Zero Trust for AI Agents Starts With Fixing Zero Visibility
Guidance says AI-agent Zero Trust needs inventory first, citing shadow agents and a $600,000 METR token theft.
A commentary argues that Zero Trust for AI agents fails unless organizations inventory agents before adding enforcement. Veeam research cited in the piece says 70 percent of organizations already have AI workflows contacting sensitive data without full oversight, and 67 percent cannot fully track employee-built autonomous workflows. It describes a METR incident in which an attacker found a personal EC2 instance running an agentic app, bypassed authentication, stole a model-provider API key, and used about $600,000 in tokens over three weeks with no spend limit. The suggested order is to discover agents via spend, network, endpoint, browser, and SaaS signals before restricting unapproved tools.
- Veeam says 70 percent of AI workflows touch sensitive data without full oversight.
- SANS says agent inventory must come before Zero Trust enforcement.
- A METR agent on personal EC2 leaked an API key worth about $600,000 in tokens.
- Network, endpoint, browser, and SaaS views each miss large parts of agent use.
- Products
- Amazon EC2
- Victims
- METRHugging Face
- Organizations
- VeeamSANSMETRHugging FaceOpenAI
From the original article
7 min read at thehackernews.com
The way we talk about AI agents is shifting, and the way we implement them requires an even more fundamental shift. While earlier discourse focused on how quickly organizations could stand up agents and how much productivity they could promise, a string of recent incidents, including a widely discussed intrusion at Hugging Face during an evaluation of OpenAI agents, has spurred organizations to
thehackernews.com
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