Governed MCP: Kernel-Level Tool Governance for AI Agents via Logit-Based Safety Primitives

• URL: http://arxiv.org/abs/2604.16870v1
• Date: Sat, 18 Apr 2026 06:40:20 GMT
• Title: Governed MCP: Kernel-Level Tool Governance for AI Agents via Logit-Based Safety Primitives
• Abstract summary: Governed MCP is a tool governance gateway built on a logit-based safety primitive.<n>The gateway interposes on every MCP tool call in a 6-layer pipeline.<n>I implement Governed MCP in a bare-metal x86_64 OS in approximately 86,000 lines of Rust.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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, companion paper: arXiv:2604.11943). The gateway interposes on every MCP tool call in a 6-layer pipeline: schema validation, trust tier check, rate limit, adversarial pre-filter, ProbeLogits gate (the load-bearing semantic check), and constitutional policy match, with a Blake3-hashed audit chain. I implement Governed MCP in Anima OS, a bare-metal x86_64 OS in approximately 86,000 lines of Rust. The five non-inference layers add 65.3 microseconds of overhead per call; ProbeLogits adds 65 ms (per-token-class semantic decision) on 7B Q4_0. A 4-config ablation on a 101-prompt MCP-domain benchmark shows that removing the ProbeLogits layer collapses F1 from 0.773 to 0.327 (Delta F1 = -0.446) -- hand-rule firewalling alone is insufficient. All 15 WASM-to-system host functions in the runtime route through the gateway (complete mediation of the WASM ABI surface; the scope and caveats of this claim are stated in Section 4.6); a 10-LoC userspace bypass that defeats existing guardrail libraries is structurally impossible against the kernel-resident gate.

Related papers

• Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning [67.04448659688579]
  FGLGuard cuts AgentDojo's ground-success rate by 43% at near-unguarded utility, zero API cost, and negligible capability loss.<n>Federation is not optional: off-the-shelf transfer collapses under distribution shift.<n>Live FGLGuard cuts AgentDojo's ground-success rate by 43% at near-unguarded utility, zero API cost, and negligible capability loss.
  arXiv  Detail & Related papers  (2026-09-02T07:57:12Z)
• LMSM: LLM Security Framework Inspired by Linux Security Modules [56.93644694627783]
  Large language models (LLMs) are increasingly deployed with layered defenses, yet malicious prompts can still bypass them.<n>We present Language Model Security Modules (LMSM), a security framework that adapts the separation behind Linux Security Modules (LSM) to LLM serving.
  arXiv  Detail & Related papers  (2026-08-26T12:13:05Z)
• Understanding and Evaluating Claw-like Agent Security Through a Computer-Systems Lens [65.53494487819053]
  Claw-like AI agents (e.g., OpenClaw) are always-on processes with persistent access to credentials, files, tools, and external services.<n>We adopt a computer-system analogy: treating a Claw-like agent as an agentic computer system whose gateway runtime plays an OS-like mediation role.<n>We develop SafeClawArena, a benchmark of 406 adversarial tasks across four attack surfaces.
  arXiv  Detail & Related papers  (2026-06-29T18:00:45Z)
• A hardware-safety-gated system for LLM-written native ARTIQ control code on a trapped-ion platform [18.226528651110133]
  Large-language-model (LLM) agents can write and run experimental control code.<n>Unchecked code can damage the apparatus, and there is no formal, per-operation boundary between human authorization/supervision, and agent decisions.<n>We present a control system that places an LLM agent in the loop of a trapped-ion experiment while enforcing such a boundary.
  arXiv  Detail & Related papers  (2026-06-25T16:19:23Z)
• A Deterministic Control Plane for LLM Coding Agents [0.0]
  A prevalence study of 10,008 GitHub repositories finds that agent configurations propagate as undeclared shared components.<n>We propose a deterministic control plane above the harness that maps one-to-one to these gaps.
  arXiv  Detail & Related papers  (2026-06-25T12:02:18Z)
• From Attack Simulation to SIEM Rule: Deterministic Detection-as-Code Synthesis with Probe-Level Traceability [51.56484100374058]
  Security teams simulate attacks against their own systems to check whether their monitoring would catch a real intruder.<n>A human bridges that gap by hand, reading each finding and writing the corresponding Sigma rule.<n>We show this translation can be partially automated when probes are drawn from a locked corpus.
  arXiv  Detail & Related papers  (2026-06-03T14:26:25Z)
• Architectural Obsolescence of Unhardened Agentic-AI Runtimes [0.0]
  upstream OpenClaw is the most engineered single-user agentic-AI gateway in public release.<n>We show that recall is 0.000 on every cell of every confusion matrix.<n>We argue that unhardened agentic-AI runtimes are architecturally obsolete.
  arXiv  Detail & Related papers  (2026-05-03T06:38:12Z)
• From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers [19.861459645485976]
  Arbiter-K is a Governance-First execution architecture that reconceptualizes the underlying model as a Probabilistic Processing Unit.<n>We show that Arbiter-K enforces security as a microarchitectural property, achieving 76% to 95% unsafe interception for a 92.79% absolute gain over native policies.
  arXiv  Detail & Related papers  (2026-04-20T05:25:37Z)
• ProbeLogits: Kernel-Level LLM Inference Primitives for AI-Native Operating Systems [0.0]
  An OS kernel that runs LLM inference internally can read logit distributions before any text is generated.<n>This paper presents ProbeLogits, a kernel-level operation that performs a single forward pass and reads specific token logits to classify agent actions as safe or dangerous.
  arXiv  Detail & Related papers  (2026-04-13T18:32:02Z)
• LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations [2.1142550386295853]
  This paper presents the LLM-assisted network Governance (LanG), an open-source, governance-aware agentic AI platform for unified security operations.<n>The platform supports multi-tenant isolation, role-based access, and fully local deployment.<n>Finetuned anomaly and threat detectors achieve weighted F1 scores of 99.0% and 91.0%, respectively, in intrusion-detection benchmarks.
  arXiv  Detail & Related papers  (2026-04-07T05:22:25Z)
• ShieldNet: Network-Level Guardrails against Emerging Supply-Chain Injections in Agentic Systems [56.613157564882925]
  Malicious behaviors are embedded in seemingly benign tools, silently hijacking agent execution, leaking sensitive data, or triggering unauthorized actions.<n>Despite their growing impact, there is currently no comprehensive benchmark for evaluating such threats.<n>We propose ShieldNet, a network-level guardrail framework that detects supply-chain poisoning by observing real network interactions.
  arXiv  Detail & Related papers  (2026-04-06T05:15:00Z)
• ML Defender (aRGus NDR): An Open-Source Embedded ML NIDS for Botnet and Anomalous Traffic Detection in Resource-Constrained Organizations [0.0]
  We present an open-source network intrusion detection system built in C++20, deployable on commodity hardware at 150-200 USD.<n> ML Defender implements a six-component pipeline over eBPF/XDP packet capture, ZeroMQ transport, and Protocol Buffers serialization.<n>The Ransomware Threat Wins policy selects the maximum arithmetic of both scores, using ML inference to suppress false positives.
  arXiv  Detail & Related papers  (2026-04-03T05:20:13Z)
• Governing Dynamic Capabilities: Cryptographic Binding and Reproducibility Verification for AI Agent Tool Use [0.0]
  No existing security layer verifies what an AI agent can do, whether it executed what it claims, or what happened in a multi-agent interaction.<n>Existing frameworks conflate the two, enabling silent capability escalation and leaving interactions without verifiable provenance.<n>We derive three Agent Governance Requirements: capability integrity (G1), behavioral verifiability (G2), and interaction auditability (G3)<n>We validate with two crypto-agnostic instantiations -- basic (Ed25519, SHA-256; 97 us verify) and enhanced (BBS+ selective disclosure, Groth16 DV-SNARK; 13.8 ms)
  arXiv  Detail & Related papers  (2026-03-15T11:46:57Z)
• CLASP: Defending Hybrid Large Language Models Against Hidden State Poisoning Attacks [48.54598003197356]
  State space models (SSMs) like Mamba have gained significant traction as efficient alternatives to Transformers.<n>HiSPAs, a recently discovered vulnerability that corrupts SSM memory through adversarial strings, pose a critical threat to these architectures.<n>We introduce the CLASP model to defend against this threat.
  arXiv  Detail & Related papers  (2026-03-12T17:29:55Z)
• Trace: Securing Smart Contract Repository Against Access Control Vulnerability [58.02691083789239]
  GitHub hosts numerous smart contract repositories containing source code, documentation, and configuration files.<n>Third-party developers often reference, reuse, or fork code from these repositories during custom development.<n>Existing tools for detecting smart contract vulnerabilities are limited in their ability to handle complex repositories.
  arXiv  Detail & Related papers  (2025-10-22T05:18:28Z)
• LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools? [50.60770039016318]
  We present LiveMCPBench, the first comprehensive benchmark for benchmarking Model Context Protocol (MCP) agents.<n>LiveMCPBench consists of 95 real-world tasks grounded in the MCP ecosystem.<n>Our evaluation covers 10 leading models, with the best-performing model reaching a 78.95% success rate.
  arXiv  Detail & Related papers  (2025-08-03T14:36:42Z)
• DRIFT: Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents [52.92354372596197]
  Large Language Models (LLMs) are increasingly central to agentic systems due to their strong reasoning and planning capabilities.<n>This interaction also introduces the risk of prompt injection attacks, where malicious inputs from external sources can mislead the agent's behavior.<n>We propose a Dynamic Rule-based Isolation Framework for Trustworthy agentic systems, which enforces both control and data-level constraints.
  arXiv  Detail & Related papers  (2025-06-13T05:01:09Z)
• SOPBench: Evaluating Language Agents at Following Standard Operating Procedures and Constraints [59.645885492637845]
  SOPBench is an evaluation pipeline that transforms each service-specific SOP code program into a directed graph of executable functions.<n>Our approach transforms each service-specific SOP code program into a directed graph of executable functions and requires agents to call these functions based on natural language SOP descriptions.<n>We evaluate 18 leading models, and results show the task is challenging even for top-tier models.
  arXiv  Detail & Related papers  (2025-03-11T17:53:02Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.