From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers
- URL: http://arxiv.org/abs/2604.18652v1
- Date: Mon, 20 Apr 2026 05:25:37 GMT
- Title: From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers
- Abstract summary: 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.
- Score: 19.861459645485976
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
Related papers
- HazardAuditor: From Executable Threats to Safer Computer-Use Agents [50.06351661912873]
Existing guard models target static prompts and responses.<n>Existing safety platforms produce evaluation verdicts rather than the normalized supervision a guard model needs to learn.<n>We introduce HazardAuditor, an execution-grounded framework that closes both gaps.
arXiv Detail & Related papers (2026-09-14T07:09:33Z) - 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) - Provably Secure Agent Guardrail [89.79561918065122]
Existing defense architectures rely on empirical semantic guardrails and probabilistic large model adjudicators.<n>This paper proposes a new security paradigm for agents based on the fundamental limitations of logical reasoning.
arXiv Detail & Related papers (2026-05-28T02:12:41Z) - Parallax: Why AI Agents That Think Must Never Act [0.0]
This paper introduces Parallax, a paradigm for safe autonomous AI execution grounded in four principles.<n>We present OpenParallax, an open-source reference implementation in Go, and evaluate it usingAssume-Compromise Evaluation.<n>Across 280 adversarial test cases in nine attack categories, Parallax blocks 98.9% of attacks with zero false positives under its default configuration, and 100% of attacks under its maximum-security configuration.
arXiv Detail & Related papers (2026-04-14T17:20:48Z) - Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors [48.881343993730844]
Safety-aligned large language models (LLMs) are increasingly deployed in real-world pipelines.<n> adversaries can distribute backdoored checkpoints that behave normally under standard evaluation but jailbreak when a hidden trigger is present.<n>Recent post-hoc weight-editing methods offer an efficient approach to injecting such backdoors.
arXiv Detail & Related papers (2026-04-14T06:48:33Z) - OpenKedge: Governing Agentic Mutation with Execution-Bound Safety and Evidence Chains [2.124730017640531]
We introduce OpenKedge, a protocol that redefines mutation as a governed process.<n>Intent-to-Execution Evidence Chain (IEEC) links intent, context, policy decisions, execution bounds, and outcomes into a unified lineage.<n>We evaluate OpenKedge across multi-agent conflict scenarios and cloud infrastructure mutations.
arXiv Detail & Related papers (2026-04-07T22:51:08Z) - Clawed and Dangerous: Can We Trust Open Agentic Systems? [12.04979073308511]
Open agentic systems combine planning with external capabilities, persistent memory, and privileged execution.<n>This paper introduces a six-dimensional analytical taxonomy and synthesizes 50 papers spanning attacks, benchmarks, defenses, audits, and adjacent engineering foundations.<n>Our review shows that the literature is relatively mature in attack characterization and benchmark construction, but remains weak in deployment controls, operational governance, persistent-memory integrity, and capability revocation.
arXiv Detail & Related papers (2026-03-27T09:45:12Z) - Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw [42.9467373594646]
This report presents a comprehensive security analysis of the OpenClaw ecosystem.<n>We highlight critical vulnerabilities such as prompt injection-driven Remote Code Execution (RCE), sequential tool attack chains, context amnesia, and supply chain contamination.<n>To address these systemic architectural flaws, we introduce the Full-Lifecycle Agent Security Architecture (FASA)<n>This theoretical defense blueprint advocates for zero-trust agentic execution, dynamic intent verification, and cross-layer reasoning-action correlation.
arXiv Detail & Related papers (2026-03-13T04:33:05Z) - AJAR: Adaptive Jailbreak Architecture for Red-teaming [1.356919241968803]
AJAR is a proof-of-concept framework designed to bridge the gap between "red-teaming" and "action security"<n>AJAR decouples adversarial logic from the execution loop, encapsulating state-of-the-art algorithms like X-Teaming as standardized, plug-and-play services.<n> AJAR is open-sourced to facilitate the standardized, environment-aware evaluation of this emerging attack surface.
arXiv Detail & Related papers (2026-01-16T03:30:40Z) - ReasAlign: Reasoning Enhanced Safety Alignment against Prompt Injection Attack [52.17935054046577]
We present ReasAlign, a model-level solution to improve safety alignment against indirect prompt injection attacks.<n>ReasAlign incorporates structured reasoning steps to analyze user queries, detect conflicting instructions, and preserve the continuity of the user's intended tasks.
arXiv Detail & Related papers (2026-01-15T08:23:38Z) - CaMeLs Can Use Computers Too: System-level Security for Computer Use Agents [60.98294016925157]
AI agents are vulnerable to prompt injection attacks, where malicious content hijacks agent behavior to steal credentials or cause financial loss.<n>We introduce Single-Shot Planning for CUAs, where a trusted planner generates a complete execution graph with conditional branches before any observation of potentially malicious content.<n>Although this architectural isolation successfully prevents instruction injections, we show that additional measures are needed to prevent Branch Steering attacks.
arXiv Detail & Related papers (2026-01-14T23:06:35Z) - The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search [58.8834056209347]
Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety guardrails to elicit harmful outputs.<n>We introduce the Correlated Knowledge Attack Agent (CKA-Agent), a dynamic framework that reframes jailbreaking as an adaptive, tree-structured exploration of the target model's knowledge base.
arXiv Detail & Related papers (2025-12-01T07:05:23Z) - Adaptive Attacks on Trusted Monitors Subvert AI Control Protocols [80.68060125494645]
We study adaptive attacks by an untrusted model that knows the protocol and the monitor model.<n>We instantiate a simple adaptive attack vector by which the attacker embeds publicly known or zero-shot prompt injections in the model outputs.
arXiv Detail & Related papers (2025-10-10T15:12:44Z) - 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)
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.