VERA: Authority-Preserving Edge Revocation for Federated AI-Agent Workflows
cs.AI
Submitted: 2026-08-30
Updated: 2026-08-30
License: http://creativecommons.org/licenses/by/4.0/
The gist: Modern agent frameworks compose planners, tool agents, remote services, and shared specialists into runtime delegation graphs, but their revocation APIs still resemble token or subtree invalidation.
Terminology
Abstract
Modern agent frameworks compose planners, tool agents, remote services, and shared specialists into runtime delegation graphs, but their revocation APIs still resemble token or subtree invalidation. When one delegation is withdrawn, the runtime must know which agents lose authority while independently authorized agents keep working. We study this authority consistency problem and introduce VERA (Verifiable Edge Revocation for Agents), a verifier-checkable revocation contract and API emitted by agent-runtime adapters as signed evidence. Under disjunctive authority, revoking edge e invalidates exactly T intent(e,G) = reach(G) reach(G e), the agents whose every authorizing root path used e. Used as a contract, this target exposes two runtime failures: tree cascades over-revoke shared agents, while deployer-scoped cascades under-revoke cross-domain descendants. In a LangGraph framework-replt cells repeated 20 times yield 500compiled-framework traces and 2,000 valid signed delegation decisions; 13/25 cells contain runtime multi-parsharing and 8/25 contain cross-deployer shies 500/500 target proofs, preserves all320 alternate-parent shared-agent cases that tree cascade revokes, and rejects unauthorized signers and omission attacks. Baseline replay over 1,9that holder/node and tree-style targetscannot express this behavior. We further validate schema portability on A2A, AutoGen, and CrewAI artifacts: nine traces, including five executable Cregned delegation events that pass schema and signature checks.
Sources
- AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation
- Authenticated Delegation and Authorized AI Agents
- Identity Management for Agentic AI: The new frontier of authorization, authentication, and security for an AI agent world
- AIP: Agent Identity Protocol for Verifiable Delegation Across MCP and A2A
- A logical reconstruction of SPKI
- Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP
- A Vision for Access Control in LLM-based Agent Systems
- Taming Various Privilege Escalation in LLM-Based Agent Systems: A Mandatory Access Control Framework
- ChainCaps: Composition-Safe Tool-Using Agents via Monotonic Capability Attenuation
- Overlaying Governance: A Compositional Authorization Framework for Delegation and Scope in Agentic AI
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