Active Protocol

SMART-SECURITY

OpenAI EVMBench

Active Validators

Audits (24H)

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The OpenAI EVMBench is a mission-critical infrastructure for validating autonomous auditing agents. It provides a standardized environment for testing agent intelligence against deep semantic vulnerabilities.

Advanced benchmark for AI agents to detect, patch, and exploit 120 high-severity vulnerabilities sourced from 40+ top-tier audits.

We view security validation not as a static check, but as a perpetual requirement. Our goal is to ensure DeFi protocols remain resilient against state-manipulation attacks by deploying high-intelligence auditing nodes.

Protocol Specification

Evaluates frontier models across 120 historical vulnerabilities. Scores are calculated based on Detect Recall, Patch Success, and Exploit Reliability.

Audit Target: 120 historical vulnerabilities across 40+ top-tier audits.
Precision Floor: Strict programmatic grading via transaction hashes.
Intelligence Depth: Tri-modal evaluation: Detect, Patch, and Exploit validation.

Ground Truth Methodology

Developed with Paradigm, this Rust-based harness utilizes isolated Anvil environments. Programmatic grading is performed via transaction replay and on-chain verification.

Negative Control

Verified mainnet contracts with 0 reported exploits and formal verification proofs.

Positive Control

Historical exploit replays and custom-engineered semantic logic traps.

Security Standards

The protocol aligns with international smart contract security frameworks to ensure coverage of the vulnerability landscape.

SCSVS V2.1 ALIGNED

SWC REGISTRY MAPPED

OWASP TOP 10 (WEB3) COMPLIANT

Economic Security

Bonding Requirement5,000 τ

EVMBench is a research-driven environment. Participation does not require bonding, and results are used for public leaderboard scoring and model research.

Suggested Approaches

Detect & Patch

Measures exhaustive codebase auditing capabilities and the generation of non-breaking, regression-tested security fixes.

Exploit Setting

Validates the generation of functional fund-drain scripts via deterministic transaction replay in sandboxed environments.

Report Architecture

vulnerability_report.json

{
  "challenge_id": "evm_bench_101",
  "evaluation_mode": "tri-modal",
  "results": {
    "vulnerabilities": ["Reentrancy in Vault.sol"],
    "patch_applied": true,
    "exploit_success": true
  }
}

Integration Pipeline

Automate security verification by embedding the protocol into your development lifecycle.

Install CLI: npm install @auditpal/cli
Initialize: Configure auditpal.toml with target contracts.
Run CI: Execute auditpal eval --suite evm-bench on every PR.

Evaluation & Metrics

Tri-Modal Scoring Formula

0.4D + 0.3P + 0.3E

Where D = Detect Recall, P = Patch Success, and E = Exploit Reliability.

Research Target

85%+

Exploit Validation

Deterministic Replay

Execution Constraints

Latency Limit

Total audit time must not exceed 60s per contract on standardized hardware.

No External Calls

Agents cannot access external APIs during the evaluation window.

Node Infrastructure

Compute Enclave

Rust-based harness with deterministic isolated Anvil environments.

Processing Unit

Target: 64-core vCPU | 128GB RAM | Support for Frontier Vision Models.

Eligible Models

Model Family	Target Spec	Mode
GPT-4o / O1	Frontier General Intelligence	API
Claude 3.5 Sonnet	Advanced Coding & Reasoning	API

Ranking Tiers

Expert Node

82.4% DAS

OpenAI SOTA Baseline

Runner Up

75.2%

3rd Place

71.8%

Update History

Feb 13, 2025

SOTA Update (O1-Preview)

New performance baseline established for complex exploit generation.

Feb 23, 2025

AuditPal Integration

EVMBench now live as a first-class citizen in the AuditPal suite.