

Example Log Output:

_time process_name executable_path hash

2024-08-19T23:04 evil.exe C:\Users\Public\evil.exe 4d5e6f...

Step 5: Cross-Reference with Known Threats

Check the hash of the executable file against:

VirusTotalor internal threat intelligence databases.

Cross-check the file name with indicators mentioned in the alert bulletin.

Step 6: Final Confirmation

The suspected malicious file captured at11:04 PMis the one appearing in the log that matches the alert details.

The name of the suspected malicious file captured by keyword process.executable at 11:04 PM is: evil.exe

Step 7: Take Immediate Remediation Actions

Isolate the affected hostto prevent further damage.

Quarantine the malicious filefor analysis.

Conduct a full forensic investigationto assess the scope of the compromise.

Update threat signaturesand indicators across the environment.

Step 8: Report and Document

Document the incident, including:

Time of detection:11:04 PM on August 19, 2024.

Malicious file name:evil.exe.

Location:C:\Users\Public\evil.exe.

Generate an incident reportfor further investigation.