On May 30, 2026, Simon Willison posted what might be the most practically useful thing written about AI agent safety this year: a close read of Anthropic’s engineering post on how they contain Claude across their products. If you build agentic AI systems, this is required reading — and here’s why.
The Gap Willison Identified
Willison opens with a complaint that resonates with anyone who’s evaluated sandboxing products: they’re rarely thoroughly documented. You’re handed marketing claims about “secure execution environments” with little detail about what that means in practice. Without documentation, you can’t reason about what you’re trusting or where the gaps might be.
Anthropic’s engineering post, published May 25, 2026, breaks that pattern. It’s a technical disclosure with real specifics, including actual incidents they encountered and fixed. That transparency is valuable not just for people using Anthropic products — it’s a template for how the industry should talk about agent safety.
The Containment Philosophy
Anthropic’s framing is important. They acknowledge directly that the blast radius of capable agents only grows as capabilities expand. Twelve months ago, they’d have rejected granting Claude access sufficient to take down an internal service. Today, that level of access is routine — because the containment architecture has matured to the point where the risk-reward calculation supports it.
The core engineering principle is this: don’t try to make the agent perfectly safe; cap the damage it can do. If credentials never enter the sandbox, they can’t be exfiltrated — regardless of whether the cause is a user mistake, a model finding a creative workaround, or an attacker. The architecture assumes imperfect behavior and designs accordingly.
Broad containment mechanisms include:
- Process sandboxes: Restrict what the agent process can do at the OS level
- VMs: Full virtualization for the highest-risk deployments
- Filesystem boundaries: Agents can only see what they’re explicitly given
- Egress controls: Network access is restricted to explicit allowlists
As Anthropic puts it: “We constrain where and how an agent can act with process sandboxes, VMs, filesystem boundaries, and egress controls. The goal is to set a hard boundary on what an agent can reach.”
The Three Products, Three Different Solutions
What makes the Anthropic post especially interesting is that they use different containment strategies for each of their three products — because the threat models are different.
Claude.ai: gVisor
Claude.ai uses gVisor, Google’s user-space kernel. gVisor intercepts system calls and runs them through a separate kernel proxy, meaning even if code running inside the sandbox exploits a kernel vulnerability, it’s exploiting the gVisor kernel — not the host kernel. This is a strong, well-understood security boundary appropriate for a service where millions of users are running arbitrary prompts.
Claude Code: Seatbelt (macOS) + Bubblewrap (Linux)
Claude Code runs locally on users’ machines, which creates a fundamentally different challenge: you can’t wrap the user’s entire laptop in a VM. Instead, Anthropic uses OS-level sandboxing:
- Seatbelt on macOS: Apple’s built-in sandbox framework, which restricts process capabilities at the kernel level
- Bubblewrap on Linux: A user-namespace-based sandboxing tool that creates lightweight container-like isolation without requiring root
This is a pragmatic choice for locally-run code: you can’t use gVisor without kernel access, and running a full VM would be heavyweight for a local development tool. Seatbelt and Bubblewrap provide meaningful containment with low overhead.
Cowork: Full VM
Claude Cowork — Anthropic’s agent-based collaborative work environment — runs in a full VM:
- Apple’s Virtualization framework on macOS
- HCS (Hyper-V Container Sandbox) on Windows
Full VMs for Cowork makes sense: this is where Claude might be editing real documents, accessing real file systems, running real code — the blast radius is highest, so the containment needs to be most complete. A full VM ensures that even a compromised Cowork session cannot reach the host machine.
The Incidents: Where Theory Meets Reality
Willison specifically highlights one real-world incident that illustrates why layered containment matters: an exfiltration vector via Anthropic’s own API domain.
The specific vulnerability was via api.anthropic.com/v1/files — an endpoint on Anthropic’s own infrastructure. Because egress to api.anthropic.com was implicitly trusted (it’s Anthropic’s own domain), a prompt injection or sufficiently creative model behavior could potentially have used the Files API to exfiltrate data from within the sandbox. The domain was trusted; the specific endpoint was dangerous.
This is the kind of subtle vulnerability that no amount of generic security review would catch. It requires actually building the system, deploying it, and watching for emergent attack surfaces. Anthropic found and fixed it — and they published it, which is exactly the behavior that builds the kind of trust that matters.
The Anthropic Sandbox Runtime (srt)
Willison notes that Anthropic has an open-source tool — the Anthropic Sandbox Runtime (srt) — available at github.com/anthropic-experimental/sandbox-runtime. He describes it as mature enough to give a “proper go” now. For practitioners building agentic systems who want production-ready sandboxing without rolling their own, this is worth investigating.
What This Means for Agent Builders
The practical takeaways from this disclosure:
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Choose containment at design time, not retrofit time. The right sandbox for your deployment depends on your threat model — a locally-run coding assistant has different exposure than a cloud-hosted multi-user service.
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Egress controls are as important as process isolation. You can sandbox a process perfectly and still get exfiltration via an allowed outbound HTTP connection. Allowlisting specific domains isn’t enough — specific paths may matter.
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Trust your own infrastructure as little as external infrastructure. The api.anthropic.com incident is a reminder that being on your own domain doesn’t mean being safe from prompt injection or creative routing.
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Document what you’ve built and what you’ve fixed. Anthropic’s transparency about incidents is rare in the industry. It builds trust in ways that marketing claims about “enterprise-grade security” never will.
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Layered containment beats any single layer. gVisor alone doesn’t solve egress. Egress controls alone don’t solve process compromise. The stack is the point.
The gap between “we have a sandbox” and “we have a well-documented, incident-informed, layered containment architecture” is the gap between thinking you’re safe and having reasonable evidence that you are.
Sources
- Simon Willison’s Weblog: How we contain Claude across products — May 30, 2026
- Anthropic Engineering: How we contain Claude across products — Primary source, May 25, 2026
- Simon Willison: Claude Cowork exfiltration via files API — Earlier coverage of the api.anthropic.com incident
- Anthropic Sandbox Runtime (srt) — Open-source containment tool
Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260531-0800
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