Automate Cyber Incident Analysis with AI & MITRE ATT&CK
Accelerate cybersecurity incident analysis by automatically enriching SIEM alerts with MITRE ATT&CK TTPs and remediation steps, cutting response times by up to 70%.
Manually analyzing SIEM alerts and correlating with MITRE ATT&CK is time-consuming and prone to human error, slowing incident response. This workflow automates cybersecurity incident analysis using AI and a MITRE ATT&CK vector store, providing instant TTP extraction, tailored remediation, and historical context.
Documentation
Automated Cybersecurity Incident Analysis with AI
This powerful n8n workflow revolutionizes how security operations centers (SOC) and security analysts handle cybersecurity incidents. By combining the intelligence of AI with the comprehensive MITRE ATT&CK framework, it automates the tedious tasks of threat intelligence gathering, correlation, and remediation planning, enabling faster and more effective incident response.
Key Features
- AI-powered MITRE ATT&CK TTP extraction from SIEM data or ticket descriptions.
- Automated generation of specific, actionable remediation steps tailored to each alert.
- Contextual cross-referencing with historical patterns and related alerts for deeper insights.
- Interactive chat interface for querying security data and threat intelligence.
- Seamless integration to enrich Zendesk security tickets with vital MITRE ATT&CK context.
How It Works
This workflow is structured into three primary operational segments, ensuring comprehensive cybersecurity analysis and integration:
- MITRE ATT&CK Knowledge Base Creation: Triggered manually, this section pulls a 'cleaned_mitre_attack_data.json' file from Google Drive. The data is then extracted, intelligently split into manageable chunks, embedded using OpenAI's advanced embedding models, and finally ingested into a Qdrant vector store. This process creates a robust and searchable knowledge base of MITRE ATT&CK TTPs.
- Real-time Cybersecurity Chat Assistant: An interactive chat interface allows security analysts to submit queries or SIEM data snippets. An AI Agent, powered by OpenAI's GPT-4o and conversational memory, leverages the Qdrant MITRE ATT&CK vector store to provide expert insights. It extracts TTPs, suggests tailored remediation steps, and offers external resources in real-time.
- Automated Zendesk Ticket Enrichment: This segment automatically fetches new and existing Zendesk tickets. For each ticket, an AI Agent analyzes the alert details (subject and description). It then queries the Qdrant vector store to identify relevant MITRE ATT&CK TTPs. A Structured Output Parser formats the AI's response into a standardized JSON, which is then used to update the Zendesk ticket with a summary, MITRE tactic, and technique ID via custom fields, significantly enhancing ticket context and accelerating resolution.