[Submitted on 1 Mar 2026 (
[v1](https://arxiv.org/abs/2603.00991v1)), last revised 7 May 2026 (this version, v2)]
[View PDF](https://arxiv.org/pdf/2603.00991)
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Abstract:AI agents that interact with the real world through tool calls pose fundamental safety challenges: agents might leak private information, cause unintended side effects, or be manipulated through prompt injection. To address these challenges, we propose to put the agent in a programming-language-based "safety harness": instead of calling tools directly, agents express their intentions as code in a capability-safe language: Scala 3 with capture checking. Capabilities are program variables that regulate access to effects and resources of interest. Scala's type system tracks capabilities statically, providing fine-grained control over what an agent can do. In particular, it enables local purity, the ability to enforce that sub-computations are side-effect-free, preventing information leakage when agents process classified data. We demonstrate that extensible agent safety harnesses can be built by leveraging a strong type system with tracked capabilities. Our experiments show that agents can generate capability-safe code with no significant loss in task performance, while the type system reliably prevents unsafe behaviors such as information leakage and malicious side effects.
Submission history #
From: Yichen Xu [
[view email](https://arxiv.org/show-email/dce1652d/2603.00991)]
**Sun, 1 Mar 2026 08:39:37 UTC (4,774 KB)**
[\[v1\]](https://arxiv.org/abs/2603.00991v1)
**[v2]** Thu, 7 May 2026 14:09:04 UTC (4,781 KB)
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