SUDP: Secret-Use Delegation Protocol for Agentic Systems
On the map: LLM agents and tool use → Agent threats, guardrails and governance
Abstract (arXiv)
Agentic systems increasingly act with user secrets for APIs, messaging platforms, and cloud services. Today's agent runtimes typically implement authorization by exposure: enabling action often means placing a reusable secret, or a reusable artifact derived from it, inside the runtime, so a transient prompt-injection or tool-side compromise becomes durable account compromise. Existing defenses cover adjacent pieces such as secret storage, scoped delegation, sender-constrained tokens, and runtime monitoring, but leave the combined agentic obligation without a common specification: an untrusted autonomous requester should be able to cause a user-authorized secret-backed operation without gaining reusable authority over it. We formalize this as the Agent Secret Use (ASU) problem and identify seven security properties any solution must satisfy, spanning authorization integrity and secret confidentiality. We propose the Secret-Use Delegation Protocol (SUDP), in which a requester proposes a canonical operation, the user authorizes it with a fresh authenticator-backed grant, and a custodian redeems the grant to perform the bounded use; reusable authority never crosses the requester boundary. We specialize SUDP for LLM-driven agents, where it applies whenever a tool call would exercise user-enrolled authority-bearing material. Under standard cryptographic assumptions, SUDP satisfies all seven properties when integrated with a hardware-rooted runtime. A reference implementation is available at https://github.com/xhyumiracle/sudp.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use. Builds on 35 of its 102 references that are in the map. First posted on arXiv 27 Apr 2026.
Builds on
35 of 102 references.
Closest ancestors · 20
Same direction, newest first
- 2026HDP: A Lightweight Cryptographic Protocol for Human Delegation Provenance in Agentic AI Systems6 Apr
- 2026How Your Credentials Are Leaked by LLM Agent Skills: An Empirical Study3 Apr
- 2026Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw13 Mar
- 2026Taming OpenClaw: Security Analysis and Mitigation of Autonomous LLM Agent Threats12 Mar
- 2026The Attack and Defense Landscape of Agentic AI: A Comprehensive Survey11 Mar
- 2026VIGIL: Defending LLM Agents Against Tool Stream Injection via Verify-Before-Commit9 Jan
- 2025Agent Tools Orchestration Leaks More: Dataset, Benchmark, and Mitigation18 Dec
- 2025Agentic JWT: A Secure Delegation Protocol for Autonomous AI Agents16 Sep
- 2025OpenAgentSafety: A Comprehensive Framework for Evaluating Real-World AI Agent Safety8 Jul
- 2025AgentAuditor: Human-Level Safety and Security Evaluation for LLM Agents31 May
- 2025LlamaFirewall: An open source guardrail system for building secure AI agents6 May
- 2025SAGA: A Security Architecture for Governing AI Agentic Systems27 Apr
8 more
- 2025Progent: Securing AI Agents with Privilege Control16 Apr
- 2025Defeating Prompt Injections by Design24 Mar
- 2025AgentSpec: Customizable Runtime Enforcement for Safe and Reliable LLM Agents24 Mar
- 2024Agent-SafetyBench: Evaluating the Safety of LLM Agents19 Dec
- 2024Agent Security Bench (ASB): Formalizing and Benchmarking Attacks and Defenses in LLM-based Agents3 Oct
- 2024IsolateGPT: An Execution Isolation Architecture for LLM-Based Agentic Systems8 Mar
- 2024InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents5 Mar
- 2023Identifying the Risks of LM Agents with an LM-Emulated Sandbox25 Sep
Other references · 15
- 2023GPT-4 Technical Reportcited by 18,132
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- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
- 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,339
- 2023Augmented Language Models: a Surveycited by 398
- 2024StruQ: Defending Against Prompt Injection with Structured Queriescited by 325
- 2024Defending Against Indirect Prompt Injection Attacks With Spotlightingcited by 233
- 2024SecAlign: Defending Against Prompt Injection with Preference Optimizationcited by 179
- 2025The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injectionscited by 108
- 2025Authenticated Delegation and Authorized AI Agentscited by 63
- 2025Contextual Agent Security: A Policy for Every Purposecited by 55
3 more
- 2026ClawKeeper: Comprehensive Safety Protection for OpenClaw Agents Through Skills, Plugins, and Watcherscited by 18
- 2026Security Considerations for Artificial Intelligence Agentscited by 7
- 2025OpenID Connect for Agents (OIDC-A) 1.0: A Standard Extension for LLM-Based Agent Identity and Authorizationcited by 3
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Citing papers per year: 2026: 2.
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