mlsanityData to 14 Oct 2026

PACE: Policy-Attested Contract Execution for Safe AI Agents in Decentralized Finance

arXiv 2608.17220 ↗First posted 18 Aug 2026cs.CR cs.AIcited by 1

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

Autonomous AI agents are emerging as interfaces for decentralized finance (DeFi) actions such as swaps, lending operations, and yield management. Because these agents rely on large language models (LLMs) to plan transactions, they inherit the LLM's susceptibility to prompt injection and lack of mechanisms to bind a verifier's approval to the exact transaction ultimately submitted on-chain. We present PACE (Policy-Attested Contract Execution), a transaction-level authorization framework that interposes between an LLM-based agent and on-chain execution. PACE introduces typed transaction intents, a deterministic policy verifier, and signed Policy Decision Records (PDRs) that cryptographically bind the approved intent, policy, and simulation report to the exact execution bytes, with replay and expiration protection. A Solidity smart account enforces PDR signatures on-chain with a measured overhead of 29,826-31,822 gas. We evaluate PACE against six baselines on 40 tasks spanning four attack categories plus benign utility (2,800 trials, 10 seeds). In our deterministic sandbox, PACE achieves a 0.00 unsafe execution rate and 0.00 false-positive rate on benign tasks, compared to 0.80 for the unguarded baseline. Ablation studies identify permissive policy settings (+57.5 pp) and the touched-contract allowlist (+12.5 pp) as the dominant safety components. To test whether the same deterministic floor holds for real model outputs, the artifact additionally provides a three-model live-LLM evaluation over the full task suite with repeated runs. A mainnet-fork harness is included for archive-RPC deployments, but fork results are reported only when the corresponding artifacts are generated. These auxiliary studies are separate from, and never substitute for, the deterministic benchmark. We frame our claims as logic-level safety within a reproducible benchmark rather than deployment-ready DeFi security.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 18 of its 35 references that are in the map. First posted on arXiv 18 Aug 2026.

Builds on

18 of 35 references.

Closest ancestors · 1

Same direction, newest first

  1. 2026Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital28 Apr

Other references · 17

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  4. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  5. 2023Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injectioncited by 1,443
  6. 2022Ignore Previous Prompt: Attack Techniques For Language Modelscited by 832
  7. 2023Identifying the Risks of LM Agents with an LM-Emulated Sandboxcited by 548
  8. 2024InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agentscited by 538
  9. 2024StruQ: Defending Against Prompt Injection with Structured Queriescited by 375
  10. 2023Formalizing and Benchmarking Prompt Injection Attacks and Defensescited by 364
  11. 2019Slither: A Static Analysis Framework For Smart Contractscited by 89
  12. 2019Manticore: A User-Friendly Symbolic Execution Framework for Binaries and Smart Contractscited by 37
5 more
  1. 2022SoK: Decentralized Finance (DeFi) Attackscited by 28
  2. 2021Quantifying Blockchain Extractable Value: How dark is the forest?cited by 15
  3. 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundariescited by 13
  4. 2020High-Frequency Trading on Decentralized On-Chain Exchangescited by 10
  5. 2025Giving AI Agents Access to Cryptocurrency and Smart Contracts Creates New Vectors of AI Harmcited by 3

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Citing papers per year: 2026: 1.

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