• Hive names

• The type of configuration settings that each hive stores

• The location of each hive on the disk

Note: The configuration settings stored in each hive listed above are just a few examples. Each hive stores more than these.

These Registry Hives contain binary data that cannot be opened directly from the file. Use the Windows OS built-in tool Registry Editor to view all the registry data available in these hives.

Windows organizes all the Registry Hives into these structured Root Keys. Instead of seeing the Registry Hives, you would always get these registry root keys whenever you open the registry.

In the table above, you can see that most of the Registry Hives are located under the HKEY_LOCAL_MACHINE (HKLM) key.

Registry Forensics

• Registry keys contain key forensic evidence.

• Avoid live analysis as it can modify data/evidence. → Collect registry hives for offline examination.

• Registry Editor cannot open offline hives. Many values appear as unreadable binary in Registry Editor. → Use specialized forensic tools for analysis.

In this task, you will use the Registry Explorer tool. It is open source and can parse the binary data out of the registry, and we can analyze it without the fear of modification.

While loading Registry Hives, it is important to know that these Registry Hives can sometimes be “dirty” when collected from live systems, meaning they may have incomplete transactions.

⭐ To ensure you get a clean, consistent hive state for analysis: Hold SHIFT, then press Open to load associated transaction log files.

Task Questions

Q1. What application was installed on the dispatch-srv01 before the abnormal activity started?

Q2. What is the full path where the user launched the application (found in question 1) from?

Hive: NTUSER.DAT. Key: This key stores information on recently accessed applications launched via the GUI. Refresh your memory with the Registry Keys table in the task.

Navigate to either:

or

ROOT\Software\Microsoft\Windows NT\CurrentVersion\AppCompatFlags\Compatibility Assistant\Store

Q3. Which value was added by the application to maintain persistence on startup?

The TBFC drone scheduler web UI is facing a critical security incident. Attackers are sending long HTTP requests containing heavily obfuscated shell code within Base64 chunks to vulnerable endpoints.

• Initial Detection: Splunk alerted on “Apache spawned an unusual process,” indicating successful command execution.

• Triage Strategy: Perform Blue Team triage by pivoting between two critical Splunk data sources:

  1. Apache Web Logs: To identify the source IP, find the specific malicious HTTP request, and extract the raw Base64 payload.

  2. Sysmon Host Telemetry: To confirm execution by tracing the malicious processes (e.g., httpd.exe spawning powershell.exe) and extracting the Base64 payload from the command line arguments.

• Goal: Extract and decode the shell code, identify compromised hosts, and determine the scope of the breach.

Detect Suspicious Web Commands

index=windows_apache_access (cmd.exe OR powershell OR “powershell.exe” OR “Invoke-Expression”) | table _time host clientip uri_path uri_query status

The query searches the web access logs for any HTTP requests that include signs of command execution attempts, such as cmd.exe, PowerShell, or Invoke-Expression. This query helps identify possible Command Injection attacks, where the evil attacker tries to execute system commands through a vulnerable CGI script (hello.bat).

Looking for Server-Side Errors or Command Execution in Apache Error Logs

index=windows_apache_error (”cmd.exe” OR “powershell” OR “Internal Server Error”)

This query inspects the Apache error logs for signs of execution attempts or internal failures caused by malicious requests. As you can tell, we are searching for error messages with particular terms such as cmd.exe and powershell.

Switch to Raw format for better visibility.

If a request like /cgi-bin/hello.bat?cmd=powershell triggers a 500 “Internal Server Error,” it often means the attacker’s input was processed by the server but failed during execution, a key sign of exploitation attempts.

Checking these results helps confirm whether the attack reached the backend or remained blocked at the web layer.

Trace Suspicious Process Creation From Apache

Let’s explore Sysmon for other malicious executable files that the web server might have spawned.

index=windows_sysmon ParentImage=”*httpd.exe”

This query focuses on process relationships from Sysmon logs, specifically when the parent process is Apache (httpd.exe).

Typically, Apache should only spawn worker threads, not system processes like cmd.exe or powershell.exe.

If results show child processes such as:

• ParentImage = C:\Apache24\bin\httpd.exe

• Image = C:\Windows\System32\cmd.exe

It indicates a successful command injection where Apache executed a system command.

The finding above is one of the strongest indicators that the web attack penetrated the operating system.

Confirm Attacker Enumeration Activity

In this step, we aim to discover what specific programs we found from previous queries do. Let’s use the following query.

index=windows_sysmon *cmd.exe* *whoami*

This query looks for command execution logs where cmd.exe ran the command whoami.

Attackers often use the whoami command immediately after gaining code execution to determine which user account their malicious process is running as.

Finding these events confirms the attacker’s post-exploitation reconnaissance, showing that the injected command was executed on the host.

Identify Base64-Encoded PowerShell Payloads

In this final step, we will work to find all successfully encoded commands. To search for encoded strings, we can use the following Splunk query:

index=windows_sysmon Image=”*powershell.exe” (CommandLine=”*enc*” OR CommandLine=”*-EncodedCommand*” OR CommandLine=”*Base64*”)

This query detects PowerShell commands containing -EncodedCommand or Base64 text, a common technique attackers use to hide their real commands.

If your defences are correctly configured, this query should return no results, meaning the encoded payload (such as the “Muahahaha” message) never ran.

If results appear, you can decode the Base64 command to inspect the attacker’s true intent.

Task Questions

What is the reconnaissance executable file name?

whoami.exe

What executable did the attacker attempt to run through the command injection?

PowerShell.exe

In what situations might defenders rely on this tool?

• Post-incident analysis: when the security team needs to verify whether traces of malware found on one compromised host still exist elsewhere in the environment.

• Threat Hunting: searching through systems and endpoints for signs of known or related malware families.

• Intelligence-based scans: applying shared YARA rules from other defenders or kingdoms to detect new indicators of compromise.

• Memory analysis: examining active processes in a memory dump for malicious code fragments.

YARA rule key elements

• Metadata: information about the rule itself: who created it, when, and for what purpose.

• Strings: the clues YARA searches for: text, byte sequences, or regular expressions that mark suspicious content.

• Conditions: the logic that decides when the rule triggers, combining multiple strings or parameters into a single decision.

Examples:

rule ExampleMalware
{
    meta:
        author = “Defender”
        description = “Detects example malware”
    strings:
        $s1 = “malicious_function”
        $s2 = { 6A 40 68 00 30 00 00 }
    condition:
        $s1 or $s2
}

rule TBFC_KingMalhare_Trace
{
    meta:
        author = “Defender of SOC-mas”
        description = “Detects traces of King Malhare’s malware”
        date = “2025-10-10”
    strings:
        $s1 = “rundll32.exe” fullword ascii
        $s2 = “msvcrt.dll” fullword wide
        $url1 = /http:\/\/.*malhare.*/ nocase
    condition:
        any of them
}

Strings

Text strings

• Case-insensitive strings - nocase
  By default, YARA matches text exactly as written. Adding the nocase modifier makes the match ignore letter casing, so “Christmas”, “CHRISTMAS”, or “christmas” will all trigger the same result.

strings:
    $xmas = “Christmas” nocase

• Wide-character strings - wide, ascii
  Many Windows executables use two-byte Unicode characters. Adding wide tells YARA to also look for this format, while ascii enforces a single-byte search. You can use both together:

strings:
    $xmas = “Christmas” wide ascii

• XOR strings - xor
  Malhare’s agents often XOR-encode text to hide it from scanners. Using the xor modifier, YARA automatically checks all possible single-byte XOR variations of a string - revealing what attackers tried to conceal.

strings:
    $hidden = “Malhare” xor

• Base64 strings - base64, base64wide
  Some malware encodes payloads or commands in Base64. With these modifiers, YARA decodes the content and searches for the original pattern, even when it’s hidden in encoded form.

strings:
    $b64 = “SOC-mas” base64

Hexadecimal strings

Sometimes, King Malhare’s code doesn’t leave readable words behind; instead, it hides in raw bytes deep inside executables or memory. Hex strings allow YARA to search for specific byte patterns, written in hexadecimal notation.

This is useful when defenders need to detect malware fragments like file headers, shellcode, or binary signatures that can’t be represented as plain text.

rule TBFC_Malhare_HexDetect
{
    strings:
        $mz = { 4D 5A 90 00 }   // MZ header of a Windows executable
        $hex_string = { E3 41 ?? C8 G? VB }

    condition:
        $mz and $hex_string
}

Regular expression strings

It’s especially useful for spotting URLs, encoded commands, or filenames that share a structure but differ slightly each time.

rule TBFC_Malhare_RegexDetect
{
    strings:
        $url = /http:\/\/.*malhare.*/ nocase
        $cmd = /powershell.*-enc\s+[A-Za-z0-9+/=]+/ nocase

    condition:
        $url and $cmd
}

Regex strings are powerful but should be used carefully; they can match a wide range of data and may slow down scans if written too broadly.

Conditions

Match a single string

The simplest condition, the rule triggers if one specific string is found. For example, the variable xmas.

condition:
    $xmas

Match any string

When multiple strings are defined, the rule can be configured to trigger as soon as any one of them is found:

condition:
    any of them

This approach is useful for detecting early signs of compromise; even a single matching clue can be enough to raise attention.

Match all strings

To make the rule stricter, you can require that all defined strings appear together:

condition:
    all of them

This approach reduces false positives; YARA will only flag a file if every indicator matches.

Combine logic using: and, or, not

Defenders often need more control over how rules behave. Logical operators let you combine multiple checks into one condition, just like building a small defensive strategy.

condition:
    ($s1 or $s2) and not $benign

This means the rule will trigger if either $s1 or $s2 is found, but not $benign. In other words: detect suspicious code, but ignore harmless system files.

Use comparisons like: filesize, entrypoint, or hash

YARA can also check file properties, not just contents. For example, you can detect files that are unusually small or large, a common trick used by King Malhare to disguise his payloads.

condition:
    any of them and (filesize < 700KB)

Here, the rule will trigger only when one of the strings matches and the file size is smaller than 700KB.

Example Use Case

rule TBFC_Simple_MZ_Detect
{
    meta:
        author = “TBFC SOC L2”
        description = “IcedID Rule”
        date = “2025-10-10”
        confidence = “low”

    strings:
        $mz   = { 4D 5A }                        // “MZ” header (PE file)
        $hex1 = { 48 8B ?? ?? 48 89 }            // malicious binary fragment
        $s1   = “malhare” nocase                 // story / IOC string

    condition:
        all of them and filesize < 10485760     // < 10MB size
}

Saved as icedid_starter.yar

yara -r icedid_starter.yar C:\icedid_starter C:\Users\WarevilleElf\AppData\Roaming\TBFC_Presents\malhare_gift_loader.exe

We can use the man yara command to find out what flags could be useful in our scenario, and we find the following:

• -r - Allows YARA to scan directories recursively and follow symlinks

• -s - Prints the strings found within files that match the rule

Putting everything together, this YARA command recursively scans the C:\ drive using the icedid_starter.yar rule file and can optionally display the matching strings when using -s.

Practice Task

It’s time to complete the practical task! The blue team has to search for the keyword TBFC: followed by an ASCII alphanumeric keyword across the /home/ubuntu/Downloads/easter directory to extract the message sent by McSkidy. Can you help decode the message sent by McSkidy?

What regex would you use to match a string that begins with TBFC: followed by one or more alphanumeric ASCII characters?

/TBFC:[A-Za-z0-9]+/

How many images contain the string TBFC?

5

What is the message sent by McSkidy?

Find me in HopSec Island

Normal Link

https://trygiftme.thm/search?term=gift

Malicious Link

https://trygiftme.thm/search?term=<script>alert( atob(”VEhNe0V2aWxfQnVubnl9”) )</script>

Stored XSS

Normal Comment Submission

POST /post/comment HTTP/1.1
Host: tgm.review-your-gifts.thm

postId=3
name=Tony Baritone
email=tony@normal-person-i-swear.net
comment=This gift set my carpet on fire but my kid loved it!

Malicious Comment Submission (Stored XSS Example)

POST /post/comment HTTP/1.1
Host: tgm.review-your-gifts.thm

postId=3
name=Tony Baritone
email=tony@normal-person-i-swear.net
comment=<script>alert(atob(”VEhNe0V2aWxfU3RvcmVkX0VnZ30=”))</script> + “This gift set my carpet on fire but my kid loved it!”

Exploiting Reflected XSS

Exploiting Stored XSS

Refresh the page.

1. Confirm the File Type.

If it’s a PDF, proceed with PDF tools. If it’s a ZIP, proceed with ZIP tools.

2. Choose Tools to Use (pick one based on file type)

• PDF: pdfcrack, john (via pdf2john)

• ZIP: fcrackzip, john (via zip2john)

• General: john (very flexible) and hashcat (GPU acceleration, more advanced)

3. Try a dictionary attack

pdfcrack

john

Create a hash that John can understand

John will report the recovered password if it finds one.

How to detect attack like this?

Offline cracking does not hit login services, so lockouts and failed logon dashboards stay quiet. We can detect the work where it runs, on endpoints and jump boxes. The important signals to monitor include:

Process creation

Password cracking has a small set of well-known binaries and command patterns that we can look out for. A mix of process events, file activity, GPU signals, and network touches tied to tooling and wordlists. Our goal is to make the activity obvious without drowning in noise.

• Binaries and aliases: john, hashcat, fcrackzip, pdfcrack, zip2john, pdf2john.pl, 7z, qpdf, unzip, 7za, perl invoking pdf2john.pl.

• Command‑line traits: --wordlist, -w, --rules, --mask, -a 3, -m in Hashcat, references to rockyou.txt, SecLists, zip2john, pdf2john.

• Potfiles and state: ~/.john/john.pot, .hashcat/hashcat.potfile, john.rec.

It’s worth noting that on Windows systems, Sysmon Event ID 1 captures process creation with full command line properties, while on Linux, auditd, execve, or EDR sensors capture binaries and arguments.

GPU and Resource Artefacts

GPU cracking is loud. Sudden high utilisation on hosts can be picked up and would need to be investigated.

• nvidia-smi shows long‑running processes named hashcat or john.

• High, steady GPU utilisation and power draw while the fan curve spikes.

• Libraries loaded: nvcuda.dll, OpenCL.dll, libcuda.so, amdocl64.dll.

Network Hints, Light but Useful

Offline cracking does not need the network once wordlists are present. Yet most operators fetch lists and tools first.

• Downloads of large text files named rockyou.txt, or Git clones of popular wordlist repos.

• Package installs, for example apt install john hashcat, detected by EDR package telemetry.

• Tool updates and driver fetches for GPU runtimes.

Unusual File Reads

Repeated reads of files such as wordlists or encrypted files would need analysis.

Detections

Below are some examples of detection rules and hunting queries we can put to use across various environments.

Sysmon:

(ProcessName=”C:\Program Files\john\john.exe” OR
 ProcessName=”C:\Tools\hashcat\hashcat.exe” OR
 CommandLine=”*pdf2john.pl*” OR
 CommandLine=”*zip2john*”)

Linux audit rules, temporary for an investigation:

auditctl -w /usr/share/wordlists/rockyou.txt -p r -k wordlists_read
auditctl -a always,exit -F arch=b64 -S execve -F exe=/usr/bin/john -k crack_exec
auditctl -a always,exit -F arch=b64 -S execve -F exe=/usr/bin/hashcat -k crack_exec

Sigma style rule, Windows process create for cracking tools:

title: Password Cracking Tools Execution
id: 9f2f4d3e-4c16-4b0a-bb3a-7b1c6c001234
status: experimental
logsource:
  product: windows
  category: process_creation
detection:
  selection_name:
    Image|endswith:
      - ‘\john.exe’
      - ‘\hashcat.exe’
      - ‘\fcrackzip.exe’
      - ‘\pdfcrack.exe’
      - ‘\7z.exe’
      - ‘\qpdf.exe’
  selection_cmd:
    CommandLine|contains:
      - ‘--wordlist’
      - ‘rockyou.txt’
      - ‘zip2john’
      - ‘pdf2john’
      - ‘--mask’
      - ‘ -a 3’
  condition: selection_name or selection_cmd
level: medium

Response Playbook

As security analysts in Wareville, it is important to have a playbook to follow when such incidents occur. The immediate actions to take are:

1. Isolate the host if malicious activity is detected. If it is a lab, tag and suppress.

2. Capture triage artefacts such as process list, process memory dump, nvidia-smi sample output, open files, and the encrypted file.

3. Preserve the working directory, wordlists, hash files, and shell history.

4. Review which files were decrypted. Search for follow‑on access, lateral movement or exfiltration.

5. Identify the origin and intent of the activity. Was this authorised? If not, escalate to the IR team.

6. Remediate the activity, rotate affected keys and passwords, and enforce MFA for accounts.

7. Close with education and correct placement of tools into approved sandboxes.

For this task, you’ll need to check every place to hide, every opened port that bunnies left unprotected. Good luck!

Scan the 1000 most commonly used ports

Scanning the ports to find a way into the server.

Connect to the http via FireFox.

HopSec asks for 3 keys to unlock.

Scanning the whole range

Use -p- to scan all 65535 ports and banner to find what’s likely behind the port.

Found an FTP server and a TBFC application.

Try accessing the FTP server in anonymous mode

Use the ftp command and see if we can find our way in!

Found the key 1.

Try accessing the TBFC application

Since the TBFC application is not a well-known service like HTTP or FTP, your web browser or FTP client won’t know how to access it. Luckily, you can always use Netcat (nc), a universal tool to interact with network services.

Got the 2nd key.

Scan UDP ports

Till now, we have scanned only TCP ports, but there are also 65535 ports for UDP.

Ask this exact DNS server for the specific TXT record for the flag.

Retrieved the 3rd key.

Combine the keys and gain access to the server.

End of quest.

Bonus

Once you have access to the console, there is no need to scan the ports, as you can simply ask the OS to list its open ports, also called listening ports. You can do it by running ss -tunlp (or netstat on older systems) inside the Secret Admin Console of the web app.

With root permissions, you can also view the process column. However, for now, let’s focus on the 3306 port, which is the default MySQL database port. Usually, databases require a password for remote clients, but allow unauthenticated logins from localhost. Since you are already inside the host, let’s see the database content by using the mysql program:

Interactive: Static Analysis

We use static analysis to gather information about a sample without executing it and digging deep. Static analysis can be a quick and effective way to understand how the sample may operate, as well as how it can be identified.

Static analysis: What is the SHA256Sum of the HopHelper.exe?

Static analysis: Within the strings of HopHelper.exe, a flag with the format THM{XXXXX} exists. What is that flag value?

Interactive: Dynamic Analysis

This section of the room provides a brief introduction to dynamic analysis. As you recall, dynamic analysis involves executing the malicious sample to identify its behaviours and how it interacts with the operating system.

Regshot

Regshot is a widely used utility, especially when analyzing malware on Windows. It works by creating two “snapshots” of the registry—one before the malware is run and another afterwards. The results are then compared to identify any changes.

Malware aims to establish persistence, meaning it seeks to run as soon as the device is switched on. A common technique for malware is to add a Run key into the registry, which is frequently used to specify which applications are automatically executed when the device is powered on.

1st shot > Shot

Run the malware

2nd shot > Shot

Compare

Dynamic analysis: What registry value has the HopHelper.exe modified for persistence?

ProcMon

Next, we will explore using ProcMon (Process Monitor) from the Sysinternals suite to investigate today’s sample. Process Monitor is used to monitor and investigate how processes are interacting with the Windows operating system. It is a powerful tool that allows us to see exactly what a process is doing. For example, reading and writing registry keys, searching for files, or creating network connections.

Open ProcMon

Run the malware

Stop capturing

Filter events by Process Name.

Result

Now it is much easier to investigate how the process is interacting with the operating system. Here are some Operations that may be of interest to us:

• RegOpenKey

• CreateFile

• TCP Connect

• TCP Recieve

Further filter events by Operation.

Result

Dynamic analysis: Filter the output of ProcMon for “TCP” operations. What network protocol is HopHelper.exe using to communicate?

Bonus: Can you find the web panel that HopHelper.exe is communicating with?

Paste the link to Chrome.

Use Malware Sandbox for analysis. Identify the hash value of the malware.

Grab the hash value and add it to the Hash Blocklist for EDR detection signature.

Received the flag.

sample2.exe - Firewall rules

Submit the exe for analysis.

The Trojan software makes network requests. Identify where the destination IP is.

Add the IP address to the Firewall Deny rule to block all outgoing traffic to this IP address.

Received the flag.

sample3.exe - DNS rules

With many IP addresses, they still link to the same domain name. Identify the domain name to which the Trojan points.

Add the domain to the DNS Deny rule to block connection attempts to this Trojan malware.

Received the flag.

sample4.exe - Registry key modification attempts

Use the analysis tool to find out the modification events made by the malware to the registry records.

Add the event details to the Sigma Rule Builder to block the same change attempts in the future.

Received the flag.

sample5.exe - Network connection attemps

There are multiple suspicious requests from the sample5.exe.

Since the network artifact can change, the goal here is to identify the unique behaviour of the malware.

The outgoing requests were sent every 30 minutes, which is 30 minutes* 60 seconds = 1,800 seconds. They all have the same byte size of 97 (not shown in the screenshot, but they were next to the Port number). Adding them to the Sigma Rule Builder for future detection.

Received the flag.

sample6.exe - Process creation attempts

Each command appends data from different sources to exfiltr8.log. Looks like the attacker was trying to exfiltrate data from the system.

The file analysis tool shows that the process cmd.exe associated with the file exfiltr8.log is suspicious. Therefore, I’ll create a rule to block commands including this file name.

And done.

Received the flag.

Reflection

Through this exercise, I gained insights into the attacker’s step-by-step mindset and understood how to respond using various defensive measures.

Following the steps in the Phishing Email Analysis playbook

The sender domain is clean.

Check the email details on Microsoft Sentinel. The URL in the content is also clean. The email wasn’t sent to other people in the last 24 hours.

Classified as False Positive.

Case ID 8815

Alert rule: Inbound Email Containing Suspicious External Link

Investigation

Case report

Time of activity: 11/14/25 9:58:36.298 PM

List of Affected Entities: 
- User: c.allen@thetrydaily.thm 
- Source IP: 10.20.2.25:32653 
- Application: web-browsing

Reason for Classifying as True Positive: 
- The link provided (https://m1crosoftsupport.co/login) is a typosquatted domain and links to a malicious host at 45.148.10.131.

Reason for Escalating the Alert: 
- The user has clicked on the malicious link, and the firewall failed to block the request, indicating potential exposure. 
- The user accessed the malicious site and may have entered credentials. Additional investigation is needed.

Recommended Remediation Actions: 
- Initiate a password reset. 
- Ask the user whether they had entered credentials or downloaded from the malicious site. Continue monitoring the workstation.

List of Attack Indicators: 
- Malicious link: https://m1crosoftsupport.co/login 
- Malicious destination domain: 45.148.10.131

Report analysis

55/100 points | TTR 12.82 minutes

Your report provides a clear and concise analysis of the incident involving a phishing attempt. You successfully identified the affected user and the internal and destination IP addresses, which is crucial for understanding the scope of the incident. Your explanation of the user’s interaction with the malicious link and the firewall’s failure to block the request is well-articulated, highlighting the need for escalation. The recommended remediation actions are appropriate and demonstrate a proactive approach to mitigating potential risks. 

However, there are areas for improvement. The report lacks details on the initial phishing attempt, such as the impersonation of Microsoft, which would provide a more comprehensive understanding of the threat. Additionally, while you noted the potential exposure, it would be beneficial to clarify whether any impact was observed, such as credential compromise or malware delivery. In terms of the 5Ws, you covered the ‘Who’ and ‘What’ effectively by identifying the user and the nature of the threat. The ‘When’ is partially addressed with the activity time, but the date format could be clearer. The ‘Where’ is well-covered with the IP addresses and domain information. The ‘Why’ is partially addressed through the explanation of the firewall’s failure and the need for escalation, but more detail on the phishing attempt itself would enhance this aspect. 

Overall, a solid report with room for additional detail in certain areas.

Case ID 8816

Alert rule: Access to Blacklisted External URL Blocked by Firewall

Investigation

Query in Splunk to find logs related to the URL in the email content.

Case report

Time of activity: 11/14/25 9:57:32.298 PM

List of Affected Entities: 
SourceIP: 10.20.2.17:34257 
Web browsing through port 80 (HTTP) 
User: h.harris@thetrydaily.thm

Reason for Classifying as True Positive: 
The target IP was flagged as malicious by threat intelligence.

Reason for Escalating the Alert: 
Not escalated. The outbound request was successfully blocked by the existing rule set.

Recommended Remediation Actions: 
Warn the user and remind them to avoid clicking unknown links.

List of Attack Indicators: 
The destination IP address (67.199.248.11) and the shortened URL (http://bit.ly/3sHkX3da12340) are malicious.

Report analysis

65/100 points | TTR 19.65 minutes

Your report provides a clear identification of the time of activity, the affected user, and the relevant IP addresses involved in the incident. You correctly identified the activity as an attempt to access a malicious URL and noted that the firewall successfully blocked the outbound connection, which is crucial information. 

However, it would be beneficial to explain why the URL was flagged as malicious, such as its inclusion in a blacklist or threat intelligence feed. Additionally, while you correctly concluded that the alert should not be escalated, it’s important to clarify that no further remediation actions are necessary beyond warning the user. 

Overall, your report covers the essential details but could benefit from more context regarding the threat intelligence and the impact assessment. In terms of the 5Ws, you have effectively covered the who, what, when, and where, but the why could be expanded upon to provide a more comprehensive understanding of the incident.