This n8n workflow automates cybersecurity incident response by integrating SIEM alerts, AI analysis, and threat intelligence. When a chat message—triggered by a cybersecurity alert—is received, the workflow leverages Langchain’s AI nodes to analyze the alert, extract attack techniques using the MITRE ATT&CK framework, and provide actionable remediation steps. It pulls detailed threat intelligence data from Google Drive, embeds this information, and populates a vector store in Qdrant for efficient retrieval. The workflow queries the vector store using AI to find relevant attack techniques based on alert descriptions, and then updates Zendesk tickets with this contextual MITRE data. Additionally, it supports manual testing and discusses embedding data for threat intelligence management, offering a comprehensive solution for proactive incident response.
Automated Cybersecurity Incident Response Workflow
Node Count | >20 Nodes |
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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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