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SIEMcompleted

Incident Response Automation Platform_

Designed and deployed SOAR/SIEM playbooks using Wazuh, TheHive, and Shuffle to automate incident triage and containment workflows, reducing escalations by 25%.

WazuhTheHiveShufflen8nSOARCTI IntegrationCorrelation RulesPython
incident-response-automation.mdreading

Overview

Developed a comprehensive SOAR/SIEM integration platform at Apphaz that automates incident triage, containment, and response workflows, significantly reducing manual effort and improving response times.

Key Achievements

  • Designed and deployed SOAR/SIEM playbooks using Wazuh, TheHive, and Shuffle to automate incident triage and containment workflows, reducing escalations by 25% in 3 months
  • Integrated CTI feeds with automated response workflows and tuned correlation rules to enhance Red/Purple Team detection capability by 30%

Architecture

┌─────────────┐      ┌─────────────┐     ┌─────────────┐
│   Wazuh     │────> │     N8N     │────>│  TheHive    │
│   (SIEM)    │      │    (SOAR)   │     │  (Case Mgmt)│
└─────────────┘      └─────────────┘     └─────────────┘
       │                                        │
       ▼                                        ▼
┌─────────────┐                          ┌─────────────┐    
│ Log Sources │                          │   Analysts  │
└─────────────┘                          └─────────────┘

Playbooks Developed

1. Malware Detection Response

Automated workflow triggered when Wazuh detects potential malware:

  1. Extract IOCs from alert
  2. Enrich with VirusTotal, AbuseIPDB
  3. Create TheHive case
  4. Isolate endpoint if high severity
  5. Notify SOC team

2. Brute Force Detection

trigger: wazuh_alert
condition: rule.id == "5710" AND data.srcip != "internal"
actions:
  - enrich_ip:
      service: abuseipdb
      ip: "{{data.srcip}}"
  - block_ip:
      firewall: pfsense
      duration: 24h
  - create_case:
      platform: thehive
      severity: medium

3. Phishing Email Analysis

Automated analysis of reported phishing emails including:

  • URL extraction and reputation check
  • Attachment sandboxing
  • Sender verification
  • Auto-response to reporter

Results

Metric Before After
MTTR (Mean Time to Respond) 45 min 12 min
Escalations per week 40 30
Detection accuracy 70% 91%
Analyst workload High Moderate

Technologies Used

  • Wazuh: SIEM and log analysis
  • n8n: SOAR workflow automation
  • TheHive: Case management
  • Shuffle: SOAR orchestration
  • MISP: Threat intelligence sharing
  • Python: Custom integrations