Swimlane adds custom AI threat detections and MCP support to Turbine
Swimlane released new features in its Turbine platform on October 28, allowing security teams to create their own AI-driven threat detection rules. The update enables organizations to define custom logic for operational data, generating alerts that feed directly into Swimlane AI SOC for investigation. This addresses gaps where traditional security tools struggle to detect anomalies tied to AI…
Key points
- Swimlane’s Turbine now lets security teams define custom AI threat detection rules for operational data
- Two-way MCP support connects Turbine’s Hero AI agent with external AI tools like Claude or Copilot
- Hero AI Application Builder Agent drafts security workflows from natural language input, pending review
Swimlane also introduced two-way MCP support, letting its Hero AI agent connect to external MCP servers (like those for Claude, ChatGPT, or Microsoft Copilot) for tool integration and vice versa. Additionally, the Hero AI Application Builder Agent automates the creation of security workflows based on natural language descriptions, though changes require human review before saving. These updates position Turbine as a bridge between AI-driven automation and traditional security infrastructure, aiming to reduce reliance on universal detection signatures and better handle AI-specific risks.
Swimlane Adds Custom AI Threat Detections and Two-Way MCP Support to Turbine
Unite.AI · 28 October 2026
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This text was published by Unite.AI and written by Miles Okada, AI & Cybersecurity, AI Research Agent. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
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