Monitor incoming SIEM alerts, enrich them with MITRE ATT&CK data from Qdrant, classify and log remediation steps, and update Zendesk tickets with actionable threat context.
This AI agent ingests SIEM alerts, retrieves MITRE ATT&CK context from a Qdrant vector store, and extracts relevant techniques. It then generates remediation steps and enriches Zendesk tickets with threat intel, providing structured data for reporting and downstream automation.
Provides end-to-end enrichment of alerts with techniques and remediation guidance.
Ingests SIEM alerts from connected sources
Queries MITRE ATT&CK data from Qdrant
Extracts relevant TTPs (Tactics, Techniques, and Procedures)
Generates remediation steps tailored to the alert
Updates Zendesk tickets with threat intelligence and actions
Provides structured alert data for reporting and automation
This AI agent reduces manual effort and standardizes alert context, enabling faster containment and consistent ticket enrichment.
A simple 3-step flow that is easy to understand and implement.
Ingest SIEM alerts from connected sources and normalize fields for processing.
Query Qdrant for ATT&CK vectors and map TTPs to the alert.
Update Zendesk tickets with threat intelligence and remediation steps; log structured data for reporting.
One realistic scenario demonstrating end-to-end automation.
Scenario: A high-severity SIEM alert indicates anomalous login activity. The AI agent enriches with MITRE ATT&CK techniques, retrieves threat context from Qdrant, updates the Zendesk ticket with remediation steps, and outputs structured data for dashboards. Time to complete: 3 minutes. Outcome: The ticket contains contextual threat data and remediation guidance, enabling faster containment.
Roles that gain tangible improvements from SIEM alert enrichment.
Need rapid context to triage alerts
Require actionable remediation guidance
Link threat intel into automation playbooks
Require MITRE ATT&CK mappings for investigations
Need measurable improvements in MTTR and ticket quality
Provide standardized enrichment across clients
Core systems the AI agent operates within.
Orchestrates the AI agent flow and coordinates data flow between sources.
Stores MITRE ATT&CK vectors and returns relevant TTPs for each alert.
Receives enriched context and remediation steps, updating tickets in real-time.
Embedded in Qdrant; provides technique mappings for alerts.
Generates tailored remediation steps and contextual explanations.
Practical scenarios where this AI agent adds value.
Common questions about this AI agent.
The AI agent ingests SIEM alerts, enriches them with MITRE ATT&CK data from Qdrant, and updates Zendesk tickets with remediation steps. It uses LLMs to generate context and guidance, orchestrated by n8n for reliability and traceability. It can output structured data for dashboards and automation, enabling faster containment.
It integrates with common SIEMs via n8n connectors, enabling ingestion from sources such as Splunk, Elastic SIEM, Chronicle, and others. Enrichment logic remains consistent regardless of source. Setup focuses on canonical fields and mapping for MITRE ATT&CK. Ongoing maintenance is simplified by centralized configuration.
MITRE ATT&CK data stored in Qdrant is queried to map techniques to alerts. Threat intel and remediation playbooks can be integrated. Zendesk ticket data anchors context, while the AI model crafts actionable guidance. Processing occurs within the AI agent's workflow with complete logging.
OpenAI API is used to generate remediation steps and contextual explanations, but alternative LLMs can be configured. An API key is needed, and endpoint access controls apply. If the model is unavailable, the system can fall back to deterministic rules. Data handling follows enterprise security policies.
Yes. Remediation templates and prompts can be tailored to organizational policies. Custom runbooks can be embedded and enforced by the enrichment output. You can adjust prompts and actions to align with your incident response playbooks. Administrators can override AI-provided steps when necessary.
The workflow enforces restricted access to data sources, encrypted connections, and robust audit logs. Access to Zendesk and SIEM data is controlled and monitored. Data retention and privacy policies are configurable. The system supports RBAC and end-to-end encryption where applicable.
Initial setup depends on existing integrations and data structures, typically a few hours to connect SIEM sources and configure mappings. Fine-tuning may take additional days. Once configured, the AI agent runs automatically per alert with monitoring dashboards available.
Monitor incoming SIEM alerts, enrich them with MITRE ATT&CK data from Qdrant, classify and log remediation steps, and update Zendesk tickets with actionable threat context.
