Zafran Agentic Exposure Management is a vulnerability management platform that uses autonomous AI agents to automate the vulnerability management lifecycle. The platform addresses the challenge of attackers moving faster than manual patching processes by automating exposure investigation, asset owner identification, exploitability validation, and report generation. The system operates through an AI-Native Exposure Graph that continuously maps exposures to compensating controls. It correlates vulnerabilities with internet reachability, control misconfigurations, and critical-asset context to identify toxic combinations of exposures. The platform models exposure at the component level using SBOM inventory and dependency intelligence to locate affected libraries and packages. Key capabilities include zero-day exposure hunting that identifies newly disclosed vulnerabilities before exploitation, exploitability validation that confirms whether specific configurations and conditions make exploitation possible, and automated asset ownership mapping through correlation of tags, login traces, and communication patterns. The platform generates mitigation plans, visualizes attack paths with mapped MITRE techniques, and provides impact analysis by mapping dependencies and assessing risk deltas before patch deployment. The system includes automated reporting for compliance with evidence-backed reports containing timestamps, validation data, and resolution context. Security controls include AWS Bedrock Guardrails for content filtering, human-in-the-loop approvals for sensitive actions, strict input validation, and full audit logging. All customer data remains within Zafran's secure AWS environment with strict tenant isolation.