Anthropic just published how they contain Claude agents, including two security incidents they got wrong

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Summary

Anthropic published a detailed engineering post on how they contain Claude agents in claude.ai, Claude Code, and Cowork, including two security incidents where their defenses failed, highlighting the need for hard environmental containment over model-layer defenses.

Anthropic dropped a solid engineering post this week about containment across claude.ai, Claude Code, and Cowork. One of the more transparent writeups from a major AI lab about what actually broke. The core insight: model-layer defenses are probabilistic and will always have a non-zero miss rate. So the real answer is hard environmental containment, not just safer models. Three patterns they use: \-claude.ai: ephemeral gVisor containers, fully server-side \-Claude Code: OS-level sandbox with human-in-the-loop approvals (93% get approved anyway, so approval fatigue is real) \-Cowork: full local VM, credentials never enter the guest Two incidents they disclosed: A red team phished an employee into running a prompt that exfiltrated AWS credentials. Succeeded 24 out of 25 times. The model had nothing to catch because the user was the one typing it. Only egress controls would have stopped it. A third-party found that Cowork’s egress allowlist passes traffic to api.anthropic.com. An attacker embedded an API key in a file in the user’s workspace, Claude followed hidden instructions, and uploaded files to the attacker’s Anthropic account. Sandbox worked perfectly and still leaked data. Their lesson: an allowlist isn’t a destination filter, it’s a capability grant. Every function reachable through an allowed domain is an attack surface. The section on persistent memory poisoning and multi-agent trust escalation at the end is worth reading too if you’re building anything agentic.
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