CHAINTRIX: A multi-pipeline LLM-augmented framework for automated smart-contract security auditing

TL;DR

Chaintrix is a comprehensive framework combining deterministic analysis and LLMs to improve the accuracy and efficiency of smart-contract security audits, significantly reducing false positives and detecting most high-severity vulnerabilities.

Contribution

It introduces a multi-pipeline LLM-augmented framework with a structured contract parser and staged verification to enhance smart-contract security auditing accuracy.

Findings

Detects 86 of 120 high-severity vulnerabilities (71.7% recall)

Achieves 100% recall in 25 audits, outperforming baseline models

Uses a structured contract representation to validate LLM claims

Abstract

Smart-contract exploits have caused billions of USD in cumulative losses, yet audits remain expensive and slow. Automated tools have emerged to close this gap, but each class has a characteristic failure mode. Static analyzers report findings that frequently fail manual triage at high rates, while large language models (LLMs) hallucinate findings that contradict the source code. Thus, we propose Chaintrix, an end-to-end auditing framework whose central architectural commitment is that every LLM-generated claim must be discharged against a deterministic structural contract representation. We introduce a Cross-Contract Interaction Model (CCIM) that parses Solidity into a structured map of function-level reads, writes, modifiers and resolved cross-contract calls. CCIM serves as the substrate against which all 12 of Chaintrix's deterministic signal engines and the parallel LLM audit pipelines operate. A staged false-positive-reduction pipeline, terminating in a Structural Verdict Engine (SVE) that applies deterministic structural checks against parsed code, filters the merged finding set, with selected high-confidence findings further validated through symbolic execution and fuzz testing. We evaluate Chaintrix on EVMbench, the smart-contract security benchmark by OpenAI, Paradigm, OtterSec. Chaintrix detects 86 of 120 high-severity vulnerabilities (71.7% recall), with 25 audits scoring 100% recall, placing Chaintrix 26 percentage points above the strongest frontier-model baseline.