Automated Cyber Threat Analysis Using AI and MITRE Framework

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This workflow automates cybersecurity incident response by integrating SIEM alerts, AI analysis, and the MITRE ATT&CK framework to provide structured threat insights and remediation steps. It triggers upon receiving chat messages related to security alerts and employs AI agents to analyze data, extract attack tactics, and offer actionable recommendations. The process involves retrieving MITRE data from Google Drive, embedding and storing threat information in a Qdrant vector database, and querying this database to contextualize alerts. The insights are then logged into Zendesk tickets, enriching incident reports with MITRE-aligned attack details for faster response and remediation. This workflow is ideal for security teams seeking to streamline threat analysis and incident management through automation and AI-driven insights.

Node Count

>20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.documentDefaultDataLoader, @n8n/n8n-nodes-langchain.embeddingsOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.textSplitterTokenSplitter, @n8n/n8n-nodes-langchain.vectorStoreQdrant, extractFromFile, googleDrive, manualTrigger, noOp, splitInBatches, splitOut, stickyNote, zendesk

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