Stored Is Not Supported: Typed Provenance and Assertion Guardrails for Persistent AI Agents
- URL: http://arxiv.org/abs/2609.02127v1
- Date: Wed, 02 Sep 2026 05:35:33 GMT
- Title: Stored Is Not Supported: Typed Provenance and Assertion Guardrails for Persistent AI Agents
- Abstract summary: Persistent AI agents construct autobiographical state through reflection, retrieval, and consolidation.<n>We specify typed provenance and assertion guardrails for autobiographical assertion boundedness.
- Score: 2.124730017640531
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Persistent AI agents construct autobiographical state through reflection, retrieval, and consolidation. Persistence changes availability, not epistemic standing: stored or retrieved material is not thereby supported. Untrusted inputs, prompt injections, and model inferences can therefore enter persistent state and later be presented as agent history or user commitments. We specify typed provenance and assertion guardrails for autobiographical assertion boundedness, a system-relative release property requiring governed statements about the agent, user, or named relationships to satisfy accepted-evidence, temporal-validity, and disclosure policies. A typed provenance graph separates origin, dependency lineage, epistemic role, validity, and disclosure scope. A resolver evaluates authorized state projections and returns one evidential status, orthogonal conflict, staleness, and withholding flags, and a protected decision witness. A generate-verify-revise mediator then checks candidate semantic units before release and renders policy-authorized status responses. Under explicit assumptions about extraction, predicate correctness, resolution soundness, view declassification, and channel mediation, we prove a conditional assertion-boundedness contract. In an executable suite of 24 hand-authored conformance cases, typed mediation passed none of 19 unsafe opportunities unqualified while preserving all five supported controls. The flat/prior and source-tag comparison rules released 19/19 and 18/19 unsafe candidates, respectively. These results validate the encoded resolver and mediator obligations; they do not constitute an end-to-end evaluation of language models or retrieval systems.
Related papers
- An Evidence Model for Agentic Processes: Evidence Claims, Trust Assumptions, and Policy Assessment [0.0]
This paper proposes an evidence claim model for agentic processes.<n>It distinguishes artifact integrity, temporal existence, provenance, approval evidence, declared ordering, capture claim, relevance claim, deliberation traceability, monitoring claim, anchoring authorization claim, policy assessment claim, risk treatment claim, mitigation implementation claim, and management response claim.<n>The model maps these claims to mechanisms, assumptions, limitations, and threats, and situates them in an agent organization with functional CEO agent, executive, operational, evidence, and audit roles, plus a plan-do-check-act-inspired management response loop.
arXiv Detail & Related papers (2026-09-08T09:25:28Z) - Zero-Knowledge Predicate Proofs Between AI Agents: A Measured, Cross-Protocol Gateway and the Source-Integrity Gap [0.0]
Multi-agent AI platforms move quickly from staging to production, but the way agents establish trust remains rudimentary.<n>We take provable data minimisation between agents from proposal to running system.<n>A 32-bit threshold predicate proves in 6.2 ms and verifies in 1.0 ms with a 608-byte Bulletproofs proof.
arXiv Detail & Related papers (2026-08-30T23:16:17Z) - Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning [38.63002496590365]
We propose a framework for improving reliability in knowledge-intensive reasoning through equivariance-based abstention.<n>A key contributing factor is that entity mentions in context activate memorised associations, causing models to generate plausible responses ungrounded in evidence.<n>We construct multiple worlds via typed substitutions of the original input that preserve relational structure while reducing parametric priors.
arXiv Detail & Related papers (2026-08-28T07:33:29Z) - AI Slop and Hallucinations in Vulnerability Assessment: A Survey on Reasoning Failures and Trustworthy Mitigation [48.55515767840701]
"AI slop" is artifacts, hallucinated vulnerabilities, plausible but incorrect patches, and semantically repackaged bug reports.<n>This paper surveys the empirical evidence, identifies a unifying mechanism, and traces a path toward trustworthy triage.
arXiv Detail & Related papers (2026-08-26T11:48:38Z) - $Z^2$-ACT: End-to-End Verifiable Agentic Intent Control for Open 6G RAN [43.15181031994434]
We propose a zero-knowledge auditable control and zero-trust verifiable agentic intent architecture.<n>A live large language model is used in the non-real-time path to translate operator intents into Intent Contracts.<n>Results indicate improved actuation filtering and attack resilience at modest latency and signaling cost.
arXiv Detail & Related papers (2026-08-21T12:44:03Z) - From Trajectories to Evidence: Auditable Experimental Records for Industrial Research Agents [47.678562263387214]
Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings.<n>Yet a completed trajectory is not automatically evidence: generated artifacts may be unsupported or incomplete, executed rounds may be invalid or confounded, and later modifications may obscure earlier findings.<n>We introduce an evidence-grounded framework that couples bounded verification of consequential artifacts with post-execution claim qualification.
arXiv Detail & Related papers (2026-08-05T13:37:38Z) - Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle [65.6642776933861]
This survey examines the protective paradigm that has grown around this intervention point.<n>We find that most protections are still validated mainly against static or weakly adaptive adversaries.<n>We close by consolidating cross-stage countermeasures and open problems for robust, composable, and deployable owner-side protection.
arXiv Detail & Related papers (2026-08-05T00:46:50Z) - StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems [6.160059055899747]
StateFuse is a conflict-aware replicated memory contract built on standard OpSet/CRDT merge.<n>We evaluate StateFuse against flat multi-value, raw-log, provenance-style, and collapsed baselines under matched resolver and verification policies.
arXiv Detail & Related papers (2026-07-07T05:06:33Z) - AgentSecBench: Measuring Prompt Injection, Privacy Leakage, and Tool-Use Integrity in LLM Agents [0.2864713389096699]
We introduce AgentSecBench as an empirical instantiation of a formal security framework for this problem.<n>It defines three games-instruction-integrity, retrieval-confidentiality, and capability-integrity-under a common notion of intent-to-execution noninterference with permitted leakage.<n>It represents an application policy as a projection onto authorized observations and capabilities, distinguishes prompt annotations from enforcing projections, and measures both adversarial advantage and whether a defense closes the relevant model-visible channel before generation.
arXiv Detail & Related papers (2026-05-25T18:53:22Z) - Trust but Verify: Prover-Verifier Deliberation for Selective LLM Prediction [4.273094752480624]
We introduce prover-verifier deliberation (PVD), an inference-time protocol grounded in interactive proof theory.<n>PVD produces both an answer and a structured confidence verdict, allowing a system to report high-confidence answers while abstaining on uncertain cases.
arXiv Detail & Related papers (2026-05-24T15:23:27Z) - Affordance Agent Harness: Verification-Gated Skill Orchestration [45.231685718099264]
Affordance grounding requires identifying where and how an agent should interact in open-world scenes.<n>We propose Affordance Agent Harness, a closed-loop runtime that unifies skills with an evidence store and cost control.
arXiv Detail & Related papers (2026-05-01T13:45:16Z) - Upholding Epistemic Agency: A Brouwerian Assertibility Constraint for Responsible AI [0.0]
I propose a Brouwer-inspired assertibility constraint for responsible AI.<n>In high-stakes domains, systems may assert or deny claims only if they can provide a publicly inspectable and contestable certificate of entitlement.
arXiv Detail & Related papers (2026-03-04T12:14:21Z)
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.