{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"The Good Tech Companies ","title":"How to audit what your AI agents are accessing","html":"","width":"100%","height":180,"duration":343,"description":"\n This story was originally published on HackerNoon at: https://hackernoon.com/how-to-audit-what-your-ai-agents-are-accessing.\nLearn how to audit AI agents with identity-based logging, LLM request tracking, data controls, tool authorization, and pre-request security policies.\nCheck more stories related to undefined at: https://hackernoon.com/c/undefined.\n You can also check exclusive content about #ai-agent-security, #ai-agent-observability, #llm-request-auditing, #ai-gateway-security, #llm-data-governance, #ai-tool-call-authorization, #ai-agent-activity-logging, #good-company, and more.\nThis story was written by: @tailscale-ad. Learn more about this writer by checking @tailscale-ad's about page,\n and for more stories, please visit hackernoon.com.\nAI agents can make dozens of LLM and tool calls during a single task, creating a visibility problem for enterprises. This article explains how Aperture uses identity-based routing, session tracking, request and response logging, access controls, tool authorization, PII filtering, and spending quotas to make agent activity auditable. The goal is to give security teams a clear record of who accessed what, where data went, what was blocked, and who accessed the resulting logs.","thumbnail_url":"https://img.transistorcdn.com/HZ9CRzf5js9DK86xzUVMWBRbXYwg4dA8xVXJGVzpL6Y/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8xMTNl/MjgwMmI0ZmEzNThj/YmJiOWNiN2UyZmRm/MzY3My5qcGVn.webp","thumbnail_width":300,"thumbnail_height":300}