arXiv:2604.16870v2 Announce Type: replace-cross Abstract: AI agents increasingly call external tools (file system, network, APIs) through the Model Context Protocol (MCP). These tool calls are the agent's syscalls: privileged operations with side effects on shared state, yet today's safety enforcement lives entirely in userspace, where a 10-line script can bypass it. I propose Governed MCP, a kernel-resident tool governance gateway built on a logit-based safety primitive (ProbeLogits). The gateway interposes on every MCP tool call in a 6-layer pipeline: schema validation, trust tier, rate limi
The rapid deployment and increasing sophistication of AI agents necessitate robust security measures to prevent misuse and ensure controlled operation within existing system architectures.
This development addresses a critical vulnerability in AI agent deployment, moving safety enforcement from easily bypassable userspace to a more secure kernel level, impacting the trust and reliability of autonomous systems.
AI agent tool calls, previously a major security weak point, can now be governed with kernel-level rigor, fundamentally altering how secure and privileged operations are managed.
- · AI agent developers
- · Cybersecurity sector
- · Operating system vendors
- · Organizations deploying AI agents
- · Malicious actors
- · Unsecured AI agent platforms
Increased reliability and trust in AI agent deployments, expanding their use cases in sensitive environments.
New standards for AI agent security emerge, potentially leading to regulatory requirements for kernel-level tool governance.
Enhanced AI agent security might accelerate the integration of agents into critical infrastructure, increasing overall system complexity and interdependence.
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Read at arXiv cs.AI