IRCopilot: Automated Incident Response with Large Language Models

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• arXiv: 2505.20945
• DOI: https://doi.org/10.48550/arXiv.2505.20945
• Submitted: 2025-05-27; revised: 2025-10-30
• Source URL: https://arxiv.org/abs/2505.20945

Abstract Summary

The paper proposes IRCopilot, a framework for automated incident response using multiple LLM-based session components. It identifies practical challenges including context loss, hallucinations, privacy concerns, and weak context-specific recommendation quality, then evaluates the framework on incident-response tasks.

Why It Matters For The Wiki

This is useful for AI SOC response-stage research. It can ground questions about whether LLM agents can move beyond triage into response planning while controlling hallucination, context loss, privacy exposure, and unsafe recommendation risks.

Recommended Ingest Notes

• Extract failure modes and session-component architecture.
• Link to AI SOC, self-improving SOC prompt governance, response safety, and evidence provenance.