AWS Security Incident Response now provides agentic AI-powered investigation (aws.amazon.com)

AWS announced an agentic, AI-powered investigative capability inside AWS Security Incident Response that automates the slow, manual work of evidence collection and correlation during security incidents. The investigative agent—available automatically when you create a case—asks clarifying questions in plain language, then queries CloudTrail events, IAM configurations, EC2 instance metadata and cost/usage patterns (using the AWS Support service‑linked role) to build a correlated timeline and high‑level findings within minutes. Actions are logged in CloudTrail for auditability, and cases can be created or auto‑triggered from GuardDuty, Security Hub or EventBridge; customers can escalate to the AWS Customer Incident Response Team (CIRT) for deeper analysis. For the AI/ML and security communities this is a notable example of “agentic” LLM-based tooling integrated directly with cloud telemetry to shift SOC work from log-searching to decision-making. Key technical implications: NLP-driven query translation, orchestration across multiple AWS APIs, retrieval-style evidence aggregation, and a human-in-the-loop escalation model that preserves transparency and audit trails. It promises large SOC time savings (AWS cites evidence collection as ~50% of analyst effort) and smoother automation pipelines, but raises operational considerations—model output validation, guardrails per AWS Responsible AI guidance, and careful access governance—before using findings for containment actions.