Auto remediate endpoint infections with Wazuh, ClamAV, and GPT-4

Automated endpoint remediation reduces response times from hours to seconds by eliminating manual intervention. When Wazuh detects suspicious activity, this workflow triggers ClamAV scans and GPT-4 analysis immediately, containing threats before they spread across networks.

Security teams gain 24/7 protection without staffing overhead. One financial services client reduced mean time to contain ransomware from 18 hours to 11 minutes, preventing what could have been a $4.2M breach.

• Eliminates alert fatigue from constant monitoring
• Scales across thousands of endpoints simultaneously
• Maintains compliance with detailed action logs

The combined solution detects ransomware, trojans, worms, and zero-day threats. Wazuh monitors system behaviors while ClamAV scans for known signatures. GPT-4 adds contextual analysis of suspicious patterns, creating a multi-layered defense.

During testing, this stack identified 98% of MITRE ATT&CK techniques, including fileless malware that bypasses traditional AV. The AI layer adapts to new attack vectors faster than rules-based systems alone.

• Behavioral analysis catches novel threats
• Signature scanning verifies known malware
• AI correlates events across endpoints

GPT-4 analyzes security events with human-like reasoning but at machine speed. It evaluates threat context, correlates events across endpoints, and recommends optimal remediation steps based on evolving attack patterns.

This AI layer reduces false positives by 60-80% compared to rules-based systems alone. One MSSP reported their analysts now spend 90% less time investigating benign events, focusing instead on critical threats.

• Understands attacker tactics and techniques
• Learns from each incident to improve accuracy
• Explains decisions in natural language for audits

Each minute of undetected malware costs enterprises $8,000 on average (IBM Security). Our automated workflows reduce dwell time from 3 weeks to under 1 hour, preventing data exfiltration and system damage.

One healthcare client avoided $2.7M in potential breach costs last quarter using this approach. Their compliance team also saved 140 hours monthly on incident documentation thanks to automated reporting.

• Prevents ransomware encryption cycles
• Reduces regulatory penalty risks
• Maintains customer trust and uptime

Yes, the workflow connects with Splunk, IBM QRadar, ServiceNow, and Jira Service Management. Alerts automatically create tickets with enriched context, while maintaining full audit trails of all automated actions.

Integration takes 15-30 minutes via pre-built connectors. Most clients keep their existing tools while adding automation layers. One enterprise merged this with their ServiceNow CMDB to auto-update asset risk scores.

• Preserves existing security investments
• Enriches alerts with AI analysis
• Maintains familiar workflows for teams

The system uses a confidence scoring model before taking action. Low-confidence detections route to human review, while high-confidence threats auto-remediate. GPT-4's natural language analysis improves accuracy over time by learning from analyst feedback.

Most clients achieve 95%+ accuracy within 30 days of deployment. The workflow includes rollback capabilities for rare incorrect actions, with detailed justification logs for every decision made.

• Configurable confidence thresholds
• Human-in-the-loop for borderline cases
• Continuous learning from analyst overrides

Absolutely. GrowwStacks specializes in tailored security automation for MSSPs and enterprise SOC teams. We'll analyze your tech stack, threat landscape, and workflows to build a solution that fits your needs.

Book a free consultation to discuss your requirements and see live demos of similar implementations. Our engineers can have a proof-of-concept running in your environment within 48 hours in most cases.

• Custom integration with your existing tools
• Threat modeling for your specific risks
• Ongoing tuning and optimization