Creating a Security Agent with Cohere North and Wiz - Cohere

· Source: cohere.com via Google News · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cybersecurity & Data Privacy, Cloud Computing & IT Infrastructure · Depth: Intermediate, medium

Summary

Cohere has developed a security agent using its enterprise AI agent platform, North, integrated with the cloud security platform Wiz via a custom Model Context Protocol (MCP) server. This solution automates incident response workflows, addressing the challenge of translating Wiz's high-fidelity security findings into actionable steps, a process that previously took 30 minutes to 2 hours per finding. The architecture connects North to Wiz's GraphQL API through a lightweight Python MCP server, exposing eight atomic tools for tasks like listing issues, querying assets, and updating issue statuses. Key use cases include a 20-second "toxic combination" blast radius analysis, assisted end-to-end incident response for critical issues, and an autonomous weekly security posture brief generated every Monday at 3:00 a.m. This automation shifts human expertise from initial alert triage to evaluating agent assessments, significantly improving efficiency and consistent visibility.

Key takeaway

For AI Security Engineers managing growing cloud footprints, integrating an AI agent platform like Cohere North with your cloud security platform can drastically cut incident response times. You can automate initial triage, generate comprehensive IR reports, and create tickets from a single prompt, freeing your team to focus on strategic evaluation rather than manual data correlation. Consider replicating this architecture to shift your security operations from reactive alert handling to proactive assessment.

Key insights

Integrating AI agents with cloud security platforms automates incident response, reducing manual effort and accelerating triage.

Principles

Method

Connect an AI agent platform (e.g., Cohere North) to a cloud security platform (e.g., Wiz) via a custom MCP server exposing atomic API tools, then define workflows with structured system prompts.

In practice

Topics

Code references

Best for: AI Security Engineer, AI Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by cohere.com via Google News.