arXiv:2606.18325v1 Announce Type: cross Abstract: Enterprise intrusion response still depends on static playbooks and analyst-driven triage, creating delay between alert generation and containment. We present Agentra, a supervisable multi-agent Intrusion Response System (IRS) framework that converts alerts from IDS, EDR, and XDR platforms into structured incident response plans grounded in MITRE ATT&CK, MITRE D3FEND, and NIST CSF 2.0. Agentra decomposes response reasoning across role-scoped agents, validates proposed plans through a bounded Planner--Validator review loop, screens retrieved thr
The accelerating complexity and volume of cyber threats, coupled with advancements in multi-agent AI, necessitate more autonomous and adaptive intrusion response systems.
This development signifies a substantial leap toward autonomous cyber defense, reducing human dependency and response times in enterprise security operations.
The shift from static, human-driven playbooks to supervisable multi-agent AI frameworks fundamentally alters enterprise intrusion response, making it more dynamic and efficient.
- · Cybersecurity solution providers
- · Enterprises with complex IT infrastructure
- · AI/ML developers
- · Traditional SOC playbook vendors
- · Manual security analysts
- · Attackers relying on slow defensive responses
Enterprise intrusion detection and response becomes significantly faster and more automated.
The demand for AI-driven cybersecurity professionals grows, while demand for manual triage roles may decrease.
Adversaries will increasingly use AI in their attacks, leading to an AI vs. AI cyber conflict landscape.
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Read at arXiv cs.AI