Agent Flight Recorder: Tamper-Evident Audit Trails with On-Chain Anchoring for Long-Horizon Tool-Using Agents
- URL: http://arxiv.org/abs/2609.01931v1
- Date: Tue, 01 Sep 2026 22:59:08 GMT
- Title: Agent Flight Recorder: Tamper-Evident Audit Trails with On-Chain Anchoring for Long-Horizon Tool-Using Agents
- Abstract summary: Long-horizon agents execute thousands of actions, resulting in sequential failures rather than isolated errors.<n>The Agent Flight Recorder captures each agent action as a structured semantically serialized event binding eight fields from intent through execution to provenance.<n>We evaluate the system across five cumulative ablation configurations on synthetic agent workloads.
- Score: 0.6564588068252765
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Long-horizon agents execute thousands of actions, resulting in sequential failures rather than isolated errors. When a coding agent deletes a production database or a prompt injection spreads across agents, the incident raises questions of causality, authority, and non-repudiable third-party verification. The Agent Flight Recorder captures each agent action as a structured, canonically serialized event binding eight semantic fields from intent through execution to provenance. Hash chaining and Merkle batching provide tamper evidence and compact inclusion proofs. For cross-organizational disputes where no party's infrastructure qualifies as neutral ground, periodic on-chain anchoring of epoch roots lets any verifier with the disclosed payload and Merkle proof check the record independently, without pre-agreeing on a trusted intermediary. The on-chain footprint is minimal: each anchor stores a 32-byte epoch root and a back-pointer, and no event content touches the chain. We evaluate the system across five cumulative ablation configurations on synthetic agent workloads. The full system adds ~48 microseconds median per-event latency and 512 bytes per event. L2 anchoring costs $2.30 per 100K events at 100-event epochs. The full integrity stack detects edit, delete, reorder, and fork tampering at 100% with zero false positives. Structured forensic queries achieve 1.0 precision on guardrail and delegation lookups where unstructured text search yields 0.013 and 0.077 respectively.
Related papers
- Attesting Outputs and Delegation Ancestry in Multi-Agent AI Systems [3.276413627586882]
After an incident, a verifier must answer two questions.<n>Credentials establish who may act, but need not bind them to later output bytes.<n>A trusted deployer runtime signs a hash of each released output.
arXiv Detail & Related papers (2026-08-31T07:42:57Z) - VERA: Authority-Preserving Edge Revocation for Federated AI-Agent Workflows [3.06815294082031]
We introduce VERA (Verifiable Edge Revocation for Agents), a verifier-checkable revocation contract and API emitted by agent-runtime adapters as signed evidence.<n>Under disjunctive authority, revoking edge e proofss exactly invalidate T_intent(e,G) = reach(G) reach(G e, the agents whose every authorizing root path used e.<n>In a LangGraph framework-replt cells repeated 20 times yield 500compiled-framework traces and 2,000 valid signed delegation decisions.
arXiv Detail & Related papers (2026-08-30T23:39:26Z) - OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality [0.0]
OrchestraBench evaluates failure, recovery, and decomposition through a controlled, seed-reproducible failure-injection harness over templated enterprise.<n>It introduces cascade radius and per-failure-mode recovery as primary metrics and compares routing policies with bootstrap confidence intervals and paired tests.
arXiv Detail & Related papers (2026-08-05T17:27:15Z) - The LLM Proposes, the Executive Disposes: A Self-Verifying Agent Instrument that Dissociates Commitment Drift from Binding Drift in Long-Horizon Agents [0.0]
We present an agent instrument built so that verification is structural rather than post-hoc.<n>Every run invalidates itself when per-organ write-error, render-size, or salted-canary-echo floors are breached.<n>We report a clean, single-variable result on a failure every long-horizon agent suffers.
arXiv Detail & Related papers (2026-08-04T15:10:37Z) - Agent Security Needs Redefinition through a Holistic Framework [46.88917910966891]
Defenses ask whether an instruction looks malicious. Benchmarks ask whether an agent performs a harmful sounding action.<n>We operationalize contextual security through four properties that must hold jointly and be evaluated continuously across the agent's trajectory.
arXiv Detail & Related papers (2026-07-24T06:43:09Z) - Building Trust in Autonomous Commerce: A Verifiable Global Event Timeline and AI-Ready Fraud Intelligence Layer [0.0]
This paper proposes a verifiable global event timeline for agentic commerce constructed from four core components.<n>We introduce a cryptographically signed fraud marker that binds risk labels to anchored evidence through an unforgeable chain provenance.
arXiv Detail & Related papers (2026-07-21T06:22:06Z) - Fantastic Adaptive Taxonomies and How to Use Them [100.20614173157708]
AdaMAST converts execution traces into a compact, evidence-grounded failure taxonomy.<n>No code is hand-authored, no trace human-annotated.<n>In agent-system search, taxonomy-coded diagnoses of failed candidates outperform free-form.
arXiv Detail & Related papers (2026-07-17T17:41:16Z) - SNARE: Adaptive Scenario Synthesis for Eliciting Overeager Behavior in Coding Agents [40.270213696031625]
A coding agent executes a benign task as a sequence of shell, file, and network actions, any of which can quietly exceed the authorized scope while the task still completes.<n>We call this overeager behavior: the prompt is not adversarial and the run succeeds, yet an out-of-scope step can leak credentials or delete files.<n>Existing benchmarks miss it: task-completion suites credit any finished run, jailbreak suites probe adversarial prompts, and the one prior overeager benchmark applies a single fixed prompt to every agent-model pair.<n>We present SNARE, a pipeline that composes benign scenarios from reusable scope
arXiv Detail & Related papers (2026-05-27T08:14:07Z) - 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) - Governing Dynamic Capabilities: Cryptographic Binding and Reproducibility Verification for AI Agent Tool Use [0.0]
No existing security layer verifies what an AI agent can do, whether it executed what it claims, or what happened in a multi-agent interaction.<n>Existing frameworks conflate the two, enabling silent capability escalation and leaving interactions without verifiable provenance.<n>We derive three Agent Governance Requirements: capability integrity (G1), behavioral verifiability (G2), and interaction auditability (G3)<n>We validate with two crypto-agnostic instantiations -- basic (Ed25519, SHA-256; 97 us verify) and enhanced (BBS+ selective disclosure, Groth16 DV-SNARK; 13.8 ms)
arXiv Detail & Related papers (2026-03-15T11:46:57Z) - AgentSys: Secure and Dynamic LLM Agents Through Explicit Hierarchical Memory Management [47.49917373646469]
Existing defenses treat bloated memory as given and focus on remaining resilient.<n>We present AgentSys, a framework that defends against indirect prompt injection through explicit memory management.
arXiv Detail & Related papers (2026-02-07T06:28:51Z) - The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search [58.8834056209347]
Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety guardrails to elicit harmful outputs.<n>We introduce the Correlated Knowledge Attack Agent (CKA-Agent), a dynamic framework that reframes jailbreaking as an adaptive, tree-structured exploration of the target model's knowledge base.
arXiv Detail & Related papers (2025-12-01T07:05:23Z)
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.