mlsanityData to 13 Oct 2026

From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers

arXiv 2604.18652 ↗First posted 20 Apr 2026cs.CR cs.AIcited by 1

On the map: LLM agents and tool use → Agent threats, guardrails and governance

Abstract (arXiv)

The transition of agentic AI from brittle prototypes to production systems is stalled by a pervasive crisis of craft. We suggest that the prevailing orchestration paradigm-delegating the system control loop to large language models and merely patching with heuristic guardrails-is the root cause of this fragility. Instead, we propose Arbiter-K, a Governance-First execution architecture that reconceptualizes the underlying model as a Probabilistic Processing Unit encapsulated by a deterministic, neuro-symbolic kernel. Arbiter-K implements a Semantic Instruction Set Architecture (ISA) to reify probabilistic messages into discrete instructions. This allows the kernel to maintain a Security Context Registry and construct an Instruction Dependency Graph at runtime, enabling active taint propagation based on the data-flow pedigree of each reasoning node. By leveraging this mechanism, Arbiter-K precisely interdicts unsafe trajectories at deterministic sinks (e.g., high-risk tool calls or unauthorized network egress) and enables autonomous execution correction and architectural rollback when security policies are triggered. Evaluations on OpenClaw and NanoBot demonstrate that Arbiter-K enforces security as a microarchitectural property, achieving 76% to 95% unsafe interception for a 92.79% absolute gain over native policies. The code is publicly available at https://github.com/cure-lab/ArbiterOS.

Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 11 of its 20 references that are in the map. First posted on arXiv 20 Apr 2026.

Builds on

11 of 20 references.

Closest ancestors · 6

Same direction, newest first

  1. 2026ClawGuard: A Runtime Security Framework for Tool-Augmented LLM Agents Against Indirect Prompt Injection13 Apr
  2. 2025AGENTSAFE: A Unified Framework for Ethical Assurance and Governance in Agentic AI2 Dec
  3. 2025OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents17 Jun
  4. 2024Agent-SafetyBench: Evaluating the Safety of LLM Agents19 Dec
  5. 2024Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents3 Oct
  6. 2024AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents19 Jun

Other references · 5

  1. 2024TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Taskscited by 313
  2. 2026ClawKeeper: Comprehensive Safety Protection for OpenClaw Agents Through Skills, Plugins, and Watcherscited by 19
  3. 2024Know When To Stop: A Study of Semantic Drift in Text Generationcited by 18
  4. 2023Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineeringcited by 17
  5. 2026AI Agent Systems: Architectures, Applications, and Evaluationcited by 13

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026SARC: A Governance-by-Architecture Framework for Agentic AI Systems
  2. 2026Trustworthy Agentic AI Requires Deterministic Architectural Boundaries
  3. 2026Trustworthy Agentic AI: A Comprehensive Cybersecurity and Systems Survey on Threat Landscapes, Defense Architectures, and Open Challenges
  4. 2026AgentKernel: The Trust-Native Agentic Operating System
  5. 2026Towards a Systems Foundation for Agentic Skills: Architecture, Lifecycle, and Security
  6. 2025From Craft to Constitution: A Governance-First Paradigm for Principled Agent Engineering
  7. 2026Toward a Modular Architecture for Embedded AI Agent Systems at the Edge
  8. 2026Sovereign Agentic Loops: Decoupling AI Reasoning from Execution in Real-World Systems