MasDrift: Benchmarking Authorization Preservation Across Multi-Agent Architectures
- URL: http://arxiv.org/abs/2608.07556v2
- Date: Tue, 11 Aug 2026 07:14:50 GMT
- Title: MasDrift: Benchmarking Authorization Preservation Across Multi-Agent Architectures
- Abstract summary: We introduce MasDrift, a benchmark of 600 benign productivity tasks across eight domains.<n>MasDrift compares single-agent, centralized, and decentralized coordination while varying hierarchy depth and peer width.<n>We compare two defenses that differ in where authorization evidence resides. One re-anchors every pending call to the original user request. The other carries an attenuated policy along the delegation chain.
- Score: 23.859862132370168
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Multi-agent systems (MAS) decompose long-horizon tasks across supervisors and subagents, but delegated goals do not necessarily carry their original authorization boundaries. Existing safety benchmarks mainly study adversarial compromise, while work on constraint drift lacks controlled architecture-level evaluation. We introduce MasDrift, a benchmark of 600 benign productivity tasks across eight domains. Each task pairs required work with reserved actions. MasDrift compares single-agent, centralized, and decentralized coordination while varying hierarchy depth and peer width, measuring task completion and authorization preservation. Across generic multi-agent conditions, centralized hierarchies achieve 93.9--98.6% task completion versus 85.7--87.0% for peer networks, while unauthorized actions occur in 2.7--19.8% of tasks versus 0.6--0.8%, a gap that widens with hierarchy depth. We further compare two defenses that differ in where authorization evidence resides. One re-anchors every pending call to the original user request. The other carries an attenuated policy along the delegation chain. Re-anchoring reduces unauthorized actions in every model configuration we evaluate, at a cost of 1.6 points of pooled completion. Chain propagation blocks required work instead, forfeiting up to 36.3 points. A heterogeneous case study confirms that the failure follows from coordination rather than model strength. MasDrift exposes a centralization tradeoff and makes authorization preservation a measurable property of MAS design.
Related papers
- Empirical Evaluation of Task-Based Permission Scoping Architecture for AI Agents [0.0]
Role-based access control leaves every credential standing exposed whether or not the current task uses them.<n>Prior work defined this as the task-context mismatch, and proposed a three-source permission architecture.<n>This paper presents that evaluation end to end by implementing the security gate; a fine-tuned RoBERTa-large encoder which matched few-shot trained Claude Haiku 4.5 on classification quality.
arXiv Detail & Related papers (2026-09-14T11:48:35Z) - Delegation Without Trust: An Empirical Gap Analysis of Identity, Authorization, and Runtime Governance in Multi-Agent LLM Systems [0.0]
We present a threat model for multi-agent delegation centered on four adversaries.<n>We show a default runtime modeling common practice fails all four threats.<n>We implement and adversarially evaluate an authorization broker that closes the gap.
arXiv Detail & Related papers (2026-08-31T19:09:34Z) - Governance at the Boundary: How Agent Decomposition Degrades Policy Compliance [6.411104724993454]
We introduce Fiducia-bench, a benchmark for the governability of financial agents.<n>We use it to study a question no prior benchmark addresses: does an agent degrade its governance?<n>Policy-relevant facts discovered by one component are attenuated at the handoff boundary before reaching the component that must act on them.
arXiv Detail & Related papers (2026-08-17T03:31:59Z) - ClawArena-Team: Benchmarking Subagent Orchestration and Dynamic Workflows in Language-Model Agents [61.184954205350984]
ClawArena-Team is a benchmark of 41 multi-turn, multimodal, multi-agent scenarios spanning 258 evaluation rounds and 72 staged updates.<n>All scoring is execution-based with no LLM judge: an overall score -- the Subagent-Management Score (SMS) -- multiplies task correctness by a least-privilege and modality-routing factor.
arXiv Detail & Related papers (2026-06-30T06:06:08Z) - The Best-Laid SCHEMEs: Coordinated Sabotage and Monitoring in Multi-Agent Systems [0.0]
SCHEME is a benchmark of 17 task instances across 7 settings and 8 real open-source libraries.<n>Each setting is designed so that no proper subset of agents can succeed alone.<n>We show coordinated sabotage is already practical with GPT 5.1 Codex and Gemini 3.1 Pro.
arXiv Detail & Related papers (2026-05-27T23:30:21Z) - Do Coding Agents Understand Least-Privilege Authorization? [14.240332406666779]
We study whether current models can infer authorization boundaries themselves.<n>We show that frontier models often omit permissions required by the execution chain while also granting unused or sensitive accesses.<n>We propose Sufficiency-Tightness Decomposition, which first generates a coverage-oriented policy and then audits each granted entry for grounding and sensitivity.
arXiv Detail & Related papers (2026-05-14T14:05:58Z) - PRISM: : Planning and Reasoning with Intent in Simulated Embodied Environments [59.07829883257003]
Built on five multi-room apartments, PRISM structures 300 human-verified tasks into three capability tiers.<n>PRISM exposes an agent-agnostic executable action API that allows arbitrary agents to be evaluated end-to-end.
arXiv Detail & Related papers (2026-05-12T04:59:47Z) - EnactToM: An Evolving Benchmark for Functional Theory of Mind in Embodied Agents [75.01735520608075]
Existing benchmarks mostly test literal Theory of Mind (ToM) by asking direct belief questions.<n>We introduce EnactToM, an evolving benchmark of 300 embodied multi-agent tasks set in a 3D household.<n>On the hard split, all seven evaluated frontier models score 0.0% Pass3 on functional task completion, while averaging 45.0% on literal belief probes.
arXiv Detail & Related papers (2026-05-11T00:04:19Z) - SDOF: Taming the Alignment Tax in Multi-Agent Orchestration with State-Constrained Dispatch [0.0]
We present SDOF, a framework that treats multi-agent execution as a constrained state machine.<n>On a recruitment system backed by the Beisen iTalent platform, 185 expert-curated scenarios trigger 1671 live API calls.<n>Our GSPO-aligned 7B Intent Router achieves higher joint accuracy than zero-shot GPT-4o on this FSM-constrained adversarial routing benchmark.
arXiv Detail & Related papers (2026-04-20T12:51:39Z) - AITH: A Post-Quantum Continuous Delegation Protocol for Human-AI Trust Establishment [9.198471344145092]
We present AITH (AI Trust Handshake), a post-quantum continuous delegation protocol.<n>AITH introduces: (1) a Continuous Delegation Certificate signed once with ML-DSA-87 (FIPS 204, NIST Level 5), replacing per-operation signing with sub-microsecond boundary checks at 4.7M ops/sec; (2) a six-check Boundary Engine enforcing hard constraints, rate limits, and escalation triggers with zero cryptographic overhead on the critical path; and (3) a push-based Revocation Protocol propagating invalidation within one second.
arXiv Detail & Related papers (2026-04-09T01:30:28Z) - Claw-Eval: Toward Trustworthy Evaluation of Autonomous Agents [66.97968363332465]
We introduce Claw-Eval, an end-to-end evaluation suite addressing all three gaps in agent benchmarks.<n>Claw-Eval comprises 300 human-verified tasks spanning 9 categories across three groups.<n>Every agent action is recorded through three independent evidence channels.
arXiv Detail & Related papers (2026-04-07T17:43:18Z) - Towards a Science of Scaling Agent Systems [79.64446272302287]
We formalize a definition for agent evaluation and characterize scaling laws as the interplay between agent quantity, coordination structure, modelic, and task properties.<n>We derive a predictive model using coordination metrics, that cross-validated R2=0, enabling prediction on unseen task domains.<n>We identify three effects: (1) a tool-coordination trade-off: under fixed computational budgets, tool-heavy tasks suffer disproportionately from multi-agent overhead, and (2) a capability saturation: coordination yields diminishing or negative returns once single-agent baselines exceed 45%.
arXiv Detail & Related papers (2025-12-09T06:52:21Z) - Eigen-1: Adaptive Multi-Agent Refinement with Monitor-Based RAG for Scientific Reasoning [53.45095336430027]
We develop a unified framework that combines implicit retrieval and structured collaboration.<n>On Humanity's Last Exam (HLE) Bio/Chem Gold, our framework achieves 48.3% accuracy.<n>Results on SuperGPQA and TRQA confirm robustness across domains.
arXiv Detail & Related papers (2025-09-25T14:05:55Z) - A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied
Tasks [111.34055449929487]
We introduce the novel task FurnMove in which agents work together to move a piece of furniture through a living room to a goal.
Unlike existing tasks, FurnMove requires agents to coordinate at every timestep.
We identify two challenges when training agents to complete FurnMove: existing decentralized action sampling procedures do not permit expressive joint action policies.
Using SYNC-policies and CORDIAL, our agents achieve a 58% completion rate on FurnMove, an impressive absolute gain of 25 percentage points over competitive decentralized baselines.
arXiv Detail & Related papers (2020-07-09T17:59:57Z)
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.