If Agents Were Angels, No Governance Would Be Necessary: Out-of-Band Policy Enforcement at a Trusted Tool Boundary
On the map: LLM safety and security → Prompt injection and agent security
Abstract (arXiv)
Give an agent a human's credential and it inherits the person's reach without the judgment that limits its use. It can sweep every reachable record into model context, where hidden instructions steer its next call, and every request stays credential-valid while the agent exceeds its job or absorbs a secret. Prompts are a brittle guardrail: one fallible reasoner interprets the task and enforces its limits. We present Out-of-Band Policy Enforcement (OBPE), a trusted boundary outside agent reasoning. It authorizes the typed operation and resource, narrows the query before the backend call, then filters records and fields or masks values in the response. Semantic gating can deny or hold an authorized call on argument values or external state. A data policy owner sets the maximum grant; agent policy can only narrow it. We prove, under stated conditions, that the policy plan is order-independent and agent policy cannot widen the ceiling. Field removal covers one execution; masking and history rules claim less. We release an HTTP proxy prototype simplified from our production system, with conformance tests tying its typed Cedar policy core to the model. Against Jira and ServiceNow mocks, our benchmark compares prompted agents with and without OBPE on four models, including 20 adaptive red-team tasks. A trace failure means protected data entered agent context, an exact value appeared in the answer, or a forbidden effect completed. In 3,621 trials it fell from 57.6% to 0.2%, a cluster-weighted reduction of 41.2 points [95% CI: 27.7, 54.9]; fulfillment fell from 79.1% to 60.9%, while paired safe-useful completion rose 21.8 points [9.5, 35.2]. Some answers reconstructed a value that never entered context or used filtered row counts as an oracle: shaping one execution is not noninterference. Write controls, durable approval, and temporal and aggregate policies lie outside this evaluation.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Prompt injection and agent security, one of 12 directions in LLM safety and security. Builds on 8 of its 34 references that are in the map. First posted on arXiv 27 Aug 2026.
Builds on
8 of 34 references.
Closest ancestors · 2
Same direction, newest first
- 2025Preventing Prompt Injection with Type-Directed Privilege Separation30 Sep
- 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection23 Feb
Other references · 6
- 2026Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Frameworkcited by 54
- 2024Cedar: A New Language for Expressive, Fast, Safe, and Analyzable Authorization (Extended Version)cited by 34
- 2025Robust AI Security and Alignment: A Sisyphean Endeavor?cited by 3
- 2026Incompleteness of AI Safety Verification via Kolmogorov Complexitycited by 2
- 2026The Importance of Out-of-Band Metadata for Safe Autonomous Agents: The Redpanda Agentic Data Planecited by 1
- 2026Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptionscited by 1
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- 2026AgentFlow: A Flow-Centric Policy Language and Framework for Securing LLM Agent Systems
- 2026AgentSecBench: Measuring Prompt Injection, Privacy Leakage, and Tool-Use Integrity in LLM Agents
- 2026What Can Be Enforced? A Theory of Certified Runtime Safety for Tool-Using Agents
- 2026OverAct: Measuring and Mitigating Proactive Over-Authorization in LLM Tool-Calling Agents
- 2026Goal-Autopilot: A Verifiable Anti-Fabrication Firewall for Unattended Long-Horizon Agents
- 2026Formal Policy Enforcement for Real-World Agentic Systems
- 2026The Claws in Plain Sight: Unauthorized Context Disclosure through LLM Agent Tool Calls
- 2026Alignment Contracts for Agentic Security Systems