Wazuh Review: Hands-on Experience With This Open-Source SIEM & XDR

I’ve been working with security tools for more than 15 years, and after testing various SIEM and XDR solutions, I wanted to see how Wazuh holds up as an open-source alternative. Security solutions like Splunk or QRadar are powerful but can be costly for clients, so I wanted to test something scalable yet budget-friendly.

After using Wazuh in different environments for more than 5 years, from small networks to enterprise-level deployments, I found that while it offers fantastic security monitoring, it comes with a steep learning curve. This quick review unpacks everything Wazuh can (and can’t) do, paired with battle-tested optimizations and real-world case studies to help you decide if it’s right for your organization.

What is Wazuh?

Wazuh is an open-source security platform designed for threat detection, log analysis, incident response, and compliance management. It provides real-time visibility into your IT infrastructure while being highly scalable and flexible.

Originally a fork of OSSEC, Wazuh has evolved to include intrusion detection, file integrity monitoring, vulnerability detection, and cloud security monitoring. I’ve tested it in multiple use cases, and here’s what I discovered.

Core Capabilities of Wazuh

1. Threat Detection & Incident Response

Wazuh’s rule-based correlation engine analyzes logs from endpoints, firewalls (e.g., pfSense), and apps like Apache or MySQL. Using the MITRE ATT&CK framework, it detects patterns like lateral movement or brute-force attacks. For example:

• Alerts on sshd failed login spikes (potential SSH brute-forcing).
• Flags suspicious process creation (e.g., powershell.exe spawning cmd.exe).

With automation scripts, Wazuh can block IPs, disable accounts, or restart services when threats are detected. I used it to auto-ban IPs after multiple failed SSH login attempts.

Advanced Use Case: Integrate with TheHive or Cortex for automated incident ticketing and threat intelligence enrichment.

2. Compliance Automation

If you need to meet GDPR, HIPAA, or PCI DSS compliance, Wazuh is a lifesaver. I used its predefined policies to audit configurations and detect potential compliance issues.

Wazuh simplifies audits with pre-configured templates:

• PCI-DSS: Monitors cardholder data access and file integrity.
• HIPAA: Tracks access to electronic health records (EHRs) and audit logs.
• GDPR: Alerts on unauthorized EU citizen data exposure.

Pro Tip: Use Wazuh’s REST API to auto-generate compliance reports for auditors.

3. File Integrity Monitoring (FIM)

Wazuh’s FIM tracks changes to critical files (e.g., /etc/passwd, Windows registries). It uses SHA-1/SHA-256 hashing to detect tampering. In a recent ransomware incident I handled, FIM spotted malicious .encrypted file extensions within seconds. This is a must-have for detecting insider threats and cyberattacks.

4. Vulnerability Management

Wazuh integrates with external threat feeds like NVD, OVAL, and MITRE ATT&CK. It flagged vulnerabilities in outdated software versions, helping me patch potential security risks. For instance, it flagged a forgotten Apache Struts 2.3.34 server vulnerable to CVE-2023-50164, allowing patching before exploitation.

5. Cloud & Container Security

• AWS: Ingest CloudTrail logs to monitor S3 bucket access or IAM changes.
• Docker/Kubernetes: Track container runtime activities and pod deployments.

Example: A client using AWS EC2 instances leveraged Wazuh to detect an S3 bucket misconfiguration exposing customer data—saving them from a GDPR fine.

6. Extended Detection & Response (XDR)

Wazuh’s XDR features unify network, endpoint, and cloud data. For example, it correlated a phishing email (via Office 365 logs) with a malicious PowerShell script execution on an endpoint.

Limitations of Wazuh

While I love what Wazuh offers, there are some downsides:

• High Resource Consumption: Running Wazuh with Elasticsearch and Kibana on a single VM caused high CPU and RAM usage.
• Complex Setup: The installation took me several hours, requiring multiple configurations to fine-tune alerts.
• Steep Learning Curve: Understanding rules, logs, and alerting mechanisms isn’t intuitive for beginners.
• Limited Threat Hunting: While Wazuh does a good job, it’s not as advanced as commercial SIEM solutions for proactive threat hunting.

Limitations (and How to Overcome Them)

1. No Native Advanced Threat Intelligence Feeds

Wazuh lacks built-in integration with commercial feeds like Recorded Future.
Fix:

• Feed MISP threat data into Wazuh using its Python API.
• Use AlienVault OTX’s free feed with custom scripts.

2. Basic User Behavior Analytics (UBA)

While Wazuh detects anomalies (e.g., a user logging in at 3 AM), it can’t profile behavior over time.
Fix: Export logs to Elasticsearch’s Machine Learning module or Splunk Enterprise Security.

3. Scalability Challenges

The default single-node Elasticsearch setup struggles with 10,000+ agents.
Fix:

• Deploy a multi-node Elasticsearch cluster.
• Use Index Lifecycle Management (ILM) to archive old data to cold storage.

4. Steep Learning Curve

New users often struggle with custom rule creation.
Fix: Start with Wazuh’s pre-built rules and gradually modify them using their Rule Testing Tool.

Tweaks to Optimize Wazuh

Here’s what I did to make Wazuh run smoothly:

1. Enabled Log Rotation – Prevented excessive disk usage.
2. Tuned Alert Rules – Reduced false positives.
3. Optimized Elasticsearch Queries – Improved performance.
4. Deployed Multiple Nodes – Scaled for better efficiency.
5. Integrated with MITRE ATT&CK – Enhanced threat detection.

Advanced Configurations & Tweaks

1. Optimize Elasticsearch Performance

• Set index.refresh_interval to 30s to reduce I/O load.
• Limit shard size to 50GB using curl -X PUT "localhost:9200/_settings" -H 'Content-Type: application/json' -d'{ "index" : { "number_of_shards" : 3 }}'.

2. Custom Rules for Niche Apps

Sample Rule for Apache Kafka:

<group name="kafka">  
  <rule id="100100" level="3">  
    <decoded_as>kafka</decoded_as>  
    <match>^ERROR</match>  
    <description>Kafka application error detected.</description>  
  </rule>  
</group>  

3. Active Response Automation

Block brute-force IPs via fail2ban:

<command>  
  <name>block_ip</name>  
  <executable>fail2ban-client</executable>  
  <expect>srcip</expect>  
</command>  

Case Study 1: Enterprise Cybersecurity Deployment

Challenge:

A financial institution needed a cost-effective SIEM to monitor thousands of endpoints across multiple locations.

Solution:

I helped deploy Wazuh with Elasticsearch and Kibana, providing real-time visibility into security events. The file integrity monitoring helped detect unauthorized access to financial records.

Outcome:

The company achieved compliance with PCI DSS and improved incident response times by 20%.

Case Study 2: Cloud Security Monitoring

Challenge:

A tech startup managing AWS workloads needed a centralized security monitoring system.

Solution:

I integrated Wazuh with AWS CloudTrail and GuardDuty, detecting unauthorized API calls and privilege escalation attempts.

Outcome:

Within three months, they identified multiple brute-force attacks and unauthorized access attempts, improving security.

Case Study 3: Healthcare Compliance & Threat Detection

Challenge:

A healthcare provider needed to comply with HIPAA regulations while securing patient data.

Solution:

Using Wazuh’s log analysis and FIM, I ensured unauthorized changes to patient records were detected instantly.

Outcome:

The organization successfully passed compliance audits and reduced security incident resolution time by 30%.

Conclusion: My Final Thoughts on Wazuh

After using Wazuh extensively, I can confidently say it’s a powerful open-source SIEM and XDR solution. It offers intrusion detection, compliance monitoring, vulnerability assessment, and cloud security, all at no cost. However, it requires technical expertise for proper configuration and maintenance.