ClawLess: A Security Model of AI Agents

Fuente: arXiv
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Main Authors: Lu, Hongyi, Liu, Nian, Wang, Shuai, Zhang, Fengwei
Format: Preprint
Published: 2026
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author Lu, Hongyi
Liu, Nian
Wang, Shuai
Zhang, Fengwei
author_facet Lu, Hongyi
Liu, Nian
Wang, Shuai
Zhang, Fengwei
contents Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve information and run code introduces significant security risks. Existing approaches attempt to regulate agent behavior through training or prompting, which does not offer fundamental security guarantees. We present ClawLess, a security framework that enforces formally verified policies on AI agents under a worst-case threat model where the agent itself may be adversarial. ClawLess formalizes a fine-grained security model over system entities, trust scopes, and permissions to express dynamic policies that adapt to agents' runtime behavior. These policies are translated into concrete security rules and enforced through a user-space kernel augmented with BPF-based syscall interception. This approach bridges the formal security model with practical enforcement, ensuring security regardless of the agent's internal design.
format Preprint
id arxiv_https___arxiv_org_abs_2604_06284
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle ClawLess: A Security Model of AI Agents
Lu, Hongyi
Liu, Nian
Wang, Shuai
Zhang, Fengwei
Cryptography and Security
Artificial Intelligence
Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve information and run code introduces significant security risks. Existing approaches attempt to regulate agent behavior through training or prompting, which does not offer fundamental security guarantees. We present ClawLess, a security framework that enforces formally verified policies on AI agents under a worst-case threat model where the agent itself may be adversarial. ClawLess formalizes a fine-grained security model over system entities, trust scopes, and permissions to express dynamic policies that adapt to agents' runtime behavior. These policies are translated into concrete security rules and enforced through a user-space kernel augmented with BPF-based syscall interception. This approach bridges the formal security model with practical enforcement, ensuring security regardless of the agent's internal design.
title ClawLess: A Security Model of AI Agents
topic Cryptography and Security
Artificial Intelligence
url https://arxiv.org/abs/2604.06284